JP2005503148A - Molecular interaction site of RNase PRNA and method for modulating the same site - Google Patents

Abstract

A polynucleotide comprising a molecular interaction site of RNase P RNA having a specific secondary structure is provided. Also provided are methods for using such polynucleotides to virtually or realistically screen combinatorial libraries of compounds that bind to the polynucleotides. Also provided are methods of modulating the activity of RNase P RNA or prokaryotic cells containing it by compounds identified by such virtual or realistic screening.

Description

【００７７】
（配列番号１）（太字ヌクレオチドは好ましい塩基対合(basepairing)を表示する）を含む。第２ポリヌクレオチドは、好ましくは、１４ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：５ヌクレオチドを含むダングリング領域、４ヌクレオチドを含む第４ステムの第２側、及び５ヌクレオチドを含む第１ステムの第２側を有する二本鎖ＲＮＡを形成する。好ましくは、第２ポリヌクレオチドは、配列：
【００７８】
【化２】

【００７９】
（配列番号２）（太字ヌクレオチドは好ましい塩基対合を表示する）を含む。部位１は、図１に示すように、大腸菌(E.coli)中に存在する。
部位２は、第１、第２及び第３ポリヌクレオチドを含む、ＲＮＡの領域を含む。第１ポリヌクレオチドは、約６ヌクレオチド〜約１６ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：約１ヌクレオチド〜約３ヌクレオチドを含むダングリング領域、及び約４ヌクレオチド〜約１０ヌクレオチドを含む第１ステムの第１側、この第１ステムの第１側には約１ヌクレオチド〜約３ヌクレオチドを含むバルジが任意に存在する、を有する二本鎖ＲＮＡを形成する。第２ポリヌクレオチドは、約１３ヌクレオチド〜約３４ヌクレオチドを含み、該ポリヌクレオチドの部分は下記特徴（５’〜３’）：約４ヌクレオチド〜約１０ヌクレオチドを含む第１ステムの第２側、この第１ステムの第２側には約１ヌクレオチド〜約３ヌクレオチドを含むバルジが任意に存在する、約４ヌクレオチド〜約１０ヌクレオチドを含むバルジ、約３ヌクレオチド〜約９ヌクレオチドを含む第２ステムの第１側、及び約１ヌクレオチド〜約２ヌクレオチドを含むダングリング領域を有する二本鎖ＲＮＡを形成する。第３ポリヌクレオチドは、約５ヌクレオチド〜約１３ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：約１ヌクレオチド〜約２ヌクレオチドを含むダングリング領域、約３ヌクレオチド〜約９ヌクレオチドを含む第２ステムの第２側、及び約１ヌクレオチド〜約２ヌクレオチドを含むダングリング領域を有する二本鎖ＲＮＡを形成する。
【００８０】
部位２に関して、第１ポリヌクレオチドは、好ましくは、１１ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：２ヌクレオチドを含むダングリング領域、及び７ヌクレオチドを含む第１ステムの第１側、この第１ステムの第１側の第５ヌクレオチドと第６ヌクレオチドとの間に２ヌクレオチドを含むバルジが存在する、を有する二本鎖ＲＮＡを形成する。好ましくは、該第１ポリヌクレオチドは、配列：
【００８１】
【化３】

【００８２】
（配列番号３）（太字ヌクレオチドは好ましい塩基対合を表示する）を含む。第２ポリヌクレオチドは、好ましくは、２３ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：７ヌクレオチドを含む第１ステムの第２側、この第１ステムの第２側の第５ヌクレオチドと第６ヌクレオチドとの間には２ヌクレオチドを含むバルジが存在する、７ヌクレオチドを含むバルジ、６ヌクレオチドを含む第２ステムの第１側、及び１ヌクレオチドを含むダングリング領域を有する二本鎖ＲＮＡを形成する。好ましくは、第２ポリヌクレオチドは、配列：
【００８３】
【化４】

【００８４】
（配列番号４）（太字ヌクレオチドは好ましい塩基対合を表示する）を含む。第３ポリヌクレオチドは、好ましくは、８ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：１ヌクレオチドを含むダングリング領域、６ヌクレオチドを含む第２ステムの第２側、及び１ヌクレオチドを含むダングリング領域を有する二本鎖ＲＮＡを形成する。好ましくは、第３ポリヌクレオチドは、配列：
【００８５】
【化５】

【００８６】
（配列番号５）（太字ヌクレオチドは好ましい塩基対合を表示する）を含む。部位２は、図１に示すように、大腸菌(E.coli)中に存在する。
部位３は、第１及び第２ポリヌクレオチドを含むＲＮＡ領域を含む。第１ポリヌクレオチドは、約１０ヌクレオチド〜約２６ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：約１ヌクレオチド〜約３ヌクレオチドを含むダングリング領域、約２ヌクレオチド〜約６ヌクレオチドを含む第１ステムの第１側、約３ヌクレオチド〜約９ヌクレオチドを含む内部ループの第１側、約３ヌクレオチド〜約６ヌクレオチドを含む第２ステムの第１側、及び約１ヌクレオチド〜約２ヌクレオチドを含むダングリング領域を有する二本鎖ＲＮＡを形成する。第２ポリヌクレオチドは、約１０ヌクレオチド〜約２７ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：約３ヌクレオチド〜約９ヌクレオチドを含む第２ステムの第２側、約３ヌクレオチド〜約７ヌクレオチドを含む内部ループの第２側、約２ヌクレオチド〜約６ヌクレオチドを含む第１ステムの第２側、及び約２ヌクレオチド〜約５ヌクレオチドを含むダングリング領域を有する二本鎖ＲＮＡを形成する。
【００８７】
部位３に関して、第１ポリヌクレオチドは、好ましくは、１９ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：２ヌクレオチドを含むダングリング領域、４ヌクレオチドを含む第１ステムの第１側、６ヌクレオチドを含む内部ループの第１側、６ヌクレオチドを含む第２ステムの第１側、及び１ヌクレオチドを含むダングリング領域を有する二本鎖ＲＮＡを形成する。好ましくは、第１ポリヌクレオチドは、配列：
【００８８】
【化６】

【００８９】
（配列番号６）（太字ヌクレオチドは好ましい塩基対合を表示する）を含む。第２ポリヌクレオチドは、好ましくは、１８ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：６ヌクレオチドを含む第２ステムの第２側、５ヌクレオチドを含む内部ループの第２側、４ヌクレオチドを含む第１ステムの第２側、及び３ヌクレオチドを含むダングリング領域を有する二本鎖ＲＮＡを形成する。好ましくは、第２ポリヌクレオチドは、配列：
【００９０】
【化７】

【００９１】
（配列番号７）（太字ヌクレオチドは好ましい塩基対合を表示する）を含む。部位３は、図１に示すように、大腸菌(E.coli)中に存在する。
部位４は、約１２ヌクレオチド〜約３４ヌクレオチドを含むポリヌクレオチドを含むＲＮＡ領域を含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：約３ヌクレオチド〜約９ヌクレオチドを含むステムの第１側、このステムの第１側には約２ヌクレオチド〜約５ヌクレオチドを含む内部ループの第１側が存在する、約２ヌクレオチド〜約６ヌクレオチドを含む末端ループ、約３ヌクレオチド〜約９ヌクレオチドを含む該ステムの第２側、このステムの第２側には約１ヌクレオチド〜約３ヌクレオチドを含む該内部ループの第２側が存在する、及び約１ヌクレオチド〜約２ヌクレオチドを含むダングリング領域を有する二本鎖ＲＮＡを形成する。
【００９２】
部位４に関して、ＲＮＡの領域は、好ましくは、２２ヌクレオチドを含むポリヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：６ヌクレオチドを含むステムの第１側、このステムの第１側の第３ヌクレオチドと第４ヌクレオチドとの間には３ヌクレオチドを含む内部ループの第１側が存在する、４ヌクレオチドを含む末端ループ、６ヌクレオチドを含む該ステムの第２側、このステムの第２側の第３ヌクレオチドと第４ヌクレオチドとの間には２ヌクレオチドを含む該内部ループの第２側が存在する、及び１ヌクレオチドを含むダングリング領域を有する二本鎖ＲＮＡを形成する。好ましくは、該ポリヌクレオチドは、配列：
【００９３】
【化８】

【００９４】
（配列番号８）（太字ヌクレオチドは好ましい塩基対合を表示する）を含む。部位４は、図２に示すように、枯草菌(B subtilis)中に存在する。
部位５は、第１、第２、第３、第４及び第５ポリヌクレオチドを含むＲＮＡ領域を含む。第１ポリヌクレオチドは約３ヌクレオチド〜約９ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：約２ヌクレオチド〜約６ヌクレオチドを含む第１ステムの第１側、及び約１ヌクレオチド〜約３ヌクレオチドを含む第２ステムの第１側を有する二本鎖ＲＮＡを形成する。第２ポリヌクレオチドは、約３ヌクレオチド〜約８ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：約１ヌクレオチド〜約３ヌクレオチドを含む第２ステムの第２側、及び約２ヌクレオチド〜約５ヌクレオチドを含む第３ステムの第１側を有する二本鎖ＲＮＡを形成する。第３ポリヌクレオチドは、約７ヌクレオチド〜約１８ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：約２ヌクレオチド〜約５ヌクレオチドを含む第３ステムの第２側、この第３ステムの第２側には約１ヌクレオチド〜約２ヌクレオチドを含むバルジが任意に存在する、約１ヌクレオチド〜約３ヌクレオチドを含む第４ステムの第１側、約１ヌクレオチド〜約３ヌクレオチドを含むバルジ、及び約２ヌクレオチド〜約５ヌクレオチドを含む第５ステムの第１側を有する二本鎖ＲＮＡを形成する。第４ポリヌクレオチドは約８ヌクレオチド〜約２０ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：約２ヌクレオチド〜約５ヌクレオチドを含む第５ステムの第２側、約３ヌクレオチド〜約７ヌクレオチドを含むバルジ、約１ヌクレオチド〜約３ヌクレオチドを含む第６ステムの第１側、及び約２ヌクレオチド〜約５ヌクレオチドを含むダングリング領域を有する二本鎖ＲＮＡを形成する。第５ポリヌクレオチドは、約５ヌクレオチド〜約１５ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：約１ヌクレオチド〜約３ヌクレオチドを含むダングリング領域、約１ヌクレオチド〜約３ヌクレオチドを含む第６ステムの第２側、約１ヌクレオチド〜約３ヌクレオチドを含む第４ステムの第２側、及び約２ヌクレオチド〜約６ヌクレオチドを含む第１ステムの第２側を有する二本鎖ＲＮＡを形成する。
【００９５】
部位５に関して、第１ポリヌクレオチドは、好ましくは、６ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：４ヌクレオチドを含む第１ステムの第１側、及び２ヌクレオチドを含む第２ステムの第１側を有する二本鎖ＲＮＡを形成する。好ましくは、第１ポリヌクレオチドは、配列：
【００９６】
【化９】

【００９７】
（太字ヌクレオチドは好ましい塩基対合を表示する）を含む。第２ポリヌクレオチドは、好ましくは、５ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：２ヌクレオチドを含む第２ステムの第２側、及び３ヌクレオチドを含む第３ステムの第１側を有する二本鎖ＲＮＡを形成する。好ましくは、第２ポリヌクレオチドは、配列：
【００９８】
【化１０】

【００９９】
（太字ヌクレオチドは好ましい塩基対合を表示する）を含む。第３ポリヌクレオチドは、好ましくは、１０ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：３ヌクレオチドを含む第３ステムの第２側、この第３ステムの第２側の第２ヌクレオチドと第３ヌクレオチドとの間には１ヌクレオチドを含むバルジが存在する、２ヌクレオチドを含む第４ステムの第１側、１ヌクレオチドを含むバルジ、及び３ヌクレオチドを含む第５ステムの第１側を有する二本鎖ＲＮＡを形成する。好ましくは、第３ポリヌクレオチドは、配列：
【０１００】
【化１１】

【０１０１】
（配列番号９）（太字ヌクレオチドは好ましい塩基対合を表示する）を含む。第４ポリヌクレオチドは、好ましくは、１３ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：３ヌクレオチドを含む第５ステムの第２側、５ヌクレオチドを含むバルジ、２ヌクレオチドを含む第６ステムの第１側、及び３ヌクレオチドを含むダングリング領域を有する二本鎖ＲＮＡを形成する。好ましくは、第４ポリヌクレオチドは、配列：
【０１０２】
【化１２】

【０１０３】
（配列番号１０）（太字ヌクレオチドは好ましい塩基対合を表示する）を含む。第５ポリヌクレオチドは、好ましくは、１０ヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：２ヌクレオチドを含むダングリング領域、２ヌクレオチドを含む第６ステムの第２側、２ヌクレオチドを含む第４ステムの第２側、及び４ヌクレオチドを含む第１ステムの第２側を有する二本鎖ＲＮＡを形成する。好ましくは、第５ポリヌクレオチドは、配列：
【０１０４】
【化１３】

【０１０５】
（配列番号１１）（太字ヌクレオチドは好ましい塩基対合を表示する）を含む。部位５は、図２に示すように、枯草菌(B.subtilis)中に存在する。
部位６は、約１３ヌクレオチド〜約３４ヌクレオチドを含むポリヌクレオチドを含むＲＮＡ領域を含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：約２ヌクレオチド〜約５ヌクレオチドを含むダングリング領域、約２ヌクレオチド〜約５ヌクレオチドを含むステムの第１側、約６ヌクレオチド〜約１６ヌクレオチドを含む末端ループ、約２ヌクレオチド〜約５ヌクレオチドを含む該ステムの第２側、及び約１ヌクレオチド〜約３ヌクレオチドを含むダングリング領域を有する二本鎖ＲＮＡを形成する。
【０１０６】
部位６に関して、ＲＮＡの領域は、好ましくは、２２ヌクレオチドを含むポリヌクレオチドを含み、該ポリヌクレオチドの部分は、下記特徴（５’〜３’）：３ヌクレオチドを含むダングリング領域、３ヌクレオチドを含むステムの第１側、１１ヌクレオチドを含む末端ループ、３ヌクレオチドを含む該ステムの第２側、及び２ヌクレオチドを含むダングリング領域を有する二本鎖ＲＮＡを形成する。好ましくは、該ポリヌクレオチドは、配列：
【０１０７】
【化１４】

【０１０８】
（配列番号１２）（太字ヌクレオチドは好ましい塩基対合を表示する）を含む。部位６は図２に示すように、枯草菌(B.subtilis)中に存在する。
【図面の簡単な説明】
【０１０９】
【図１】図１は、部位１、２及び３を示す大腸菌(E.coli)ＲＮアーゼＰ ＲＮＡの代表的構造を示す。
【図１Ａ】図１Ａは、部位１、２及び３を示す大腸菌(E.coli)ＲＮアーゼＰ ＲＮＡの代表的構造を示す。
【図１Ｂ】図１Ｂは、部位１、２及び３を示す大腸菌(E.coli)ＲＮアーゼＰ ＲＮＡの代表的構造を示す。
【図１Ｃ】図１Ｃは、部位１、２及び３を示す大腸菌(E.coli)ＲＮアーゼＰ ＲＮＡの代表的構造を示す。
【図２】図２は、部位４、５及び６を示す枯草菌(B.subtilis)ＲＮアーゼＰ ＲＮＡの代表的構造を示す。
【図２Ａ】図２Ａは、部位４、５及び６を示す枯草菌(B.subtilis)ＲＮアーゼＰ ＲＮＡの代表的構造を示す。
【図２Ｂ】図２Ｂは、部位４、５及び６を示す枯草菌(B.subtilis)ＲＮアーゼＰ ＲＮＡの代表的構造を示す。
【図２Ｃ】図２Ｃは、部位４、５及び６を示す枯草菌(B.subtilis)ＲＮアーゼＰ ＲＮＡの代表的構造を示す。【Technical field】
[0001]
Field of Invention
The present invention identifies molecular interaction sites of RNase P RNA, virtual or realistic screening of compounds that bind to the same site, and RNase P RNA activity by the compounds identified in virtual and realistic screening. Regarding modulation.
[0002]
Background of the Invention
Ribonuclease P (RNase P) is an endoribonuclease responsible for removal of the leader sequence from the mature tRNA precursor at the 5 ′ end of the tRNA. Altman et al., FASEB J., 1993, 7, 7-14 and Pace et al., J. Bacteriol., 1995, 177, 1919-1928. RNase P has at least its catalytic function in bacteria depending on the protein. Rather, it is a ribonucleoprotein performed by its RNA component (RNase P RNA). Guerrier-Takada et al., Cell, 1983, 35, 849-857. Another feature of RNase P RNA is its ability to recognize the tertiary structure of its pre-tRNA substrate. Kahle et al., EMBO J., 1990, 9, 1929-1937. The secondary structure of the bacterial RNase P RNA was inferred from a primary comparative analysis of the sequence (James et al., Cell, 1988, 52, 19- 26), fine-tuned when additional sequences were available (Haas et al., Science, 1991, 254, 853-856; Haas et al., Proc. Natl. Acad. Sci. USA, 1994, 91, 2527-2531; Brown et al., Nutl. Acids Res., 1993, 21, 671-679). Furthermore, the induction of the three-dimensional architecture of bacterial RNase P RNA from E. coli and Bacillus subtilis is described in Massire et al., J. Mol. Biol., 1998, 279, 773. -793, which is hereby incorporated by reference in its entirety.
[0003]
Recent advances in genomics, molecular biology and structural biology have emphasized how RNA molecules are involved or control many of the events required for protein expression in cells. RNA molecules do not simply function as intermediates, but actively regulate their own transcription from DNA, splicing and editing mRNA and tRNA molecules, synthesizing peptide bonds in ribosomes, and nascent proteins Catalyze migration to cell membranes and fine-tune the translation speed of messages. RNA molecules can introduce a variety of unique structural motifs that provide the necessary framework to perform these functions.
[0004]
“Small” molecular therapeutics that specifically bind to the constructed RNA molecule are organic chemical molecules that are not polymers. “Small” molecular therapeutics are, for example, the most potent naturally occurring antibiotics. For example, aminoglycosides and macrolide antibiotics act by binding to defined regions of the ribosomal RNA (rRNA) structure and preventing RNA conformational changes necessary for protein synthesis. This is a “small” molecule. Furthermore, changes in the conformation of RNA molecules have been found to regulate the rate of transcription and translation of mRNA. Small molecules are generally less than 10 kDa.
[0005]
Applicants believe that an RNA molecule or group of related RNA molecules has regulatory regions that are utilized by the cell for protein synthesis. Cells are thought to exert control over both the timing and amount of protein synthesized by direct specific interactions with RNA. This idea contradicts the impression obtained by reading scientific papers on gene regulation that are highly concentrated in transcription. The process of RNA maturation, transport, subcellular localization and translation is rich in RNA recognition sites that provide good opportunities for drug binding. Applicant's invention relates, inter alia, to finding these sites of RNA molecules, particularly RNase P RNA, in the microbial genome. Applicant's invention further produces a large number of chemical entities, realistically or virtually, with respect to their ability to bind and / or modulate these drug binding sites and / or Or use combinatorial chemistry to screen.
[0006]
The determination of possible conformations of nucleic acids and their associated structural motifs can be performed, for example, by studying RNA catalysis, RNA-RNA interactions, RNA-nucleic acid interactions, RNA-protein interactions, and small molecule recognition by nucleic acids. Like to give insight into the field. Four general approaches for forming model conformations of RNA have been demonstrated in the literature. All of these use esoteric molecular modeling and computational algorithms for the simulation of folding and tertiary interactions within the target nucleic acid, such as RNA. Westhof and Altman (Proc. Natl. Acad. Sci., 1994, 91, 5133, which is incorporated herein in its entirety) from E. coli by an interactive computer modeling protocol. Of RNase P catalytic RNA subunit, M1 RNA. Mueller and Brimacombe (J. Mol. Biol., 1997, 271, 524) have used a series of important studies in the field of cryogenic electron microscopy (cryo-EM) and biochemical research on ribosomal RNA to produce the E. coli 16S ribosome. A three-dimensional model of RNA is being constructed. Methods for modeling nucleic acid hairpin motifs have been developed based on a set of reduced coordinates representing nucleic acid structure and a sampling algorithm that balances the structure using Monte Carlo (MC) simulation ( Tung, Biophysical J., 1997,72,876, which is incorporated herein in its entirety). The MC-SYM program is yet another approach to predict RNA conformation using constraint-satisfaction methods (Major et al., Proc. Natl. Acad. Sci., 1993, 90, 9408). . The MC-SYM program is a constraint-satisfaction-based algorithm that searches the conformation space for all models that satisfy the query input constraints, for example, Cedergren et al., RNA Structure And Function, 1998. , Cold Spring Harbor Lab. Press, p.37-75. According to this method, RNA conformation is created by stepwise addition of nucleotides having one or several different conformations to a growing oligonucleotide model.
[0007]
Westoff and Altman (Proc. Natl. Acad. Sci., 1994, 91, 5133) have described the catalytic RNA subunit of RNase P from E. coli, M1 RNA, according to an interactive computer modeling protocol. Describes the creation of a three-dimensional model. This modeling protocol incorporated data from chemical and enzymatic defense experiments, phylogenetic analysis, mutant activity studies, and kinetics of reactions catalyzed by substrate binding to M1 RNA. . Modeling was for the most part performed as described in the literature (Westhof et al., In “Theoretical Biochemistry and Molecular Biophysics”, Beveridge and Lavery (Eds.), Adenine, NY, 1990, 399). In general, starting from the primary sequence of M1 RNA, secondary stem-loop structures and other elements were created. Subsequent assembly of these elements into 3D structures using computer graphics stations and FRODO (Jones, J. Appl. Crystallogr., 1978, 11, 268) followed by refinement using NUCLIN-NUCLSQ ) Provided an RNA model with the correct geometry, the absence of bad contacts and the appropriate stereochemistry. The model created in this way has been found to be consistent with most of the empirical data for M1 RNA and provides a hypothesis for the mechanism of action of RNase P. However, since the model created by this method has not been well analyzed, the structure is determined by X-ray crystallography.
[0008]
Mueller and Brimacombe (J. Mol. Biol., 1997, 271, 524, which is incorporated herein in its entirety) uses a modeling program called ERNA-3D to develop a three-dimensional model of E. coli 16S ribosomal RNA. I am making it. This program allows conformations such as A-form RNA helices and single-stranded regions by single-stranded dynamic docking to fit the electron density obtained from low-resolution diffraction data. Is made. After the helical element is determined and positioned in the model, the placement of the single stranded region is adjusted to meet any known biochemical constraints, such as RNA-protein cross-linking and footprinting data. Yes.
[0009]
Methods for modeling nucleic acid hairpin motifs have been developed based on a set of reduced coordinates representing the nucleic acid structure and a sampling algorithm that equilibrates the structure using Monte Carlo (MC) simulation (Tung, Biophysical J ., 1997, 72, 876, which is incorporated herein in its entirety). The stem region of a nucleic acid can be appropriately modeled by using standard canonical duplex formation. An algorithm was created that could form a single stranded loop structure with a pair of fixed ends using a set of reduced coordinates. This allows an effective structural sampling of the loop in the conformation space. Combining this algorithm with a modified Metropolis Monte Carlo algorithm provides a structure simulation package that simplifies the study of nucleic acid hairpin structures by computer means. Once the RNA subdomains have been identified, they can be stabilized as needed by the methods disclosed in US Pat. No. 5,712,096.
[0010]
X-ray crystallography is a very powerful method that allows the determination of several secondary and tertiary structures of biopolymer targets (Erikson et al., Ann. Rep. In Med. Chem., 1992, 27, 271-289), this method is an expensive tool and can be very difficult to achieve. Crystallization of biopolymers is extremely challenging but difficult to perform with adequate resolution and is often considered a technique similar to science. Further confounding the usefulness of X-ray crystal structures in the drug development process is that crystallography cannot reveal the insight into the liquid phase and hence the biologically relevant structure of the target in question That is. Several analyzes of the nature and strength of the interaction between a ligand (agonist, antagonist or inhibitor) and its target are described in ELISA (Kemeny and Challacombe, in ELISA and oher Solid Phase Immunoassays: 1988), radioligand binding assay (Berson et al., Clin. 1968; Chard, in “An Introduction to Radioimmunoassay and Related Techniques”, 1982), surface plasmon resonance (Karlsson et al., 1991, Jonsson et al., Biotechniquws, 1991), or scintillation approximation assay (Udenfriend et al., Anal. Biochem., 1987), all of which have been cited previously. Radioligand binding assays are usually only useful when assessing competitive binding of unknowns at the binding site for radioligand binding and further require the use of radioactivity. The surface plasmon resonance method can be used more directly, but is also very expensive. Conventional biochemical assays for binding kinetics and dissociation and binding constants are also useful in elucidating the nature of target-ligand interactions.
[0011]
Thus, one aspect of the invention identifies molecular interaction sites in RNase P RNA. These molecular interaction sites that make up the secondary structural elements are likely to cause significant therapeutic, regulatory or other interactions with “small” molecules and the like. Another aspect of the invention is to compare the molecular interaction site of RNase P RNA with the compounds proposed for interaction therewith.
[0012]
Yet another aspect of the present invention is the establishment of a database of numerical representations of the three-dimensional structure of the molecular interaction site of RNase P RNA. Such a database library is a powerful tool for elucidating and predicting the structure of molecular interaction sites and the interactions between molecular interaction sites and possible ligands. Another aspect of the invention is a general approach for screening combinatorial libraries containing individual compounds or mixtures of compounds against RNase P RNA to determine which elements of the library bind to the target. Is to provide a practical way.
[0013]
Summary of the Invention
The present invention relates to the identification of molecular interaction sites of RNase P RNA that contain specific secondary structures.
The present invention further relates to nucleic acid molecules, polynucleotides or oligonucleotides containing molecular interaction sites that can be used to virtually or realistically screen combinatorial libraries of compounds that bind to molecular interaction sites. Related.
The invention further relates to a computer readable medium comprising a three-dimensional representation of the structure of the molecular binding site.
[0014]
The invention further relates to the modulation of RNase P RNA activity by contacting RNase P RNA or prokaryotic cells containing it with a compound identified in such a virtual or realistic screen.
The present invention also relates to the modulation of prokaryotic cell proliferation comprising contacting the prokaryotic cell with a compound identified in such a virtual or realistic screen.
[0015]
DESCRIPTION OF PREFERRED EMBODIMENTS OF THE INVENTION
The present invention relates, inter alia, to the identification of molecular interaction sites of RNase P RNA. Such molecular interaction sites include secondary structures that can interact with cellular components, such as factors and proteins, necessary for translation and other cellular processes. Nucleic acid molecules or polynucleotides containing molecular interaction sites can be used to virtually or realistically screen combinatorial libraries of compounds that bind to them. Since compounds identified by such screening are used to modulate the activity of RNase P RNA, such compounds may be used to modulate, ie inhibit or stimulate, prokaryotic cell proliferation. Can be used. Therefore, it is possible to identify novel drugs, agricultural chemicals, industrial chemicals, etc. that act via modulation of RNase P RNA.
[0016]
It is preferable to integrate several methods and protocols in order to identify potent drugs and other biologically useful compounds. Useful for drugs, veterinary drugs, agricultural chemicals, pesticides, herbicides, fungicides, industrial chemicals, laboratory chemicals, and pollution prevention, industrial biochemistry and biocatalytic systems Many other active compounds can be identified by embodiments of the present invention. A novel combination of several means gives the method of the present invention great power and versatility. As described in more detail herein, it is preferred in some embodiments to integrate several processes developed by the assignee of the present application, but other methodologies are sufficiently effective with the present invention. It should be recognized that it can be integrated into. Thus, although it is highly advantageous to determine the molecular binding site on RNase P RNA in accordance with the teachings of the present invention, the ligand and ligand mixture and other RNase P RNAs identified as important The interaction can greatly benefit from other aspects of the invention. All such combinations are within the scope of the present invention.
[0017]
One aspect of Applicants' invention relates to the identification of secondary structures in RNase P RNA, called “molecular interaction sites”. As used herein, a “molecular interaction site” is a region of RNase P RNA that has a secondary structure. Molecular interaction sites can be conserved among multiple different taxonomic species of RNase P RNA. The molecular interaction site is contained within a large RNA molecule and is small, preferably less than 200 nucleotides, preferably less than 150 nucleotides, preferably less than 70 nucleotides, preferably less than 50 nucleotides, or less than 30 nucleotides, independent Is a functional subdomain folded into Molecular interaction sites can contain both single-stranded and double-stranded regions. Thus, molecular interaction sites can be interacted with and otherwise with “small” molecules and are “small” in therapeutic and other applications, such as oligonucleotides and other compounds. It is expected to serve as a site for interaction with molecules and oligomers. Molecular interaction sites further include pockets for binding small molecules, drugs and the like.
[0018]
The molecular interaction site is present at least in the RNase P RNA. It will be appreciated that, according to some embodiments of the invention, RNase P RNA having molecular interaction site (s) can be derived from a number of sources. Accordingly, a compound capable of identifying such RNase P RNA by any means, translating it into a three-dimensional representation, and interacting with RNase P RNA to modulate the RNase P RNA. Can be used to identify. In some embodiments, the molecular reciprocal site identified in the RNase P RNA is not present in eukaryotes, particularly humans, and thus is not toxic to humans, and prokaryotic RNase P RNA is It can serve as a “small” molecular binding site while simultaneously modulating.
[0019]
Molecular interaction sites can be identified by any means known to those skilled in the art. In some embodiments of the invention, the molecular interaction sites in RNase P RNA are identified by the general methods described in International Publication No. WO 99/58719, which is incorporated herein in its entirety. Is done. Briefly, the target RNase P RNA nucleotide sequence is selected from known sequences. Any RNase P RNA nucleotide sequence can be selected. The nucleotide sequence of the target RNase P RNA is compared to the nucleotide sequence of multiple RNase P RNAs from different taxonomic species. At least one sequence region is identified that is effectively conserved in the plurality of RNase P RNAs and the target RNase P RNA. Such conserved regions are tested to determine whether any secondary structure is present, and such secondary structures are identified with respect to conserved regions having secondary structures.
[0020]
According to some embodiments of the invention, the nucleotide sequence of the target RNase P RNA is compared to the nucleotide sequences of multiple corresponding RNase P RNAs from different taxonomic species. The initial selection of a particular target nucleic acid can be based on any functional criteria. For example, RNase P RNAs known to be involved in pathogenic genomes, such as bacteria and yeast, are specific targets. Pathogenic bacteria and yeast are well known to those skilled in the art. Other RNase P RNA targets can be determined independently or can be selected from publicly available prokaryotic gene databases known to those skilled in the art. The database includes, for example, Online Mendelian Inheritance in Man (OMIM), the Cancer Genome Anomaly Project (CGAP), GenBank, EMBL, PIR, SWISS-PROT, and the like. OMIM, a database of disease-related gene mutations, was developed in part for the National Center for Biotechnology Information (NCBI). OMIM is, for example, ncbi. nlm. nih. Gov / Omim / can be accessed via the global web of the Internet. CGAP, an interdisciplinary program that establishes the information and technology tools necessary to decipher the molecular anatomy of cancer cells, for example, ncbi. nlm. nih. Gov / ncicgap / can be accessed via the global web of the Internet. Some of these databases may contain complete or partial nucleotide sequences. In addition, RNase P RNA targets can be selected from private gene databases. Alternatively, RNase P RNA targets can be selected from available publications or can be determined specifically for use in connection with the present invention.
[0021]
After selecting or preparing an RNase P RNA target, the nucleotide sequence of the RNase P RNA target is determined and then compared to the nucleotide sequences of multiple RNase P RNAs from different taxonomic species . In one embodiment of the invention, the nucleotide sequence of the RNase P RNA target is determined by scanning at least one gene database or identified in available publications. Databases known and available to those skilled in the art include, for example, GenBank and others. These databases can be used with a searching program such as, for example, Entrez, which is known and available to those skilled in the art. Entrez is, for example, ncbi. nlm. nih. Gov / Entrez / can be accessed via the global web of the Internet. Preferably, the most complete nucleic acid sequence representation available from various databases is used. The GenBank database known and available to those skilled in the art can also be used to obtain the most complete nucleotide sequence. GenBank is the NIH gene sequence database, an annotated collection of all publicly available DNA sequences. GenBank is described, for example, in Nuc. Acids Res., 1998, 26, 1-7, which is hereby incorporated by reference in its entirety, and is known to those skilled in the art, for example, ncbi. nlm. nih. gov / Web / Genbank / index. It can be accessed via the worldwide web of the Internet at html. Alternatively, the partial nucleotide sequence of the RNase P RNA target can be used when the complete nucleotide sequence is not available.
[0022]
The nucleotide sequence of the RNase P RNA target is compared to the nucleotide sequence of multiple RNase P RNAs from different taxonomic species. Multiple RNase P RNAs from different taxonomic species and their nucleotide sequences can be found in genetic databases from available publications or specifically determined for use in connection with the present invention be able to. In one embodiment of the invention, the RNase P RNA target is compared with nucleotide sequences of multiple RNase P RNAs from different taxonomic species by performing a sequence similarity search, an ortholog search, or both. Such searches are known to those skilled in the art.
[0023]
The result of the sequence similarity search is a plurality of RNase P RNAs having at least a portion of their nucleotide sequence that is homologous to a region of at least 8 to 20 nucleotides of the target RNase P RNA, referred to as the window region. is there. Preferably, the plurality of RNase P RNAs comprise at least one portion that is at least 60% homologous to any window region of the target RNase P RNA. More preferably, this homology is at least 70%. More preferably, this homology is at least 80%. Most preferably, this homology is at least 90% or 95%. For example, the window size, ie the portion of the target RNase P RNA to which the plurality of sequences are compared, is about 8 to about 20 contiguous nucleotides, preferably about 10 to about 15 contiguous nucleotides, most preferably about 11 to 11 There can be about 12 contiguous nucleotides. Accordingly, the window size can be adjusted. Next, multiple RNase P RNAs from different taxonomic species are placed in each possible window of the target RNase P RNA, preferably all portions of the plurality of sequences are of the target RNase P RNA. Compare until compared to the window. From different taxonomic species having portions that are at least 60%, preferably at least 70%, more preferably at least 80%, or most preferably at least 90% homologous to any window sequence of the target RNase P RNA Multiple RNase P RNA sequences are considered possible homologous sequences.
[0024]
The sequence similarity search can be performed manually or using several available computer programs known to those skilled in the art. Preferably, the Blast and Smith-Waterman algorithms that are available and known to those skilled in the art can be used. Blast is NCBI's sequence similarity search tool designed to support analysis of nucleotide and protein sequence databases. Blast is, for example, ncbi. nlm. nih. Gov / BLAST / can be accessed via the global web of the Internet. GCG Package provides a local version of Blast that can be used by either a public domain database or any locally available and searchable database. GCG Package v. 9.0 is a commercially available software package that contains over 100 interrelated software programs and allows analysis of sequences by editing, mapping, comparing and aligning them. Other programs encompassed by the GCG Package include, for example, programs that facilitate RNA secondary structure prediction, nucleic acid fragment assembly, and evolutionary analysis. In addition, very good gene databases (GenBank, EMBL, PIR and SWISS-PROT) are distributed with the GCG Package, which are fully accessible by database searching and manipulation programs. GCG is, for example, gcg. com. Is accessible via the global web of the Internet. Fetch is a tool available for GCG, which can get an annotated GenBank record based on the accession number, similar to Entrez. Other sequence similarity searches can be performed by GeneWorld and GeneThesaurus from Pangea. GeneWorld 2.5 is an automated, flexible, high-throughput application for the analysis of polynucleotide and protein sequences. GeneWorld allows for automatic analysis and annotation of sequences. Similar to GCG, GeneWorld incorporates several tools for homology searching, gene detection, multiple sequence alignment, secondary structure prediction, and motif identification. GeneThesaurus1.0 ^TM Is an array and annotation data subscription service that provides information from multiple sources and provides a relational data model for public and local data.
[0025]
Other alternative sequence similarity searches can be performed, for example, by BlastParse. BlastParse is a PERL script that runs on the UNIX® platform that automates the above strategy. BlastParase takes a list of target acceptance numbers in question and parses all GenBank fields to form “tab-delimited” text, which in turn gives flexibility, It can be registered in a “relational database” format for easier searching and analysis. The end result is a series of fully parsed GenBank records as well as an annotation-relational database that can be easily filtered, filtered and queried.
[0026]
Another toolkit that can perform sequence similarity searching and data manipulation is SEALS from NCBI as well. This toolset is written in Perl and C and can run on any computer platform that supports these languages. This is for example ncbi. nlm. nih. It is available for download on the global web of the Internet at gov / Walker / SEALS /. This toolkit allows access to Blast2 or gapped blast. This also includes a tool called tax-collector, which, together with a tool called tax-break, parses the output of Blast2 and presents various query sequences that exist. Returns the identifier of the sequence that is most homologous to (query sequence). Another useful tool is feature2fasta, which extracts sequence fragments based on annotations from the input sequence.
[0027]
Preferably, as described above in the sequence similarity search, to find multiple RNase P RNAs from different taxonomic species that have homology to the target nucleic acid, within which to find orthologs of the target RNase P RNA Delineated further. An ortholog is a term defined in the genetic classification to mean two genes in widely divergent organisms that have sequence similarity and perform similar functions in relation to the organism. In contrast, paralogs are genes within a species that are caused by gene duplication but develop new functions and are also called isotypes. Optionally, a paralog search can be performed. By performing an ortholog search, an exhaustive list of homologous sequences from various organisms can be obtained. These sequences are then analyzed to select the best representative sequence that fits the criteria for being an ortholog. The ortholog search can be performed by programs available to those skilled in the art including, for example, Compare. Preferably, an ortholog search is performed with access to the complete, analyzed GenBank annotation for each of the sequences. Currently, the records obtained from GenBank are “flat-files” and are not ideally suited for automated analysis. Preferably, an ortholog search is performed using the Q-Compare program. The Blast Results-Relation and Annotations-Relational databases are used in the Q-Compare protocol, whereby a list of ortholog sequences is obtained and compared with the interspecies sequence comparison program described below.
[0028]
The similarity search gives results based on a cut-off value called e-score. The e-score represents the probability of a random sequence match within a fixed window of nucleotides. The lower the e-score, the better the match.
Those skilled in the art are familiar with e-scores. The user defines an e-value cutoff depending on stringency or the desired degree of homology, as described above. In some embodiments of the invention, it is preferred that none of the identified RNase P RNA homologous nucleotide sequences are present in the human genome.
[0029]
In another embodiment of the invention, the required sequence is obtained by searching an ortholog database. One such database is Hovergen, which is a curated database of vertebrate orthologs. The ortholog set can be exported from this database and used as is, or as a seed for other sequence similarity searches, as described above. For example, further searches may be desirable to find invertebrate orthologs. Hovergen is, for example, pbil. univ-lyon1. It can be downloaded as a file transfer program at fr / pub / hovergen /. A database of prokaryotic orthologs, COGS, is available, eg, ncbi. nlm. nih. Gov / COG / can be used interactively via the global web of the Internet.
[0030]
After obtaining the orthologs or virtual transcripts by either a sequence similarity search or an ortholog search, among multiple RNase P RNAs and target RNase P RNAs from different taxonomic species Identifying at least one sequence region conserved in Interspecies sequence comparisons can be performed using a number of computer programs available and known to those skilled in the art. It is preferred to perform interspecies sequence comparisons using known compare available to those skilled in the art. Compare is a GCG tool that allows pair-wise comparison of sequences using window / stringency criteria. Compare produces an output file containing the points where a match of the specified property is found. These can be plotted with another GCG tool, DotPlot.
[0031]
Alternatively, a conserved sequence region is identified by interspecies sequence comparison using an ortholog sequence obtained from Q-Compare in combination with CompareOverWins. Preferably, a list of sequences for comparison, ie, an ortholog sequence obtained from Q-Compare, is entered into the CompareOverWins algorithm. Preferably, interspecies sequence comparison is performed by pair-wise sequence comparison by sliding the query sequence over the master target sequence window. Preferably, the window is from about 9 to about 99 contiguous nucleotides.
[0032]
The sequence homology between the target RNase P RNA and the query sequence of any of the plurality of RNase P RNAs obtained as described above is preferably at least 60%, more preferably at least 70%, even more preferably At least 80%, most preferably at least 90% or 95%. The most preferred method of selecting the threshold is to have the computer automatically try all thresholds between 50% and 100% and select the threshold based on user provided metrics. One such metric is to select a threshold so that when n is usually set to 3, exactly n hits are returned. This process is repeated until all bases on the query nucleic acid that are members of the plurality of RNase P RNAs are compared to all bases on the master target sequence. The resulting scoring matrix can be plotted as a scatter plot. Based on the match density at a fixed position, either there are no dots, there are isolated dots, or there is a set of dots that are so close together that they look like lines Can happen. Although small, the presence of the line suggests primary sequence homology. Sequence conservation within RNase P RNA in branched species appears to be an indicator of conserved regulatory elements that may have secondary structure. The results of interspecies sequence comparison can be analyzed using MS Excel and visual basic tools in a fully automated manner known to those skilled in the art.
[0033]
After identifying at least one region conserved between the nucleotide sequence of the RNase P RNA target and the nucleotide sequence of multiple RNase P RNAs from different taxonomic species, preferably by orthologue, the conserved region is Analyze to determine if it contains secondary structure. The determination of whether an identified conserved region contains secondary structure can be made by a number of means known to those skilled in the art. Secondary structure determination is preferably done by self complementarity comparison, alignment and covariance analysis, secondary structure prediction or a combination thereof.
[0034]
In one embodiment of the invention, secondary structure analysis is performed by alignment and covariance analysis. Many protocols for alignment and covariance analysis are known to those skilled in the art. Preferably, the alignment is performed by a known ClustalW, available to those skilled in the art. ClustalW is a tool for multiple sequence alignment that is not part of GCG but can be used with local sequences in addition to an extension of the existing GCG toolset. ClustalW is, for example, dot. imgen. bcm. tmc. edu: 9331 / multi-align / Options / clustalw. It can be accessed via the worldwide web of the Internet at html. ClustalW is further described in Thompson, et al., Nuc. Acids Res., 1994, 22, 4673-4680, which is incorporated herein in its entirety. These processes can be scripted to automatically use the conserved UTR regions identified in the early stages. Sequed, a known UNIX command line interface, available to those skilled in the art, allows the extraction of selected local regions from a large array. Multiple sequences from many different species can be clustered and aligned for further analysis.
[0035]
In another embodiment of the invention, the output of all possible pair-wise CompareOverWindows® comparisons are compiled and matched to the reference sequence using a program called AlignHits, ie a program that can be reproduced by those skilled in the art. Align. One purpose of this program is to map all hits from pairwise comparisons to positions on the reference sequence. This method, combining CompareOverWindow and AlignHits, produces a larger local alignment (over 20-100 bases) than any other algorithm. This local alignment is necessary for the structure finding routine described below, such as covariation or RevComp. This algorithm writes a fasta file of aligned sequences. It is important to distinguish this from using only ClustalW, without CompareOverWindows® and AlignHits.
[0036]
Covariation is a process that uses phylogenetic analysis of primary structure information for consensus secondary structure prediction. Covariation is described in the following references, each of which is incorporated herein in their entirety: Gutell et al., “Comparative Sequence Analysis Of Experiments Performed During Evolution” In Ribosomal RNA Group. I Introns, Green, Ed., Austin: Landes, 1996; Gautheret et al., Nuc. Acids Res., 1997, 25, 1559-1564; Gautheret et al., RNA, 1995, I, 807-814; Lodmell et al., Proc. Natl. Sci. USA, 1995, 92, 10555-10559; Gautheret et al., J. Mol. Biol., 1995, 248, 27-43; Gutell, Nuc. Acids Res., 1994, 22 , 3502-3517; Gutell, Nuc. Acids Res., 1993, 21, 3055-3074; Gutell, Nuc. Acids Res., 1993, 21, 3051-3054; Woese, Proc. Natl. Sci. USA, 1989, 86 , 3119-3122; and Woese et al., Nuc. Acids Res., 1980, 8, 2275-2293, each of which is incorporated herein in its entirety. Preferably, covariance software is used for covariance analysis. Preferably, a program set for covariation, ie, comparative analysis of RNA structure from sequence alignments, is used. Covariation uses phylogenetic analysis of primary sequence information for consensus secondary structure prediction. Covariation is described in, for example, ncsu. edu / RNaseP / info / programs / programs. It can be obtained via the worldwide web of the Internet at html. A complete description of the version of the program has been published (Brown, JW1991, Phylogenetic analysis of RNA structure on the Macintosh computer. CABIOS 7: 391-393). The current version is v4.1, which includes various types of RNA sequence alignments, including standard covariation analysis, compensatory base-changes identification, and mutual information analysis. A covariation analysis can be performed. The program is well documented and has a wide range of example files. It has been edited as a stand-alone program; it does not require Hypercard (but includes a very small “stack” version). This program runs on any Macintosh environment running MacOS v7.1 or higher. Faster processor machines (68040 or PowerPC) are proposed for mutual information analysis or analysis of large sequence alignments.
[0037]
In another embodiment of the present invention, secondary structure analysis is performed by secondary structure prediction. There are many algorithms for predicting RNA secondary structure based on thermodynamic parameters and energy calculations. It is preferred to perform secondary structure prediction using either M-fold or RNA structure 2.52. M-fold is, for example, ibc. Wustl. edu / -zuker / ma / form2. It can be accessed via the global web with cgi or downloaded on the UNIX platform for local use. M-fold is also available as part of the GCG package. RNA Structure 2.52 is a Windows adaptation of the M-fold algorithm, for example, 128.151.176.70/RNAstructure. It can be accessed via the worldwide web of the Internet at html.
[0038]
In another embodiment of the present invention, secondary structure analysis is performed by self complementarity comparison. Preferably, the self-complementary comparison is performed using the above-described Compare. More preferably, the Compare is modified to expand the pairing matrix so that in addition to the conventional Watson-Crick GC / CG or AU / UA pair, GU or UG It can occupy base pairs. Such a modified Compare program (modified Compare) starts by predicting all possible base pairs within a given sequence. As described above, small but conserved regions are identified based on a primary sequence comparison of a series of orthologs. In the modified Compare, each of these sequences is compared to its own reverse complement. Acceptable base pairings include Watson-Crick AU, GC pairings and non-canonical GU pairings. The overlay of such self-complementary plots of all available orthologs and the selection of the largest repeating pattern in each yields the fewest possible folding configurations. These overlays can then be used with additional constraints, including those limited by the above energy considerations, to deduce the most possible secondary structure.
[0039]
In another embodiment of the invention, the output of AlignHits is read by a program called RevComp. This program can be reproduced by those skilled in the art. One of the goals of this program is to predict RNA secondary structure using base pairing rules and ortholog evolution. The RNA secondary structure is composed of a single-stranded region and a base pairing region called a stem. Since we search for structures conserved by evolution, the most promising stem for a certain alignment of ortholog sequences is the stem that can be formed by the most sequences. Possible stem formation or base pairing rules are determined by analyzing base pairing statistics of stems determined by other techniques, such as, for example, NMR. The output of RevComp is a classification list of possible structures, ranked by the percentage of ortholog set member sequences that could form this structure. Since this approach uses a percentage threshold approach, it is insensitive to noise sequences. A noise sequence is a sequence that is either not an actual ortholog, or one that spans the output of AlignHits because of the high degree of sequence homology, even though it does not represent an example of the structure being searched. A very similar algorithm was implemented using Visual basic for Applications (VBA) and Microsoft Excel to run on PCs to generate a reverse complement matrix view for a given set of sequences. Form.
[0040]
The results of the secondary structure analysis, whether performed by alignment and covariation, self-complementary analysis, eg secondary structure prediction using M-fold or other formats, Identification of secondary structures in conserved regions among multiple RNase P RNAs from different taxonomic species. Specific secondary structures that can be identified include, but are not limited to, bulges, loops, stems, hairpins, knots, triple interacts, cloverleafs, or helices, or these Includes combinations. Alternatively, new secondary structures may be identified.
[0041]
The invention also relates to nucleic acid molecules, such as polynucleotides and oligonucleotides, that contain molecular interaction sites present in 16S rRNA. A nucleic acid molecule encompasses the physical compound itself as well as an in silico representation of the compound. Thus, the nucleic acid molecule is derived from RNase P RNA. The molecular interaction site serves as a binding site for at least one molecule that modulates the expression of RNase P RNA in the cell when binding to the molecular interaction site. The nucleotide sequence of the polynucleotide is selected to provide the secondary structure of the molecular interaction site as further detailed in the examples. The nucleotide sequence of the polynucleotide is preferably the nucleotide sequence of the target RNase P RNA described above. Alternatively, the nucleotide sequence is preferably the nucleotide sequence of RNase P RNA from multiple different taxonomic species that also contains molecular interaction sites.
[0042]
The polynucleotide of the present invention comprises a molecular interaction site of RNase P RNA. Thus, the polynucleotide of the present invention comprises the nucleotide sequence of the molecular interaction site. Further, the polynucleotide may be at the 5 ′ or 3 ′ end of each polynucleotide or combinations thereof, up to 50, more preferably up to 40, more preferably up to 30, even more preferably up to 20, most preferably up to 10. Additional nucleotides can be included. Thus, for example, a polynucleotide can contain up to 75 nucleotides when the molecular interaction site contains 25 nucleotides. Nucleotides other than those present at the molecular interaction site are selected to maintain the secondary structure of the molecular interaction site. One skilled in the art can select such additional nucleotides to preserve secondary structure. The polynucleotide can comprise either RNA or DNA, or can be chimeric RNA / DNA. The polynucleotide can include modified bases, sugars and backbones well known to those skilled in the art. In addition, a single polynucleotide can include multiple molecular interaction sites. In addition, multiple polynucleotides can include a single molecule interaction site together. Alternatively, if a plurality of polynucleotides together contain a molecular interaction site, those skilled in the art can combine these polynucleotides together to form a single polynucleotide.
[0043]
The portion of the polynucleotide, including the molecular interaction site, can include one or more deletions, insertions and substitutions. The stem, terminal loop, bulge, inner loop and dangling region can contain one or more deletions, insertions and substitutions. Thus, for example, the terminal loop of a molecular interaction site consisting of 10 nucleotides can be modified to contain one or more insertions, deletions or substitutions to shorten or extend the stem preceding the terminal loop. . Further, for example, unpaired dangling nucleotides adjacent to the double stranded region can be deleted, or other nucleotides can be added to form base pairs and extend the stem. In addition, nucleotide base pairing within the stem can also be substituted, deleted or inserted. Thus, for example, an AU base pair in the stem portion of the molecular interaction site can be replaced with a GC base pair. In addition, non-standard base pairing (eg, GA, CT, GU, etc.) can also be present in the polynucleotide. Thus, for example, as described in the examples below, at least 70%, more preferably 80%, more preferably 90%, more preferably 95%, most preferably 99% homology with the molecular interaction site. Are encompassed within the scope of the present invention. The percent homology is calculated, for example, by the algorithm of Smith and Waterman (Adv. Appl. Math.) By the Gap program (Wisconsin Sequence Analysis Package, Version 8 for Unix (registered trademark), Genetics Computer Group, University Research Park, Madison WI). 1981, 2, 482-489, which is incorporated herein in its entirety).
[0044]
The invention further relates to the above-described refined and isolated nucleic acids or polynucleotides present in RNase P RNA. A polynucleotide containing a molecular interaction site mimics the portion of RNase P RNA that contains the molecular interaction site.
[0045]
Polynucleotides and their modifications are well known to those skilled in the art. The polynucleotide of the present invention can be used, for example, as a research reagent for detecting a naturally occurring molecule that binds to a molecular interaction site. Alternatively, as detailed below, the polynucleotides of the invention can be used to screen realistically or virtually for small molecules that bind to a molecular interaction site. The virtual formation of compounds for binding to molecular interaction sites and their screening are described, for example, in International Application Publication No. WO 99/58947, which is hereby incorporated by reference in its entirety. The polynucleotides of the invention can also be used as decoys that compete with naturally occurring molecular interaction sites in cells for research, diagnostic and therapeutic applications. In particular, the polynucleotide can be used for therapeutic applications to inhibit bacterial growth. Molecules that bind to molecular interaction sites modulate the function of the RNase P RNA during translation, either by enhancement or reduction. The polynucleotide can also be used for agricultural, industrial and other uses.
[0046]
The present invention also relates to a composition comprising at least one of the above polynucleotides. In some embodiments of the invention, two polynucleotides are included in one composition. The composition of the present invention can optionally include a carrier. A “carrier” is an acceptable solvent, diluent, suspending agent or any other inert vehicle for delivering one or more nucleic acids to an animal and is well known to those skilled in the art. The carrier can be a pharmaceutically acceptable carrier. The carrier can be liquid or solid and is selected with the intended method of administration in mind to give the desired bulk, consistency, etc. when combined with the other components of the composition. The Typical pharmaceutical carriers include, but are not limited to, binders (such as pregelatined corn starch, polyvinyl pyrrolidone or hydroxypropyl methylcellulose); fillers (eg, lactose and other sugars, microcrystalline cellulose, Pectin, gelatin, calcium sulfate, ethyl cellulose, polyacrylate or calcium hydrogen phosphate); lubricants (eg, magnesium stearate, talc, silica, colloidal silicon dioxide, stearic acid, metal stearate, hydrogenated vegetable oil, corn starch Polyethylene glycol, sodium benzoate, sodium acetate, etc.); disintegrating agents (eg, starch, sodium starch glycolate, etc.); or wetting agents (eg, sodium lauryl sulfate, etc.).
[0047]
The present invention is also a method for identifying a compound that binds to a molecular interaction site of RNase P RNA, comprising preparing a numerical representation of the three-dimensional structure of the molecular interaction site, and the three-dimensional structure of a plurality of organic compounds. And providing a compound data set comprising a numerical representation of The numerical representation of the molecular interaction site is then compared with the members of the compound data set, and the organic compound is ranked according to the ability of the organic compound to produce a physical interaction with the molecular interaction site form (hierarchy).
[0048]
The invention also relates to a method of identifying a compound that binds to a molecular interaction site of RNase P RNA or a polynucleotide comprising the same. In some embodiments of the invention, a compound that binds to a molecular interaction site of RNase P RNA or a polynucleotide comprising the same is described in International Application Publication No. WO 99/58947, which is incorporated herein in its entirety. ) Is identified according to the general method described in). Briefly, the method provides a numerical representation of the three-dimensional structure of a molecular interaction site or polynucleotide comprising it, and a compound data set comprising a numerical representation of the three-dimensional structure of a plurality of organic compounds. Comparing the numerical representation of a molecular interaction site with a member of the compound data set and ranking the organic compounds ranked according to the ability of the organic compound to produce a physical interaction with the molecular interaction site Forming.
[0049]
There are many ways to characterize the binding of a molecular interaction site to a ligand, such as an organic compound, for example, International Application Publications WO99 / 58819, WO99 / 59061, WO99 / 58722, WO99 / 45150, WO99 / 58474. And WO 99/58947 describe methodologies, each of which is assigned to the assignee of the present invention, each of which is incorporated herein in its entirety.
[0050]
Furthermore, the present invention also relates to a three-dimensional representation of the nucleic acid molecule and the composition comprising it as described above. The three-dimensional structure of the molecular interaction site of RNase P RNA can be manipulated as a numerical expression. Three-dimensional representations, ie in silico (eg in computer readable form) representations, are generated, for example, in the manner disclosed in International Application Publication No. WO 99/58947, which is hereby incorporated by reference in its entirety. be able to. Briefly, preferably the three-dimensional structure of the molecular interaction site of RNA can be manipulated as a numerical expression. Computer software is commercially available that gives those skilled in the art the ability to design molecules based on the chemistry performed and available reaction building blocks. For example, software packages such as Sybyl / Base (Tripos, St. Louis, MO), Insight II (Molecular Simulations, San Diego, Calif.), And Sculpt (MDL Information Systems, San Leandro, Calif.) Provides computer generation means. These software products also provide methods for evaluating and comparing computer generated molecules and their structures. In silico collections of molecular interaction sites can be generated using software from any of the above suppliers and other software that may or may be available. The three-dimensional representation can be used, for example, to dock the molecule (s) to a possible therapeutic compound. Thus, the three-dimensional representation can be used for drug searching means. Accordingly, the nucleic acid molecules and compositions comprising the same of the present invention include three-dimensional representations of the nucleic acid molecules.
[0051]
A series of structural constraints on the molecular interaction sites of RNase P RNA can arise from, for example, enzymatic mapping and biochemical analysis such as chemical probes, and genomic information such as covariation and sequence conservation. There is. For example, information such as this can be used to form base pairings in specific secondary structure stems and other regions. Additional structural hypotheses may arise for non-standard base pairing schemes in the loop and bulge regions. The Monte Carlo search method can sample the possible conformation of RNase P RNA that matches the program constraints to create a three-dimensional structure.
[0052]
Reports on the generation of three-dimensional in silico representations are available from the perspective of library design, development, and screening for protein targets. Similarly, several attempts in the field of RNA modeling have been reported in the literature. However, a report on the use of a structure-based design approach to query in silico representations of organic molecules, “small” molecules, polynucleotides, or other nucleic acids with a three-dimensional, in silico representation of RNase P RNA structure Does not exist. The present invention preferably comprises the construction of a three-dimensional model of RNase P RNA structure, the construction of three-dimensional in silico representations of multiple organic compounds, “small” molecules, polymer compounds, polynucleotides and other nucleic acids, in silico Screening of such in silico representations for RNase P RNA molecule interaction sites, scoring and identification of the best possible binders from multiple compounds, and finally such in combinatorial format Computer software is used that allows the synthesis of such compounds and the experimental testing of such compounds to identify new ligands for such RNase P RNA targets.
[0053]
Molecules that can be screened using the methods of the present invention include, but are not limited to, organic or inorganic, small to large molecular weight individual compounds, ligands, inhibitors, agonists, antagonists, substrates and, for example, peptides or Includes combinatorial mixtures or libraries of biopolymers such as polynucleotides. Combinatorial mixtures include, but are not limited to, a collection of compounds and a library of compounds. These mixtures can be produced by combinatorial synthesis of the mixtures or by mixing individual compounds. A collection of compounds includes, but is not limited to, individual compound sets or mixture sets or compound pools. These combinatorial libraries can be obtained from synthesis or from natural sources, such as natural sources of microbial, plant, marine, viral and animal substances. Combinatorial libraries include at least about 20 compounds, thousands of individual compounds, and possibly even more. When the combinatorial library is a mixture of compounds, these mixtures typically contain 20-5000 compounds, preferably 50-1000, more preferably 50-100 compounds. Combinations of 100-500 compounds are useful as well as mixtures having 500-1000 individual species. Typically, members of a combinatorial library have a molecular weight of less than about 10,000 Da, more preferably less than 7,500 Da, and most preferably less than 5000 Da.
[0054]
An important advance in the field of virtual screening, called DOCK, allows structure-based database searches to find and identify known molecular interactions for a receptor of interest It was the development of a software program (Kuntz et al., ACC. Chem. Res., 1994, 27, 117; Geschwend and Kuntz, J. Compt.-Aided Mol. Des., 1996, 10, 123). DOCK allows the screening of molecules whose 3D structures are formed in silico but for which no prior knowledge about the interaction with the receptor is available. Therefore, DOCK provides a tool to assist in the discovery of new ligands for the receptor in question. Thus, DOCK can be used to dock a compound prepared by the method of the invention to a desired target. The implementation of DOCK is described, for example, in International Application Publication No. WO 99/58947, which is hereby incorporated by reference in its entirety.
[0055]
In some embodiments of the invention, from RNase P RNA that meets biochemical and genomic constraints specified by the user, eg, using an automated computer-based search algorithm, as described above. Predict all acceptable 3D molecular interaction site structures. These structures are clustered into different families based on, for example, their root mean square deviation values. Further structural refinement can be performed on the representative member (s) of each family by molecular dynamics with explicit solvents and cations.
[0056]
Structural enumeration and representation by these software programs is typically done by drawing molecular skeletons and substituents in two dimensions. Once drawn and stored in a computer, these molecules can be made into a three-dimensional structure using algorithms present in commercially available software. Preferably, MC-SYM is used to create a three-dimensional representation of the molecular interaction site. Making the two-dimensional structure of the molecular interaction site into a three-dimensional model typically results in a low energy conformation or collection of low energy conformers for each molecule. The end result of these commercially available programs is the conversion of the RNase P RNA sequence containing the molecular interaction site into a family of similar numerical representations of the three-dimensional structure of the molecular interaction site. . These numerical representations form an ensemble data set.
[0057]
The three-dimensional structure of a plurality of compounds, preferably “small” organic compounds, can be displayed as a compound data set containing a numerical representation of the three-dimensional structure of these compounds. In this context, “small” molecules refer to non-oligomeric organic compounds. The two-dimensional structure of a compound can be converted to a three-dimensional structure and used for querying the three-dimensional structure of the molecular interaction site, as described above with respect to the molecular interaction site. By using commercially available structure rendering algorithms, two-dimensional structures of compounds can be rapidly generated. Three-dimensional representations of compounds that are polymeric in nature, such as polynucleotides or other nucleic acid structures, can be generated using the literature methods described above. Three-dimensional structures of “small” molecules or other compounds can be generated and low energy conformations can be obtained from short molecular dynamics minimization. These three-dimensional structures can be stored in a relational database. The compound in which the three-dimensional structure is constructed can be proprietary, commercially available, or virtual.
[0058]
In some embodiments of the invention, a compound data set comprising a numerical representation of the three-dimensional structure of a plurality of organic compounds is generated, for example, by a two-dimensional compound library generated by a computer program modified from a commercial program. From, for example, Converter (MSI, San Diego). By converting the two-dimensional structure of the chemical compound into a three-dimensional structure as described above, another appropriate database can be constructed. The final result is a transformation from the two-dimensional structure of an organic compound to a numerical representation of the three-dimensional structure of a plurality of organic compounds. These numerical representations are presented as compound data sets.
[0059]
After both a numerical representation of the three-dimensional structure of the polynucleotide containing the molecular interaction site and a compound data set containing a numerical representation of the three-dimensional structure of multiple organic compounds, a numerical representation of the molecular interaction site is obtained. Expressions are compared with members of the compound data set to form an order of organic compounds. This order is ranked according to the ability of the organic compound to form a physical interaction with the molecular interaction site. Preferably, this comparison is performed sequentially on members of the compound data set. According to some embodiments, this comparison can be performed simultaneously by a plurality of polynucleotides comprising molecular interaction sites.
[0060]
A variety of theoretical and combinatorial methods for studying and optimizing the interaction of “small” molecules or organic compounds with biological targets such as nucleic acids are known to those skilled in the art. These structure-based drug design tools have been very useful in modeling the interactions between proteins and small molecule ligands and optimizing these interactions. Typically, this type of study is performed when the structure of a protein receptor is known by querying individual small molecules, one at a time for this receptor. ing. Usually, these small molecules are either co-crystallized with the receptor, or are related to other molecules that are co-crystallized, or some series with respect to their interaction with the receptor. The knowledge of either was a molecule that existed. Using DOCK as described above, one can find and identify a molecule that is expected to bind to a polynucleotide containing a molecular interaction site, and thus to the RNase P RNA in question. DOCK 4.0 is commercially available from the Regents of the University of California. Equivalent programs are also encompassed by the present invention.
[0061]
The DOCK program has been widely applied to the identification of protein targets and ligands that bind to them. Typically, a new class of molecules that bind to known targets have been identified and later demonstrated in in vitro experiments. The DOCK software programs are SPHGEN (Kuntz et al., J. Mol. Biol., 1982, 161, 269) and CHEMGRID (Meng et al., J. Comput. Chem., 1992, 13, 505, each of which is in its entirety. Which is incorporated herein by reference). SPHGEN forms a cluster of overlapping spheres that represent the solvent accessible surface of the binding pocket within the target receptor. Each cluster represents a possible binding site for a small molecule. CHEMGRID pre-calculates information required for force field scoring of the interaction between the binding molecule and the target RNase P RNA and stores it in a grid file. . The scoring function approximates the molecular mechanics interaction energy and consists of a van der Waals component and an electrostatic component. DOCK orients the ligand molecule to the target site on the RNase P RNA using selected cluster of spheres. Each molecule in the pre-formed three-dimensional database is tested in numerous thousands of orientations within the site, and each orientation is evaluated by a scoring function. Only the orientation with the best score for each compound screened in this way is stored in the output file. Finally, all compounds in the database can be ranked in order of score, and then the best candidate collection can be screened experimentally.
[0062]
A large number of ligands for a variety of protein targets have been identified using DOCK. Recent efforts in this field have generated reports on the use of DOCK to identify and design small molecule ligands that exhibit binding specificity for nucleic acids such as RNA duplexes. RNA plays an important role in many diseases such as AIDS, viral infections and bacterial infections, but little research has been done on small molecules capable of specific RNA binding. For RNA duplexes, compounds with specificity were identified using the DOCK methodology, based on the unique geometry of its deep major groove. Chen et al., Biochemistry, 1997, 36, 11402; and Kuntz et al., ACC. Chem. Res., 1994, 27, 117. Recently reported application of DOCK to the problem of ligand recognition in DNA quadruplexes. Has been. Chen et al., Proc. Natl. Acad. Sci., 1996, 93, 2635.
Individual compounds are preferably represented, for example, as a mol file and combined into a collection of in silico representations using an appropriate chemical structure program or equivalent software. These 2D molar files are exported and converted to 3D structures using commercial software such as Converter (Molecular Simulations Inc., San Diego) or equivalent software, as described above. . For example, atom types suitable for use by docking programs such as DOCK or QXP can be assigned to all atoms in a three-dimensional molar file using, for example, software such as Babel or equivalent software. ).
[0063]
The low energy conformation of each molecule is generated by software such as Discover (MSI, San Diego). An orientation search is performed by bringing each of a plurality of compounds close to the molecular interaction site in many orientations using DOCK or QXP. A contact score for each orientation is determined and then the optimal orientation of the compound is used. Alternatively, the conformation of the compound can be determined from a pre-determined scaffold template conformation.
[0064]
The interaction between a plurality of compounds and a molecular interaction site is examined by comparing a numerical representation of the molecular interaction site with a member of a compound data set. Preferably, multiple compounds are compared to molecular interaction sites, eg, created by a computer program or otherwise, to experience random “movement” between the dihedral bonds of the compounds . Preferably, about 20,000-100,000 compounds are compared to at least one molecular interaction site. Typically, 20,000 compounds are scored compared to about 5 molecule interaction sites. Individual conformations of the three-dimensional structure are placed in many orientations at the target site. Furthermore, during the execution of the DOCK program, the compound and the molecular interaction site are allowed to be “flexible” so that optimal hydrogen bonding, static electricity and van der Waals contacts can be achieved. The energy of interaction is calculated and stored for 10-15 possible orientations of the compound and molecular interaction site. The QXP methodology is currently preferred because it allows for true flexibility in both the ligand and the target.
[0065]
The relative weights of each energy contribution are constantly updated to ensure that the binding scores calculated for all compounds represent experimental binding data. The binding energy for each orientation is scored based on hydrogen bonding, van der Waals contact, static electricity, solvation / desolvation, and quality of the fit. Low energy van der Waals, bipolar and hydrogen bonding interactions between the compound and the molecular interaction site are measured and summed. In some implementations, these parameters can be adjusted according to empirically obtained results. The binding energy of each molecule to the target is output to a relational database. The relational database contains a sequence of compounds that are ranked according to their ability to form physical interactions with molecular interaction sites. Highly ranked compounds can better form physical interactions with molecular interaction sites.
[0066]
In other embodiments, the compound with the highest rank, ie, the best fit, is selected for synthesis. In some embodiments of the invention, compounds are selected for synthesis that are believed to have the desired binding characteristics based on the binding data. Preferably, a maximum ranking of 5% is selected for synthesis. More preferably, a maximum ranking of 10% is selected for synthesis. Even more preferably, the highest ranking of 20% is selected for synthesis. The synthesis of selected compounds can be automated using a parallel array synthesizer or can be prepared using liquid or solid phase methods and equipment. Furthermore, the interaction between the highly ranked compound and the nucleic acid containing the molecular interaction site is evaluated as described below.
[0067]
The interaction of highly ranked organic compounds with polynucleotides containing RNase P RNA molecule interaction sites can be assessed by numerous methods known to those skilled in the art. For example, the highest ranking compounds can be tested for high throughput (HTS) function and activity in cell screens. HTS assays can be measured by scintillation proximity, sedimentation, fluorescence-based formats, filtration-based assays, colorometry assays, and the like. The lead compound can then be scaled up and tested for activity and toxicity in animal models. This assessment preferably includes mass spectrometry or functional bioassay of a mixture of RNase P RNA polynucleotide and at least one compound.
[0068]
Certain evaluation methods using mass spectroscopy are described in International Application Publication No. WO 99/45150, which is hereby incorporated by reference in its entirety, as an illustration of certain useful mass spectrometry methods for use in accordance with the present invention. Incorporated). However, it should be clearly understood that it is not essential to use these specific mass spectrometry methods to practice the present invention. Rather, any evaluation method can be undertaken as long as the purpose of the present invention is maintained.
[0069]
In some embodiments of the invention, an organic compound comprising a compound that is chemically related to the highest ranking compound in the order, using the highest ranking compound of 20% from the order formed using the DOCK program or QXP Form a further data set of a three-dimensional representation of The best fitting compounds are likely to be included in the highest ranking 1%, but up to about 20% addition for the second comparison to give diversity (ring size, chain length, functional group) The selected compound is selected. This process ensures that small errors in the molecular interaction site do not extend to the compound identification process. For example, the structure / score data obtained from the highest ranking of 20% is mathematically studied (clustered) to find trends or features within the compound that enhance binding. The compounds are clustered into different groups. The chemical synthesis and screening of compounds described above makes it possible to correlate the calculated DOCK or QXP score with the actual binding data. After the compounds are prepared and screened, the predicted binding energy and the observed Kd value are correlated for each compound.
[0070]
The results are used to develop a predictive scoring scheme that appropriately weighs various elements (stereoscopic, electrostatic). The above strategy allows for the rapid evaluation of many scaffolds with different sizes and shapes of different functional groups for highly ranked compounds. In this way, comparing other data sets of representations of organic compounds, including compounds that are chemically related to organic compounds that are ranked higher in the rank, to numerical representations of molecular interaction sites, Further ranks ranked according to their ability to form physical interactions with the interaction site can be determined. In this way, we obtain an additional data set of 3D structural representations of the compounds related to the compounds ranked higher in the order, and actually optimize this by correlating the real bonds with the virtual bonds. Yes. The entire cycle can be repeated as necessary until the desired number of compounds with the highest order is obtained.
[0071]
Compounds that are known to have affinity and specificity for a target biomolecule, particularly a target RNase P RNA, or that are known to be able to bind to and modulate a target RNase P RNA Can be tagged or labeled in a detectable manner according to some embodiments of the invention. Such labeling can include all of the labeling formats known to those skilled in the art, such as, for example, fluorophores, radioactive labels, enzyme labels and many other formats. Such labeling or tagging facilitates the detection of molecular interaction sites and allows for easy chromosome mapping and other useful processes.
[0072]
In order that the invention disclosed herein may be more fully understood, the following examples are provided. It should be understood that these examples are for illustrative purposes only and should not be construed as limiting the invention in any way. In addition to those described herein, various modifications of the present invention will be apparent to those skilled in the art from the foregoing description. Such modifications are also intended to fall within the scope of the claims. Furthermore, the disclosures of each patent, patent application, and publication cited and described herein are hereby incorporated by reference in their entirety.
[0073]
Example
Example 1: Selection of RNase P RNA
To explain the strategy for identifying molecular interaction sites for small molecules, RNase P RNA was used. The structure of the RNase P RNA is disclosed in Massire et al., J. Mol. Biol., 1998, 279, 773-793. The RNase P RNA is an RNA of about 375 to 400 nucleotides that folds into several domains.
[0074]
Example 2: Molecular interaction sites in RNase P RNA
Numerous molecular interaction sites have been discovered within RNase P RNA. Site 1 includes a region of RNA that includes first and second polynucleotides. The first polynucleotide comprises from about 24 nucleotides to about 69 nucleotides, the portion of the polynucleotide comprising the following features (5′-3 ′): a dangling region comprising from about 1 nucleotide to about 3 nucleotides, from about 3 nucleotides to about 3 nucleotides The first side of the first stem comprising 8 nucleotides, the first side of the second stem comprising from about 3 nucleotides to about 8 nucleotides, the first terminal loop comprising from about 3 nucleotides to about 8 nucleotides, from about 3 nucleotides to about 8 nucleotides A second side of the second stem comprising, a first side of the third stem comprising from about 2 nucleotides to about 6 nucleotides, a second terminal loop comprising from about 2 nucleotides to about 6 nucleotides, comprising from about 2 nucleotides to about 6 nucleotides Optional bulge containing about 1 to about 3 nucleotides on the second side of the third stem, the second side of the third stem Present, the first side of the fourth stem comprising about 2 nucleotides to about 6 nucleotides, optionally having a bulge comprising about 1 nucleotides to about 5 nucleotides on the first side of the fourth stem, and about 1 nucleotides Forms double stranded RNA having a dangling region comprising ˜about 5 nucleotides. The second polynucleotide comprises from about 8 nucleotides to about 22 nucleotides, the portion of the polynucleotide comprising the following features (5′-3 ′): a dangling region comprising from about 3 nucleotides to about 8 nucleotides, from about 2 nucleotides to A double stranded RNA is formed having a second side of the fourth stem comprising about 6 nucleotides and a second side of the first stem comprising about 3 to about 8 nucleotides.
[0075]
With respect to site 1, the first polynucleotide preferably comprises 45 nucleotides, and the portion of the polynucleotide is characterized by the following features (5′-3 ′): dangling region comprising 2 nucleotides, first stem comprising 5 nucleotides The first side of the second stem comprising 5 nucleotides, the first end loop comprising 5 nucleotides, the second side of the second stem comprising 5 nucleotides, the first side of the third stem comprising 4 nucleotides, A second terminal loop containing 4 nucleotides, a second side of the third stem containing 4 nucleotides, and a bulge containing 1 nucleotide between the third and fourth nucleotides on the second side of the third stem. The first side of the fourth stem containing 4 nucleotides, 3 nucleotides between the second and third nucleotides on the first side of the fourth stem. No bulge is present, and to form a double-stranded RNA having a dangling region containing the 3 nucleotides. Preferably, the first polynucleotide has the sequence:
[0076]
[Chemical 1]

[0077]
(SEQ ID NO: 1) (bold nucleotides indicate preferred base pairing). The second polynucleotide preferably comprises 14 nucleotides, the portion of the polynucleotide being characterized as follows (5′-3 ′): dangling region comprising 5 nucleotides, second side of the fourth stem comprising 4 nucleotides , And a double stranded RNA having the second side of the first stem comprising 5 nucleotides. Preferably, the second polynucleotide has the sequence:
[0078]
[Chemical formula 2]

[0079]
(SEQ ID NO: 2) (bold nucleotides indicate preferred base pairing). Site 1 is present in E. coli as shown in FIG.
Site 2 includes a region of RNA that includes first, second and third polynucleotides. The first polynucleotide comprises from about 6 nucleotides to about 16 nucleotides, the portion of the polynucleotide comprising the following features (5′-3 ′): a dangling region comprising from about 1 nucleotide to about 3 nucleotides, and about 4 nucleotides A double-stranded RNA is formed having a first side of a first stem comprising about 10 nucleotides, optionally having a bulge comprising about 1 to about 3 nucleotides on the first side of the first stem. The second polynucleotide comprises from about 13 nucleotides to about 34 nucleotides, a portion of the polynucleotide comprising the following features (5′-3 ′): the second side of the first stem comprising from about 4 nucleotides to about 10 nucleotides, There is optionally a bulge comprising about 1 nucleotide to about 3 nucleotides on the second side of the first stem, a bulge comprising about 4 nucleotides to about 10 nucleotides, a second bulge comprising about 3 nucleotides to about 9 nucleotides. A double stranded RNA is formed having a dangling region comprising one side and from about 1 nucleotide to about 2 nucleotides. The third polynucleotide comprises from about 5 nucleotides to about 13 nucleotides, the portion of the polynucleotide comprising the following features (5′-3 ′): a dangling region comprising from about 1 nucleotide to about 2 nucleotides, from about 3 nucleotides to A double stranded RNA is formed having a second side of a second stem comprising about 9 nucleotides and a dangling region comprising about 1 to about 2 nucleotides.
[0080]
With respect to site 2, the first polynucleotide preferably comprises 11 nucleotides, the portion of the polynucleotide comprising the following features (5′-3 ′): a dangling region comprising 2 nucleotides, and a first comprising 7 nucleotides. A double-stranded RNA is formed having a first side of the stem, a bulge containing 2 nucleotides between the 5th and 6th nucleotides on the first side of the first stem. Preferably, the first polynucleotide has the sequence:
[0081]
[Chemical Formula 3]

[0082]
(SEQ ID NO: 3) (bold nucleotides indicate preferred base pairing). The second polynucleotide preferably comprises 23 nucleotides and the portion of the polynucleotide comprises the following features (5′-3 ′): the second side of the first stem comprising 7 nucleotides, the second of the first stem A bulge containing 2 nucleotides exists between the 5th and 6th nucleotides on the side, a bulge containing 7 nucleotides, a first side of the second stem containing 6 nucleotides, and a dangling region containing 1 nucleotide Having double stranded RNA. Preferably, the second polynucleotide has the sequence:
[0083]
[Formula 4]

[0084]
(SEQ ID NO: 4) (bold nucleotides indicate preferred base pairing). The third polynucleotide preferably comprises 8 nucleotides, the portion of the polynucleotide being characterized as follows (5′-3 ′): a dangling region comprising 1 nucleotide, the second side of the second stem comprising 6 nucleotides And a double stranded RNA having a dangling region comprising 1 nucleotide. Preferably, the third polynucleotide has the sequence:
[0085]
[Chemical formula 5]

[0086]
(SEQ ID NO: 5) (bold nucleotides indicate preferred base pairing). Site 2 is present in E. coli as shown in FIG.
Site 3 includes an RNA region that includes first and second polynucleotides. The first polynucleotide comprises from about 10 nucleotides to about 26 nucleotides, the portion of the polynucleotide comprising the following features (5 ′ to 3 ′): a dangling region comprising from about 1 nucleotide to about 3 nucleotides, from about 2 nucleotides to A first side of a first stem comprising about 6 nucleotides, a first side of an inner loop comprising from about 3 nucleotides to about 9 nucleotides, a first side of a second stem comprising from about 3 nucleotides to about 6 nucleotides, and about 1 nucleotide Forms double stranded RNA having a dangling region comprising ˜about 2 nucleotides. The second polynucleotide comprises from about 10 nucleotides to about 27 nucleotides, the portion of the polynucleotide comprising the following features (5′-3 ′): the second side of the second stem comprising from about 3 nucleotides to about 9 nucleotides, Two having a second side of an inner loop comprising about 3 nucleotides to about 7 nucleotides, a second side of a first stem comprising about 2 nucleotides to about 6 nucleotides, and a dangling region comprising about 2 nucleotides to about 5 nucleotides Forms strand RNA.
[0087]
With respect to site 3, the first polynucleotide preferably comprises 19 nucleotides, and the portion of the polynucleotide comprises the following features (5′-3 ′): dangling region comprising 2 nucleotides, first stem comprising 4 nucleotides A double-stranded RNA having a first side of the first side of the inner loop comprising 6 nucleotides, a first side of the second stem comprising 6 nucleotides, and a dangling region comprising 1 nucleotide. Preferably, the first polynucleotide has the sequence:
[0088]
[Chemical 6]

[0089]
(SEQ ID NO: 6) (bold nucleotides indicate preferred base pairing). The second polynucleotide preferably comprises 18 nucleotides, the portion of the polynucleotide being characterized by the following features (5′-3 ′): the second side of the second stem comprising 6 nucleotides and the inner loop comprising 5 nucleotides A double-stranded RNA is formed having a second side, a second side of the first stem containing 4 nucleotides, and a dangling region containing 3 nucleotides. Preferably, the second polynucleotide has the sequence:
[0090]
[Chemical 7]

[0091]
(SEQ ID NO: 7) (bold nucleotides indicate preferred base pairing). Site 3 is present in E. coli as shown in FIG.
Site 4 comprises an RNA region comprising a polynucleotide comprising from about 12 nucleotides to about 34 nucleotides, the portion of the polynucleotide comprising the following features (5′-3 ′): of a stem comprising from about 3 nucleotides to about 9 nucleotides On the first side, the first side of the stem has a first side of an internal loop containing about 2 nucleotides to about 5 nucleotides, a terminal loop containing about 2 nucleotides to about 6 nucleotides, about 3 nucleotides to about 9 nucleotides A second side of the stem comprising, a second side of the stem is present on the second side of the inner loop comprising from about 1 nucleotide to about 3 nucleotides, and has a dangling region comprising from about 1 nucleotide to about 2 nucleotides Forms double-stranded RNA.
[0092]
With respect to site 4, the region of RNA preferably comprises a polynucleotide comprising 22 nucleotides, the portion of the polynucleotide comprising the following features (5′-3 ′): the first side of the stem comprising 6 nucleotides, this stem There is a first side of an internal loop containing 3 nucleotides between the 3rd and 4th nucleotides on the 1st side of this, a terminal loop containing 4 nucleotides, the second side of the stem containing 6 nucleotides, this stem The second side of the inner loop containing 2 nucleotides is present between the third and fourth nucleotides on the second side of the double-stranded RNA having a dangling region containing 1 nucleotide and a dangling region containing 1 nucleotide. Preferably, the polynucleotide has the sequence:
[0093]
[Chemical 8]

[0094]
(SEQ ID NO: 8) (bold nucleotides indicate preferred base pairing). Site 4 is present in B subtilis as shown in FIG.
Site 5 includes an RNA region comprising first, second, third, fourth and fifth polynucleotides. The first polynucleotide comprises from about 3 nucleotides to about 9 nucleotides, the portion of the polynucleotide comprising the following features (5′-3 ′): the first side of the first stem comprising from about 2 nucleotides to about 6 nucleotides, and A double stranded RNA is formed having the first side of the second stem comprising from about 1 nucleotide to about 3 nucleotides. The second polynucleotide comprises from about 3 nucleotides to about 8 nucleotides, and the portion of the polynucleotide comprises the following features (5′-3 ′): the second side of the second stem comprising from about 1 nucleotide to about 3 nucleotides; And forming a double-stranded RNA having a first side of a third stem comprising from about 2 nucleotides to about 5 nucleotides. The third polynucleotide comprises from about 7 nucleotides to about 18 nucleotides, the portion of the polynucleotide comprising the following features (5′-3 ′): the second side of the third stem comprising from about 2 nucleotides to about 5 nucleotides, The second side of the third stem optionally has a bulge comprising about 1 nucleotide to about 2 nucleotides, the first side of the fourth stem comprising about 1 nucleotide to about 3 nucleotides, about 1 nucleotide to about 3 nucleotides And a double-stranded RNA having a first side of a fifth stem comprising from about 2 nucleotides to about 5 nucleotides. The fourth polynucleotide comprises from about 8 nucleotides to about 20 nucleotides, the portion of the polynucleotide comprising the following features (5′-3 ′): the second side of the fifth stem comprising from about 2 nucleotides to about 5 nucleotides, about A double stranded RNA is formed having a bulge comprising 3 to about 7 nucleotides, a first side of a sixth stem comprising about 1 to about 3 nucleotides, and a dangling region comprising about 2 to about 5 nucleotides. The fifth polynucleotide comprises from about 5 nucleotides to about 15 nucleotides, the portion of the polynucleotide comprising the following features (5 ′ to 3 ′): a dangling region comprising from about 1 nucleotide to about 3 nucleotides, from about 1 nucleotide to Two having a second side of the sixth stem comprising about 3 nucleotides, a second side of the fourth stem comprising about 1 nucleotide to about 3 nucleotides, and a second side of the first stem comprising about 2 nucleotides to about 6 nucleotides. Forms single-stranded RNA.
[0095]
With respect to site 5, the first polynucleotide preferably comprises 6 nucleotides, the portion of the polynucleotide comprising the following features (5′-3 ′): the first side of the first stem comprising 4 nucleotides, and 2 nucleotides A double-stranded RNA having the first side of the second stem containing Preferably, the first polynucleotide has the sequence:
[0096]
[Chemical 9]

[0097]
(Bold nucleotides indicate preferred base pairing). The second polynucleotide preferably comprises 5 nucleotides, the portion of the polynucleotide being characterized as follows (5′-3 ′): the second side of the second stem comprising 2 nucleotides, and the third comprising 3 nucleotides. A double stranded RNA having the first side of the stem is formed. Preferably, the second polynucleotide has the sequence:
[0098]
[Chemical Formula 10]

[0099]
(Bold nucleotides indicate preferred base pairing). The third polynucleotide preferably comprises 10 nucleotides and the portion of the polynucleotide comprises the following features (5′-3 ′): the second side of the third stem comprising 3 nucleotides, the second of the third stem There is a bulge containing 1 nucleotide between the second and third nucleotides on the side. A double-stranded RNA having a first side is formed. Preferably, the third polynucleotide has the sequence:
[0100]
Embedded image

[0101]
(SEQ ID NO: 9) (bold nucleotides indicate preferred base pairing). The fourth polynucleotide preferably comprises 13 nucleotides, and the portion of the polynucleotide comprises the following characteristics (5′-3 ′): the second side of the fifth stem comprising 3 nucleotides, the bulge comprising 5 nucleotides, 2 A double-stranded RNA is formed having a first side of a sixth stem containing nucleotides and a dangling region containing 3 nucleotides. Preferably, the fourth polynucleotide has the sequence:
[0102]
Embedded image

[0103]
(SEQ ID NO: 10) (bold nucleotides indicate preferred base pairing). The fifth polynucleotide preferably comprises 10 nucleotides, and the portion of the polynucleotide is characterized by the following features (5′-3 ′): dangling region comprising 2 nucleotides, second side of the sixth stem comprising 2 nucleotides A double stranded RNA is formed having a second side of the fourth stem comprising 2 nucleotides and a second side of the first stem comprising 4 nucleotides. Preferably, the fifth polynucleotide has the sequence:
[0104]
Embedded image

[0105]
(SEQ ID NO: 11) (bold nucleotides indicate preferred base pairing). Site 5 is present in B. subtilis as shown in FIG.
Site 6 comprises an RNA region comprising a polynucleotide comprising from about 13 nucleotides to about 34 nucleotides, the portion of the polynucleotide comprising the following features (5′-3 ′): dangling comprising from about 2 nucleotides to about 5 nucleotides A region, a first side of a stem comprising from about 2 nucleotides to about 5 nucleotides, a terminal loop comprising from about 6 nucleotides to about 16 nucleotides, a second side of the stem comprising from about 2 nucleotides to about 5 nucleotides, and from about 1 nucleotide to A double stranded RNA is formed having a dangling region comprising about 3 nucleotides.
[0106]
With respect to site 6, the region of RNA preferably comprises a polynucleotide comprising 22 nucleotides, the portion of the polynucleotide comprising the following features (5′-3 ′): a dangling region comprising 3 nucleotides, 3 nucleotides A double stranded RNA is formed having a first side of the stem, a terminal loop containing 11 nucleotides, a second side of the stem containing 3 nucleotides, and a dangling region containing 2 nucleotides. Preferably, the polynucleotide has the sequence:
[0107]
Embedded image

[0108]
(SEQ ID NO: 12) (bold nucleotides indicate preferred base pairing). Site 6 is present in B. subtilis as shown in FIG.
[Brief description of the drawings]
[0109]
FIG. 1 shows a representative structure of E. coli RNase P RNA showing sites 1, 2 and 3. FIG.
FIG. 1A shows a representative structure of E. coli RNase P RNA showing sites 1, 2 and 3.
FIG. 1B shows a representative structure of E. coli RNase P RNA showing sites 1, 2 and 3.
FIG. 1C shows a representative structure of E. coli RNase P RNA showing sites 1, 2 and 3.
FIG. 2 shows a representative structure of B. subtilis RNase P RNA showing sites 4, 5, and 6.
FIG. 2A shows a representative structure of B. subtilis RNase P RNA showing sites 4, 5, and 6. FIG.
FIG. 2B shows a representative structure of B. subtilis RNase P RNA showing sites 4, 5, and 6.
FIG. 2C shows a representative structure of B. subtilis RNase P RNA showing sites 4, 5, and 6.

Claims (26)

A composition comprising a first polynucleotide and a second polynucleotide comprising:
A first polynucleotide comprising a dangling region comprising at least 26 nucleotides and not more than 117 nucleotides and comprising from about 1 nucleotide to about 3 nucleotides; a first side of the first stem comprising from about 3 nucleotides to about 7 nucleotides; The first side of the second stem comprising nucleotides to about 7 nucleotides, the first terminal loop comprising about 3 nucleotides to about 7 nucleotides, the second side of the second stem comprising about 3 nucleotides to about 7 nucleotides, about 2 nucleotides to A first side of a third stem comprising about 6 nucleotides; a second terminal loop comprising about 2 nucleotides to about 6 nucleotides; a second side of a third stem comprising about 2 nucleotides to about 6 nucleotides; On the two side there is a bulge containing from about 1 nucleotide to about 2 nucleotides, from about 2 nucleotides to A first side of a fourth stem comprising 6 nucleotides, a bulge comprising from about 2 nucleotides to about 5 nucleotides is present on the first side of the fourth stem, and a dangling region comprising from about 2 nucleotides to about 5 nucleotides As well as a dangling region comprising from about 3 nucleotides to about 7 nucleotides, and from about 2 nucleotides to about 6 nucleotides A composition comprising a secondary structure defined by a second side of the fourth stem and a second side of the first stem comprising from about 3 nucleotides to about 7 nucleotides. A first polynucleotide comprising at least 45 to 95 nucleotides and a dangling region comprising 2 nucleotides, a first side of a first stem comprising 5 nucleotides, a first side of a second stem comprising 5 nucleotides, A first end loop comprising 5 nucleotides, a second side of a second stem comprising 5 nucleotides, a first side of a third stem comprising 4 nucleotides, a second end loop comprising 4 nucleotides, a third stem comprising 4 nucleotides There is a bulge containing 1 nucleotide between the third and fourth nucleotides on the second side, the second side of the third stem, the first side of the fourth stem containing 4 nucleotides, the fourth stem A bulge containing 3 nucleotides exists between the second and third nucleotides on the first side of A secondary structure defined by a dangling region comprising a tide; and a fourth stem, wherein the second polynucleotide comprises at least 14 nucleotides up to 64 nucleotides and comprises 5 nucleotides And a secondary structure defined by the second side of the first stem comprising 5 nucleotides. The composition of claim 2, wherein the first polynucleotide comprises SEQ ID NO: 1. The composition of claim 2, wherein the second polynucleotide comprises SEQ ID NO: 2. A composition comprising a first polynucleotide, a second polynucleotide and a third polynucleotide comprising:
A first polynucleotide comprising a dangling region comprising at least 6 nucleotides up to 56 nucleotides and comprising from about 1 nucleotide to about 3 nucleotides, and a first side of the first stem comprising from about 4 nucleotides to about 10 nucleotides; Including a secondary structure defined by the presence of a bulge comprising about 1 to about 3 nucleotides on the first side of the first stem;
The second polynucleotide comprises at least 13 nucleotides up to 84 nucleotides and comprises about 4 nucleotides to about 10 nucleotides on the second side of the first stem, the second side of the first stem about 1 nucleotides to about A bulge comprising about 4 to about 10 nucleotides, a first side of a second stem comprising about 3 to about 9 nucleotides, and a dangling region comprising about 1 to about 2 nucleotides, wherein a bulge comprising 3 nucleotides is present A dangling region comprising from about 3 nucleotides to about 9 nucleotides, wherein the third polynucleotide comprises at least 5 to 63 nucleotides and comprises from about 1 nucleotide to about 2 nucleotides. The second side of the second stem containing, and about 1 nu Composition comprising a secondary structure as defined by dangling region containing Reochido to about 2 nucleotides. A first polynucleotide comprising at least 11 to 61 nucleotides and comprising a dangling region comprising 2 nucleotides; a first side of the first stem comprising 7 nucleotides; a fifth nucleotide on the first side of the first stem A secondary structure defined by the presence of a bulge containing 2 nucleotides between and 6th nucleotide;
The second polynucleotide comprises at least 23 nucleotides to 73 nucleotides or less and includes 7 nucleotides on the second side of the first stem, between the 5th and 6th nucleotides on the second side of the first stem. A bulge comprising 2 nucleotides, a bulge comprising 7 nucleotides, a first side of a second stem comprising 6 nucleotides, and a dangling region comprising 1 nucleotide, comprising a secondary structure, and a third polynucleotide Includes a secondary structure defined by a dangling region comprising at least 8 to 58 nucleotides and comprising a dangling region comprising 1 nucleotide, a second side of a second stem comprising 6 nucleotides, and a dangling region comprising 1 nucleotide. The composition according to claim 5. The composition of claim 6, wherein the first polynucleotide comprises SEQ ID NO: 3. 7. The composition of claim 6, wherein the second polynucleotide comprises SEQ ID NO: 4. The composition of claim 6, wherein the third polynucleotide comprises SEQ ID NO: 5. A composition comprising a first polynucleotide and a second polynucleotide comprising:
A dangling region wherein the first polynucleotide comprises at least 10 nucleotides up to 79 nucleotides and comprises about 1 nucleotide to about 3 nucleotides; the first side of the first stem comprising about 2 nucleotides to about 6 nucleotides; about 3 nucleotides A secondary structure defined by a first side of an inner loop comprising about 9 nucleotides, a first side of a second stem comprising about 3 nucleotides to about 9 nucleotides, and a dangling region comprising about 1 nucleotides to about 2 nucleotides And an internal loop comprising from about 3 nucleotides to about 7 nucleotides on the second side of the second stem, wherein the second polynucleotide comprises at least 10 nucleotides up to 77 nucleotides and comprises about 3 nucleotides to about 9 nucleotides The second side of from about 2 nucleotides to about 6 nucleotides The second side of the first stem comprising fault, and compositions comprising a secondary structure as defined by dangling region comprising about 2 nucleotides to about 5 nucleotides. A first polynucleotide comprising at least 19 to 69 nucleotides and a dangling region comprising 2 nucleotides, a first side of a first stem comprising 4 nucleotides, a first side of an internal loop comprising 6 nucleotides, 6 nucleotides Including a secondary structure defined by a first side of a second stem comprising a dangling region comprising 1 nucleotide; and a second polynucleotide comprising at least 18 to 68 nucleotides and 6 nucleotides Comprising a secondary structure defined by a second side of the second stem comprising, a second side of the inner loop comprising 5 nucleotides, a second side of the first stem comprising 4 nucleotides, and a dangling region comprising 3 nucleotides, The composition according to claim 10. 12. The composition of claim 11, wherein the first polynucleotide comprises SEQ ID NO: 6. 12. The composition of claim 11, wherein the second polynucleotide comprises SEQ ID NO: 7. A polynucleotide comprising at least 12 to 84 nucleotides, the first side of the stem comprising from about 3 nucleotides to about 9 nucleotides, the inner side comprising from about 2 nucleotides to about 5 nucleotides on the first side of the stem The first side is present, a terminal loop comprising about 2 nucleotides to about 6 nucleotides, a second side of the stem comprising about 3 nucleotides to about 9 nucleotides, and about 1 nucleotide to about 3 nucleotides on the second side of the stem. A polynucleotide comprising a secondary structure defined by a dangling region comprising a second side of the inner loop comprising and comprising from about 1 nucleotide to about 2 nucleotides. 15. The polynucleotide of claim 14, comprising at least 22 to 72 nucleotides, wherein the first side of the stem comprising 6 nucleotides, between the third and fourth nucleotides on the first side of the stem There is a first side of an internal loop containing 3 nucleotides, a terminal loop containing 4 nucleotides, a second side of the stem containing 6 nucleotides, and between the third and fourth nucleotides on the second side of the stem A polynucleotide comprising a secondary structure present by a second side of the inner loop comprising 2 nucleotides and defined by a dangling region comprising 1 nucleotide. The polynucleotide of claim 15 comprising SEQ ID NO: 8. A composition comprising a first polynucleotide, a second polynucleotide, a third polynucleotide, a fourth polynucleotide and a fifth polynucleotide comprising:
The first polynucleotide comprises at least 3 nucleotides up to 59 nucleotides and less, and the first side of the first stem comprising from about 2 nucleotides to about 6 nucleotides, and the second stem second comprising from about 1 nucleotides to about 3 nucleotides. Including a secondary structure defined by one side;
The second polynucleotide comprises at least 3 nucleotides to 58 nucleotides or less, the second side of the second stem comprising from about 1 nucleotide to about 3 nucleotides, and the first of the third stem comprising from about 2 nucleotides to about 5 nucleotides. Including secondary structures defined by sides;
The third polynucleotide comprises at least 7 nucleotides up to 68 nucleotides and comprises about 2 nucleotides to about 5 nucleotides on the second side of the third stem, on the second side of the third stem about 1 nucleotides to about A first side of a fourth stem comprising from about 1 nucleotide to about 3 nucleotides, a bulge comprising from about 1 nucleotide to about 3 nucleotides, and a fifth stem comprising from about 2 nucleotides to about 5 nucleotides, wherein a bulge comprising 2 nucleotides is present A secondary structure defined by the first side of
The fourth polynucleotide comprises at least 8 nucleotides to 70 nucleotides or less and the second side of the fifth stem comprising from about 2 nucleotides to about 5 nucleotides, a bulge comprising from about 3 nucleotides to about 7 nucleotides, from about 1 nucleotide to Comprising a secondary structure defined by the first side of the sixth stem comprising about 3 nucleotides and a dangling region comprising about 2 to about 5 nucleotides; and the fifth polynucleotide comprises at least 5 to 65 nucleotides or less And a dangling region comprising about 1 nucleotide to about 3 nucleotides, the second side of the sixth stem comprising about 1 nucleotide to about 3 nucleotides, the second of the fourth stem comprising about 1 nucleotide to about 3 nucleotides Side, and from about 2 nucleotides to about 6 nucleotides Composition comprising a secondary structure defined by the second side of the non-first stem. The first polynucleotide comprises a secondary structure defined by a first side of a first stem comprising at least 6 to 56 nucleotides and comprising 4 nucleotides and a second stem comprising 2 nucleotides. Including;
The second polynucleotide comprises at least 5 to 55 nucleotides and has a secondary structure defined by the second side of the second stem comprising 2 nucleotides and the first side of the third stem comprising 3 nucleotides Including;
The third polynucleotide comprises at least 10 to 60 nucleotides or less, and includes a second side of the third stem containing 3 nucleotides, a second nucleotide between the second and third nucleotides on the second side of the third stem. A secondary structure defined by a first side of a fourth stem comprising 2 nucleotides, a bulge comprising 1 nucleotide, and a first side of a fifth stem comprising 3 nucleotides, wherein a bulge comprising nucleotides is present;
The fourth polynucleotide comprises at least 13 to 63 nucleotides and less, and the second side of the fifth stem containing 3 nucleotides, the bulge containing 5 nucleotides, the first side of the sixth stem containing 2 nucleotides, and 3 A sixth structure comprising a dangling region defined by a dangling region comprising nucleotides; and a fifth polynucleotide comprising a dangling region comprising at least 10 to 50 nucleotides and comprising 2 nucleotides; 18. The composition of claim 17, comprising a secondary structure defined by the second side of the second stem of the fourth stem comprising 2 nucleotides and the second side of the first stem comprising 4 nucleotides. 19. The composition of claim 18, wherein the first polynucleotide comprises 5'-cgucccc-3 '. The composition of claim 18, wherein the second polynucleotide comprises 5'-ggggca-3 '. 19. The composition of claim 18, wherein the third polynucleotide comprises SEQ ID NO: 9. 19. The composition of claim 18, wherein the fourth polynucleotide comprises SEQ ID NO: 10. 19. The composition of claim 18, wherein the fifth polynucleotide comprises SEQ ID NO: 11. A polynucleotide comprising at least 13 to 84 nucleotides, a dangling region comprising from about 2 nucleotides to about 5 nucleotides, a first side of a stem comprising from about 2 nucleotides to about 5 nucleotides, from about 6 nucleotides to about 16 nucleotides A polynucleotide comprising a secondary structure defined by a terminal loop comprising: a second side of the stem comprising from about 2 nucleotides to about 5 nucleotides; and a dangling region comprising from about 1 nucleotide to about 3 nucleotides. 25. The polynucleotide of claim 24 comprising at least 22 to 72 nucleotides, a dangling region comprising 3 nucleotides, a first side of a stem comprising 3 nucleotides, a terminal loop comprising 11 nucleotides, comprising 3 nucleotides A polynucleotide comprising a secondary structure defined by a second side of the stem and a dangling region comprising 2 nucleotides. 26. The polynucleotide of claim 25 comprising SEQ ID NO: 12.