WO2011035456A1 - 通过计算机辅助设计来获得高亲和力的蛋白质的方法 - Google Patents

通过计算机辅助设计来获得高亲和力的蛋白质的方法 Download PDF

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WO2011035456A1
WO2011035456A1 PCT/CN2009/001079 CN2009001079W WO2011035456A1 WO 2011035456 A1 WO2011035456 A1 WO 2011035456A1 CN 2009001079 W CN2009001079 W CN 2009001079W WO 2011035456 A1 WO2011035456 A1 WO 2011035456A1
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antibody
protein
affinity
binding
energy
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PCT/CN2009/001079
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English (en)
French (fr)
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郭亚军
李博华
王皓
侯盛
赵磊
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上海抗体药物国家工程研究中心有限公司
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Priority to EP09849644.1A priority Critical patent/EP2482212A4/en
Priority to US13/497,859 priority patent/US20120191435A1/en
Priority to PCT/CN2009/001079 priority patent/WO2011035456A1/zh
Priority to BR112012006727A priority patent/BR112012006727A2/pt
Priority to JP2012530069A priority patent/JP2013505707A/ja
Priority to CN2009801615123A priority patent/CN102511045A/zh
Priority to AU2009353265A priority patent/AU2009353265A1/en
Priority to CA2775159A priority patent/CA2775159A1/en
Publication of WO2011035456A1 publication Critical patent/WO2011035456A1/zh

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    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07KPEPTIDES
    • C07K16/00Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies
    • C07K16/18Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans
    • C07K16/32Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against translation products of oncogenes
    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07KPEPTIDES
    • C07K16/00Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies
    • C07K16/18Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans
    • C07K16/28Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
    • C07K16/2803Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants against the immunoglobulin superfamily
    • C07K16/2818Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants against the immunoglobulin superfamily against CD28 or CD152
    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07KPEPTIDES
    • C07K16/00Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies
    • C07K16/18Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans
    • C07K16/28Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
    • C07K16/2887Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants against CD20
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6803General methods of protein analysis not limited to specific proteins or families of proteins
    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07KPEPTIDES
    • C07K2317/00Immunoglobulins specific features
    • C07K2317/20Immunoglobulins specific features characterized by taxonomic origin
    • C07K2317/24Immunoglobulins specific features characterized by taxonomic origin containing regions, domains or residues from different species, e.g. chimeric, humanized or veneered
    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07KPEPTIDES
    • C07K2317/00Immunoglobulins specific features
    • C07K2317/50Immunoglobulins specific features characterized by immunoglobulin fragments
    • C07K2317/56Immunoglobulins specific features characterized by immunoglobulin fragments variable (Fv) region, i.e. VH and/or VL
    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07KPEPTIDES
    • C07K2317/00Immunoglobulins specific features
    • C07K2317/50Immunoglobulins specific features characterized by immunoglobulin fragments
    • C07K2317/56Immunoglobulins specific features characterized by immunoglobulin fragments variable (Fv) region, i.e. VH and/or VL
    • C07K2317/565Complementarity determining region [CDR]
    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07KPEPTIDES
    • C07K2317/00Immunoglobulins specific features
    • C07K2317/90Immunoglobulins specific features characterized by (pharmaco)kinetic aspects or by stability of the immunoglobulin
    • C07K2317/92Affinity (KD), association rate (Ka), dissociation rate (Kd) or EC50 value

Definitions

  • the present invention is in the field of medical biotechnology, and in particular, relates to a method of obtaining an antibody or protein molecule having improved affinity by computer. Background technique
  • the method for increasing antibody affinity is mainly to use the original parental monoclonal antibody as a template for transformation, and to construct a mutant antibody library (such as ribosome display, yeast two-hybrid, phage display antibody library, etc.) for screening, and finally achieve higher affinity.
  • Monoclonal antibody have significant limitations: It is difficult to construct a mutant library that is mutated to any amino acid, covering all sites; it is time-consuming and labor-intensive to construct an antibody library and its screening process; when the target protein is difficult to express or screen in vitro When the combination is unstable, it is difficult to use the antibody library method for screening.
  • the invention firstly summarizes the laws in the process of antibody affinity maturation, and establishes a computer-aided design method based on the evolutionary law of antibodies to rapidly and efficiently increase the affinity of antibodies (accuracy rate is greater than 57%).
  • the present invention further uses this method to carry out an improvement test of the affinity of a fusion protein receptor to obtain a similar accuracy.
  • the method of the present invention can be widely applied to enhance the interaction between protein complexes and accelerate the development of proteins having biological and medical significance.
  • the combination of antibody evolution law and computer simulation technology provides a new idea for computer-aided design in the future.
  • the computer aided method of the invention for increasing antibody affinity comprises the steps of:
  • a method for obtaining high affinity antibodies or protein molecules by computer aid comprising the steps of:
  • the mutation sites are selected according to the characteristics of the changes in the crystal structure during the affinity maturation of the known antibody or protein, and those having a bias distribution on the contact surface and surface of the protein complex are selected.
  • the amino acid serves as a candidate mutant amino acid.
  • the selected mutation site is located at the periphery of the contact surface of the antibody or protein molecule with the antigen or binding protein and does not interact with the antigen or binding protein.
  • step 2) the virtual mutation site is mutated to the following amino acids:
  • Step 4) includes:
  • step 3 a) sorting the initially optimized antibodies or protein molecules obtained in step 3) according to the overall energy; b) determining, based on the crystal structure information of the antibody or protein molecule complex, an amino acid located on the target molecule that plays a key role in binding;
  • the selection of the mutation site is mainly based on the known characteristics of changes in the crystal structure during the affinity maturation of the antibody, and the amino acids which are distributed in the contact surface and surface of the protein complex are selected;
  • the strategy for selecting mutations should first satisfy the following aspects: i) The site of the mutation is preferably located in the CDR region, and try to avoid possible immunogenicity; ii) not too many sites of mutation, can cooperate in a limited number of positions Significantly improve affinity without overly changing the interface of the antibody; iii) The final method must be efficient, accurate, and capable of rapidly obtaining antibodies with increased affinity through limited mutations.
  • the mutation position selected by the invention has the following two characteristics: i) maximally ensuring that the single point mutation has an increased potential position; ii) maximizing the optimal synergy of the combined mutation, greatly improving the amino acid The affinity of the antibody.
  • Clark LA et al. performed a mathematical and statistical analysis of the antigen-antibody co-crystallization in the PDB database, and obtained the bias of the amino acid composition generally distributed on the antibody interface through information mining technology [see Figure 2, Clark LA, Ganesan S , Papp S, et al. Trends in antibody sequence changes during the somatic hypermutation process. [J]. J Immunol. 2006, 177(1): 333-340; Lo CL, Chothia C, Janin J. The atomic structure of protein -protein recognition sites. [J]. J Mol Biol. 1999, 285(5): 2177-2198].
  • the present invention selects amino acids which have a high probability of appearing on the contact surface and surface of the antibody as a selective amino acid for mutation. Based on the accuracy of the existing predictions, this purposeful screening eliminates the predicted false positive amino acids that rarely appear on the antibody interface, making it possible to improve the accuracy of the prediction.
  • the present invention selects a position located around the contact surface of the antigen antibody as a mutation site, and preferably an amino acid site which does not interact with the antigen.
  • the antibody mutation site selected by the present invention has the following characteristics: (1) the selected mutation site: located at the periphery of the antibody contact surface and preferably does not form an interaction with the antigenic substance; (2) the selected mutant acid is selected from Glu , Arg, Asn, Ser, Thr, Tyr, Lys, Asp, Pro, and Ala.
  • the module is hydrogenated, and all heavy atoms of the immobilized protein minimize the energy of 5000 steps (in steps of lfs).
  • the structure obtained by minimizing the energy is obtained, and the distance from the antigen 6A is set to be the contact surface. Add water to the distance of 25A around the contact surface.
  • the selected mutation position is subjected to amino acid mutation, and the amino acid molecule at a distance of 6A from the mutation site is subjected to auto-rotamer to select the optimal starting site in space [Dunbrack R L. Rotamer Libraries in the 21st Century [J]. Current Opinion In Structural Biology. 2002, 12(4): 431-440. Ponder JW, Richards F M.
  • the Quartic VDW van der waals
  • coulombic interactions off method is used for initial screening to find possible binding conformations.
  • the constant of van der Waals force and hydrogen bond is reduced to 0.5 in this process, and 6000 steps are searched each time, resulting in 60 After preliminary optimization of the conformation.
  • the cell-mutipole method is used to make a more detailed search for the first 60 constellations [Ding HQ, Karasawa N, Goddard 11. Atomic level simulations on a million particles: The cell multipole method for Coulomb and London nonbond interactions ⁇ ] J. Chem. Phys.
  • the selected complex is introduced into charmm V34bl (Bernard, RB and EB Robert, et al. (1983). "CHARMM: A program for macromolecular energy, minimization, and dynamics calculations.” J Comput Chem. 4(2): 187 -217. ), using the HBUILD command to hydrogenate the heavy atoms of the PDB structure, using the charmm force field (Becker, OM and M. Karplus (2005). Guide to Biomolecular Simulations (Focus on Structural)
  • Emm is the molecular mechanics energy calculated by CVFF force field
  • AGsolv is the solvation free energy
  • -TAS is the entropy of solute.
  • the molecular mechanics energy consists of three parts: intramolecular energy, van der Waals force and electrostatic interaction. Since each antibody does not change in its binding to the unbound antigen, the internal energy portion of the molecular mechanical energy contributes zero to the binding free energy.
  • AGPB indicates electrostatic solvation energy
  • AGnp indicates non-polar solvation energy
  • the Quartic VDW (van der waals) with coulombic interactions off method can be used to optimize the structure after the mutation to generate a certain number of preliminary optimized structures that meet the conditions.
  • the conformational search of protein molecules is still a bottleneck in structural simulation.
  • the present invention first evaluates the van der waals using a rigid sphere model of the single cylinder, and does not calculate the influence of the Coulomb force between the molecules. In turn, the energy interface becomes smoother and the local energy minimum can be picked out relatively easily.
  • the Quartic VDW (van der waals) with coulombic interactions off method is typically used to perform an initial constellation space search. Then, the generated initial structure can be further optimized by the cell_mutipole method to perform a final fine conformation search to obtain an energy-optimized antibody or protein molecule.
  • the optimized structure is subjected to comprehensive evaluation of energy scoring and root mean square deviation (RMSD) to obtain predicted mutation points of antibodies with increased affinity, and the specific steps include: firstly, the above energy-optimized antibody or protein molecule Sorting according to the total energy, sorting from high to low; then determining the amino acids that play a key role in the binding on the target molecule according to the crystal structure information of the protein complex; after mutating the amino acids that play a key role in the binding Perform RMSD analysis (heavy atom) with the crystal structure, select those with the lowest total energy and RMSD The calculation of the binding energy is performed on a relatively small mutant structure; finally, a simulated structure capable of increasing the affinity of the antibody or protein molecule is obtained.
  • RMSD root mean square deviation
  • the present invention has developed a method for increasing the affinity of an antibody or protein molecule by summarizing and attempting to finally combine the laws of antibody affinity maturation from conventional computer simulation techniques.
  • the method of the present invention significantly improves the accuracy of computer simulations to improve protein affinity, greatly reduces computational effort, reduces laboratory costs for increasing antibody affinity, and makes protein affinity changes simple and efficient.
  • Figure 1 Experimental flow chart showing the method of the invention
  • Figure 2 shows the bias analysis of the amino acid distribution
  • Figure 3 shows the experimental site to confirm the mutation site of Trastuzumab affinity; as shown, it is the heavy chain 55 Asn, the heavy chain 102 Asp, the light chain 28 Asp and the light chain 93 Thr.
  • Figure 4 shows the nucleotide sequence and amino acid sequence of the heavy chain variable region (VH) and light chain variable region (VL) of Trastuzumab;
  • Figure 5 shows the experimental site to verify the mutation site of Rituximab affinity; as shown, H57Asp and H102Tyr;
  • FIG. 6 Nucleosides showing the Rituximab heavy chain variable region (VH) and light chain variable region (VL)
  • Figure 7 Sensorgram showing biacore detection of Rituximab and ituximab mutants at the same sample concentration
  • Figure 8 shows the nucleotide sequence and amino acid sequence of the extracellular region of CTLA-4
  • Figure 9 Sensorgram showing biacore detection of Abatacept and CTLA-4/Ig mutants at the same sample concentration.
  • Trastuzumab (Herceptin) is a humanized monoclonal antibody targeting HER2 developed by Genentech, Inc., and has a high affinity for the HER2 receptor for the treatment of HER2/neu overexpressing metastatic breast cancer.
  • the invention simulates the process of improving the affinity in vitro by computer, overcomes the limitation of the affinity maturation process in the body, and further obtains the Trastuzumab with the same epitope but high affinity. It has been repeatedly verified by experiments in vitro and in vivo to finally obtain a new type of Tratuzumabo with stronger antitumor activity.
  • the optimized structure was obtained, and the distance from the antigen 6A was set to be the contact surface. Water molecules are added at a distance of 25 A around the contact surface.
  • the selected mutation position was subjected to amino acid mutation, and then based on the rotamer library summarized by Ponder and Richards, the auto-rotamer selection space starting point was selected for the amino acid molecule at a distance of 6A from the mutation site.
  • the peripheral water molecules and antibody molecules other than the contact interface are fixed and subjected to simulated annealing to find the most likely contact pattern.
  • lymphocyte separation solution Separating healthy human lymphocytes with lymphocyte separation solution (Dingguo Biotechnology Development Co., Ltd.) Cloning human and mouse kappa immunoglobulin constant and J region genes conserve homology in functional segments. Hieter PA, Max EE, Seidman JG, Maizel JV Jr, Leder R Cell 1980 Nov;22(l Pt 1): 197-207) and the literature (The nucleotide sequence of a human immunoglobulin C gamma 1 gene. Ellison JW, Berson BJ, Hood LE. Nucleic Acids Res.
  • HC sense GCTAG CACCA AGGGC CCATC GGTCT TCC
  • HC antisense TTTAC CGGGA GACAG GGAGA GGCTC TTC
  • Lc sense ACTGT GGCTG CACCA TCTGT CTTCA TCT
  • Lc antisense ACACT CTCCC CTGTT GAAGC TCTTT GTG.
  • the antibody heavy and light chain constant region genes were amplified by RT-PCR reaction.
  • the PCR product was purified by agarose gel electrophoresis and cloned into pGEM-T vector (Promega). After sequencing, it was confirmed that the correct clone was obtained.
  • SEQ ID NO: 1 shows the nucleotide sequence of the heavy chain constant region (CH)
  • SEQ ID NO: 2 shows the amino acid sequence of the heavy chain constant region (CH)
  • SEQ ID NO: 3 and SEQ ID NO: 4 respectively show The nucleotide sequence and amino acid sequence of the light chain constant region (CL).
  • the correct clones in this example were designated pGEM-T/CH and pGEM-T/CL.
  • Humanized antibody heavy chain gene was synthesized by overlapping PCR using Her2VH gene and pGEM-T/CH vector as template. The reaction conditions were: 95TM 5 min; 94 ° C 50 sec, 58 ° C 50 sec, 72 ° C 50 sec, 30 Cycle; 72 ° C for 10 minutes.
  • the 5' end of the humanized heavy chain gene contains the restriction enzyme site Hind III and the signal peptide gene sequence, and the 3' end contains the translation stop codon TAA and the restriction enzyme site EcoR I.
  • the signal peptide gene sequence is: ATG GAT TTT CAG GTG CAG ATT TTC AGC TTC CTG CTAATC AGT GCC TCA GTC ATAATA TCC AGA GGA.
  • the PCR amplification product was separated by agarose gel electrophoresis, and the target band was recovered and cloned into pGEMT vector, and positive clones were screened for sequencing.
  • the clones with the correct sequencing were digested with ffindlll and EcoR I, and the humanized antibody heavy chain fragment Her2VHCH was purified by agarose gel electrophoresis, and the capsular granule pcDNA3.1 ( + ) digested with Hind III and EcoR I (United States) Invitrogen products were ligated to construct the adult-derived heavy chain eukaryotic expression vector pcDNA3.1 ( + ) ( Her2VHCH ).
  • the humanized antibody light chain gene was synthesized by overlapping PCR using the Her2VL gene and the pGEM-T/CL vector as a template.
  • the reaction conditions were: 95 ° C for 15 minutes; 94 ° C for 50 seconds, 58 ° C for 50 seconds, 72 ° C for 50 seconds. , 30 cycles; 72 ° C for 10 minutes, the PCR product Her2VLCL, the 5' end contains restrictions
  • the enzyme site Hindlll and the signal peptide gene sequence have a translation termination code TAA and a restriction enzyme site EcoR I at the 3' end.
  • the signal peptide gene sequence is: ATG GAT TTT CAG GTG CAG ATT TTC AGC
  • the correct clone was digested with Hind III and EcoR I, and purified by agarose gel electrophoresis to recover the humanized antibody light chain fragment C2B8VLCL, and with Hind III and The EcoR I digested plasmid pcDNA3.1 vector (product of Invitrogen, USA) was ligated to construct an adult-derived light chain eukaryotic expression vector pcDNA3.1 (Her2VLCL).
  • 3x105 CHO-K1 cells (ATCC CRL-9618) were seeded in 3.5 cm tissue culture dishes, and transfected when the cells were cultured to 90%-95% confluence: plasmid lO g (plasmid pcDNA3.1(+) ( Her2VHCH ) 4 g , plasmid pcDNA3.1 ( Her2VLCL ) 6 ⁇ ⁇ ) and 20 ⁇ 1 Lipofectamine2000 Reagent (Invitrogen) were dissolved in 500 ⁇ 1 serum-free DMEM medium, allowed to stand at room temperature for 5 minutes, mixed the above two liquids, and incubated at room temperature for 20 minutes to make DNA-liposome complex formation, during which the serum-containing medium in culture was replaced with 3 ml of serum-free DMEM medium, and then the formed DNA-liposome complex was added to the plate, C0 2 incubator culture After 4 hours, 2 ml of DMEM complete medium containing 10% serum was added, and the culture was continued in a C0 2 incubator
  • the highly expressed clones were screened for serum-free medium.
  • the culture was expanded, and the humanized antibody trastuzumab was isolated and purified using a Protein A affinity column (product of GE).
  • the purified antibody was dialyzed against PBS, and finally the concentration of the purified antibody was quantitatively determined by ultraviolet absorption.
  • the construction of the Trastuzumab antibody mutant was carried out by means of overlapPCR, and the method of construction and expression and purification was the same as that of the Trastuzumab humanized antibody.
  • a total of 10 antibody mutants were constructed, ranging from Hmutl to HmutlO.
  • the specific amino acid sequences are shown in SEQ ID NO: 5 ⁇ SEQ, respectively.
  • Her2 extracellular domain protein was expressed and purified according to Carter's method, and then coated with an ELISA plate at 37 degrees for 2 hours; then, a fixed concentration of the antibody was incubated with the diluted diluted Her2 membrane outer region protein for 1 hour at room temperature. The amount of affinity is then calculated by identifying the amount of free antibody in the incubation antibody antigen complex. See [Carter P, et al. (1992) for details. Humanization of an anti-pl85HER2 antibody for human cancer therapy. Proc Natl Acad Sci USA 89: 4285-4289; Friguet B, Chaffotte AF, Djavadi-Ohaniance antigen-antibody complexes by enzyme-linked immunosorbent assay.
  • H57Tyr lie 0.06 ⁇ 0.01
  • the experimental error is represented by SD, which is derived from three independent experiments; WT, which is Trastuzumab antibody; ND, which means that the affinity is too weak to detect.
  • KdWT 0.16 ⁇ 0.02 nM
  • KdHerc 0.21 ⁇ 0.04 nM
  • Hmutl 0 H102Asp Lys 2.31 ⁇ 0.20 3.03 ⁇ 0.26 The error is expressed in SD and is derived from the results of three independent experiments.
  • WT is an unmutated antibody sequence; Here is indicated as a commercially available Herceptin. Raising the Rituximab antibody affinity test
  • Rituximab is a genetically engineered human and mouse chimeric monoclonal antibody consisting of murine Fab and human Fc with a molecular weight of approximately 150 kDa, which specifically binds to the CD20 antigen on the surface of B lymphocytes, ultimately leading to the death of B lymphocytes. Chikin's lymphoma and the like.
  • the contact surface on Rituximab is analyzed: Usually, the solvation contact area of the short peptide with the protein is 400-700A, which is usually smaller than the solvation contact area of the protein-protein contact, and the ituximab and CD20 short peptide.
  • the contact SAS is 440A, and the SAS in the interaction between short peptides and proteins is relatively small. A virtual mutation was sequentially performed on the peripheral amino acids at the contact surface.
  • the selected mutation position was subjected to amino acid mutation, and then based on the rotamer library summarized by Ponder and Richards, the amino acid molecule at a distance of 6A from the mutation site was subjected to an optimization start site on the auto_rotamer selection space.
  • the peripheral water molecules and antibody molecules other than the contact interface are fixed and simulated annealing is performed to find the most likely contact pattern.
  • the structure generated by the above process is RMSD ( Root mean square deviation ) analysis, comparing the amino acid of the antigenic peptide on the antigenic peptide in the resulting structural complex with the amino acid of the pre-mutation amino acid. Finally, we choose those with the lowest total energy and relatively low RMSD. The structure is selected.
  • the selected structure is introduced into the charmm for energy minimization. Energy evaluation was performed using the MM-PBSA method. In order to evaluate the accuracy of the computer prediction method, we selected experimentally validated amino acids predicted to increase affinity and amino acids with decreased predicted affinity at three candidate sites.
  • HC sense GCTAG CACCA AGGGC CCATC GGTCT TCC
  • HC antisense TTTAC CGGGA GACAG GGAGA GGCTC TTC
  • Lc sense ACTGT GGCTG CACCA TCTGT CTTCA TCT
  • Lc antisense ACACT CTCCC CTGTT GAAGC TCTTT GTG.
  • the antibody heavy and light chain constant region genes were amplified by RT-PCR reaction.
  • the PCR product was purified by agarose gel electrophoresis and cloned into pGEM-T vector. After sequencing, it was confirmed that the correct clone was obtained.
  • SEQ ID NO: 1 and SEQ ID NO: 2 show the nucleotide sequence and amino acid sequence of the heavy chain constant region (CH), respectively.
  • SEQ ID NO: 3 and SEQ ID NO: 4 show the nucleotide sequence and amino acid sequence of the light chain constant region (CL), respectively.
  • the correct clones in this example were recorded as pGEM-T/CH and pGEM-T/CL.
  • Example 7 Construction of an anti-CD20 chimeric antibody Rituximab
  • the anti-human CD20 monoclonal antibody Rituximab (C2B8) heavy chain variable region gene (C2B8VH) and light chain variable region gene (C2B8VL) were synthesized.
  • Figure 6 shows the nucleoside and amino columns of the C2B8 heavy and light chain variable regions.
  • Humanized antibody heavy chain gene was synthesized by overlapping PCR using C2B8VH gene and pGEM-T/CH vector as template. The reaction conditions were: 95 ° C for 15 minutes; 94 ° C for 50 seconds, 58 ° C for 50 seconds, 72 ° C for 50 seconds. , 30 cycles; 72 ° C for 10 minutes.
  • the 5' end of the humanized heavy chain gene contains the restriction enzyme site Hindlll and the signal peptide gene sequence, and the 3' end contains a translation stop codon TAA and a restriction enzyme site EcoR l.
  • the signal peptide gene sequence is: ATG GGATTC AGC AGGATC TTT CTC TTC CTC CTG TCA GTAACT ACA GGT GTC CAC TCC.
  • the PCR amplification product was separated by agarose gel electrophoresis, and the target band was recovered and cloned into pGEMT vector, and positive clones were screened for sequencing.
  • the humanized antibody light chain gene was synthesized by overlapping PCR using C2B8VL gene and pGEM-T/CL vector as template.
  • the reaction conditions were: 95 ° C for 15 minutes; 94 ° C for 50 seconds, 58 ° C for 50 seconds, 72 ° C 50 Seconds, 30 cycles; , 2.
  • the PCR product C2B8 VLCL was obtained, which contained the restriction enzyme site Hindlll and the signal peptide gene sequence at the 5' end, and the translation termination code TAA and the restriction enzyme site EcoR I at the 3' end.
  • the signal peptide gene sequence is ATG GAT TTT CAA GTG CAG ATT TTC.
  • the correct clone was digested with Hindlll and EcoR I.
  • the humanized antibody light chain fragment C2B8VLCL was purified by agarose gel electrophoresis, and the Hindlll and EcoR I enzymes were used.
  • the cut plasmid pcDNA3.1 vector (product of Invitrogen, USA) was ligated to construct an adult-derived light chain eukaryotic expression vector pcDNA3.1 (C2B8VLCL).
  • 3 x l05 CHO-K1 cells (ATCC CRL-9618) were inoculated in 3.5 cm tissue culture subculture, and transfected when the cells were cultured to 90%-95% confluence: plasmid 10 g (plasmid pcDNA3.1(+)(C2B8VHCH) 4 g, plasmid pcDNA3.1 (C2B8VLCL) 6 g) and 20 ⁇ 1 Lipofectamine 2000 Reagent (Invitrogen) were dissolved in 500 ⁇ 1 serum-free DMEM medium, allowed to stand at room temperature for 5 minutes, mixed with the above two liquids, and incubated at room temperature for 20 Minutes to form a DNA-liposome complex, during which the serum-containing medium in the cultured JUL was replaced with 3 ml of serum-free DMEM medium, and then the formed DNA-lipid complex was added to the plate, C02 incubation After 4 hours of tank culture, 2 ml of DMEM complete medium containing 10% serum was added, and the
  • the C2B8 antibody mutant was constructed by overlapPCR, and its construction and expression were the same as the C2B8 chimeric antibody. A total of 10 antibody mutants were constructed, Rmutl to Rmut7, and the specific amino acid sequences are shown in SEQ ID NO: 25 ⁇ SEQ ID NO: 38, respectively.
  • the SA chip was equilibrated in 50 ⁇ l/ ⁇ PBS solution at 25 ° C for 30 min, and then activated 3 times with lM NaCl 50 mM NaOH activation solution for 1 min each; biotin-labeled antigen peptide (which is part of the human CD20 molecular extramembrane region) Fragments, whose sources are found in the literature ( Structural Basis for Recognition of CD20 by Therapeutic Antibody Rituximab. Du, J.; Wang, H.; Zhong, C.
  • the affinity of the C2B8 antibody mutant Rmut3 was increased by 6.08-fold, and the affinity of the mutant Rmut7 was increased by 3.96-fold. Its prediction accuracy reached 71.4%.
  • the mutation sites in which the affinity is shown to be increased are the heavy chain 57 Asp and the heavy chain 102 Tyr.
  • ND indicates no biacore detection
  • WT indicates unmutated C2B8
  • ritu indicates commercially available rituximab.
  • Cytotoxic T-Lymphocyte Antigen 4 (CTLA-4) is a homodimer, which is mainly expressed in activated T cells and has high homology with CD28.
  • Abatacept is a fusion protein of extracellular domain of CTLA-4 and immunoglobulin. It inhibits the activation of T cells by binding to B7 molecule, and then acts as a specific co-stimulatory factor modulator for the treatment of anti-TNF. - ⁇ treatment of ineffective rheumatoid arthritis.
  • Belatacept was also developed by Squibb, which has only two amino acid changes with Abatacept, but significantly increases affinity with ligands (CD80, CD86).
  • the CTDA4/Ig and CD86 co-crystallized PDB file (li85) was introduced into Insightl Accelrys), loaded into the CVFF force field, and the heavy atoms of the immobilized protein were used to minimize the energy of the added hydrogen bonds by hydrogenation of Biopol mer: Perform the Steepest descent method for energy minimization until the maximum derivative is less than 1000 kcal/mol/A.
  • the gradient method performs energy minimization, a total of 10,000 steps (step lfs), and finally the convergence reaches 0.01.
  • the optimized structure was obtained, and the distance from the antigen 6A was set to be the contact surface. Water molecules are added at a distance of 25 A around the contact surface.
  • the selected mutation position was subjected to amino acid mutation, and then based on the rotamer library summarized by Ponder and Richards, the amino acid molecule at a distance of 6A from the mutation site was subjected to an auto-rotamer selection space on the optimization starting site.
  • the peripheral water molecules and antibody molecules other than the contact interface are fixed and simulated annealing is performed to find the most likely contact pattern.
  • the influence factor of the van der Waals and Coulomb options is set to 0.5, and then the temperature is from 500K. 50 stages are performed at 280K, each stage is performed for 100fs, and the resulting structure is minimized in energy of 8000 steps.
  • the generated structure was subjected to the combination of binding energy, total energy and RMSD, and the most probable structure was selected to evaluate the binding energy between different mutants.
  • the PCR reactions were all initiated by hot start. Reaction conditions: 94 ° C for 15 minutes; 94 ° C for 45 seconds; 60 ° C for 45 seconds; 72 ° C for 1 minute and 10 seconds; 30 cycles; 72 ° C for 10 minutes.
  • FIG. 8 shows the nucleotide and amino acid sequences of CTLA-4.
  • SEQ ID NO: 39 and SEQ ID NO: 40 show the nucleotide sequence and amino acid sequence of the Fc region, respectively.
  • the correct clones in this example were recorded as pGEM-T/CT and pGEM-T/Fc.
  • the primers were designed to carry out overlapPCR of the synthesized signal peptide sequence SEQ ID NO: 41 and the cloned CTLA-4 extracellular gene fragment, and the correctly ligated fragment and the antibody Fc were subjected to overlapPCR, and the pGEM-T vector was used for sequencing. 4 mega-sequencing and correct cloning
  • the CTLA-4/Ig fusion receptor protein gene was digested with Hindlll and EcoR 1 and purified by agarose gel electrophoresis, and the plasmid pcDNA3.1(+) digested with Hindlll and EcoR I. (Products of Invitrogen, USA) Ligation, construction of the adult-derived heavy chain eukaryotic expression vector pcDNA3.1 (+), designated pcDNA3.1 (+) (CTLA-4/Ig).
  • Plasmid 10 ⁇ Plasmid pcDNA3.1 (+) (CTLA-4) /Ig) and 20 ⁇ 1 Lipofectamine2000 Reagent (Invitrogen) were dissolved in 500 ⁇ 1 serum-free DMEM medium, allowed to stand at room temperature for 5 minutes, and the above two liquids were mixed and incubated at room temperature for 20 minutes to form DNA-liposome complex.
  • the serum-containing medium in the culture medium was replaced with 3 ml of serum-free DMEM medium, and then the formed DNA-liposome complex was added to the plate, and 2 ml of serum containing 10% was added after incubation for 4 hours in a C0 2 incubator.
  • the complete medium of DMEM was placed in the C0 2 incubator to continue the culture.
  • the cells were replaced with 60 ( ⁇ g/ml G418 selection medium to screen for resistant clones.
  • the cell culture supernatant was screened by ELISA for high expression. Cloning: goat anti-human IgG (Fc) was coated on ELISA plate, overnight at 4.
  • the CTLA-4/Ig mutant was constructed by overlapPCR, and its construction (shown in Figure 8) was identical to the CTLA-4/Ig fusion protein in expression and purification.
  • the mutant amino acid sequences are shown in SEQ ID NO: 42 to SEQ ID NO: 50.
  • the CM5 chip was equilibrated in a 50 ⁇ l/ ⁇ phosphate buffered saline (PBS) solution at 25 ° C for 30 min, then ⁇ ⁇ -hydroxysuccinimide (NHS) and ⁇ 1-ethyl-3-(3-di) Methylaminopropyl)-carbodiimide (EDC) was mixed and the chip was activated with ⁇ /ml for 8 min.
  • PBS phosphate buffered saline
  • EDC 1-ethyl-3-(3-di) Methylaminopropyl)-carbodiimide
  • CTmut5 D63Leu Lys 1.85 ⁇ 0.16 1.97 ⁇ 0.17
  • CTmut6 D63Leu Tyr 2.29 ⁇ 0.31 2.44 ⁇ 0.33
  • CTmut9 D106Leu Asn 0.88 ⁇ 0.06 0.94 ⁇ 0.06
  • the experimental error is expressed in SD and determined by three different experiments.
  • WT represents the original fusion receptor that has not been mutated; abat, which represents commercially available Abatacept; industrial applicability
  • the method of the present invention can be widely applied to increase the affinity between protein complexes and accelerate the development of biologically and medically high affinity protein molecules.
  • the combination of antibody evolution law and computer simulation technology provides a new idea for computer-aided design in the future.

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Description

通过计算机辅助设计来获得高亲和力的蛋白质的方法 技术领域
本发明属于医药生物技术领域,具体地说, 涉及一种通过计算机辅助获 得提高的亲和力的抗体或蛋白分子的方法。 背景技术
上世纪八十年代以来,蛋白质结构被解析的数量逐年增加和界面友好的 结构分析软件的不断发展使我们能够更加深刻地理解分子相互识别的原子 基础。 早先在结构的基础上改造酶的特异性的研究取得了一些成功的例子, 这些证明了改造蛋白质功能在不远的将来成为可能。迄今为止,通过计算机 辅助设计,研究人员已经成功地在一些研究模型上改造酶的活性,提高抗体 亲和力,甚至通过改造产生自然界并不存在的催化活性。增强抗体亲和力对 于提高其检测灵敏度、延长解离时间、降低药物使用剂量和增强药效都具有 非常重要的意义。
目前,提高抗体亲和力的方法主要是以原亲本单抗为改造模板, 通过构 建其突变体抗体库(如核糖体展示、 酵母双杂交、 噬菌体展示抗体库等)进 行筛选, 最终袭得更高亲和力的单抗。 但是, 这些技术具有很大的局限性: 很难构建出足以覆盖所有位点的、突变成任何氨基酸的突变文库;构建抗体 库及其筛选过程费时费力;当目标蛋白难以表达或者在体外筛选的环境下结 合不稳定的时候, 就难以采用抗体库的方法进行筛选。
与以往的抗体库技术相比,计算机辅助设计可以通过虚拟突变的方法来 进行筛选, 大大节约了实验所用时间; 可对抗体结合域所有位点进行单点和 組合虚拟突变;其预测突变的氨基酸往往只有一个就可以显著提高抗体亲和 力。但现有的计算机辅助设计方法还存在准确率低和计算量过大的问题。例 如,在蛋白质的改造和模拟试驗中,生物信息学家对蛋白质的改造的尝试总 是将与配体相互接触面上的所有的氣基酸突变成除了脯氨酸以外的其他氨 基酸, 由于蛋白质间接触面上的氨基酸数量众多,将所有氨基酸不加选择地 进行突变需要完成相当大的计算量,而且受计算机运行速度的限制,在算法 上也需要取很多的近似值来简化运算,最终不仅造成巨大的运算时间的浪费 而且未必会产生很高的预测准确性。探索如何能够在不增加运算时间甚至是 减少运算时间而快速准确地得到高亲和力的突变位点的方法是非常有必要 和有意义的。 发明内容 本发明的目的是提供一种计算机辅助提高抗体亲和力的方法,该方法将 抗体进化规律与计算机模拟技术相结合, 增加了计算机模拟中真阳性的位 点, 显著提高了蛋白亲和力预测的准确率。
本发明首先对抗体亲和力成熟过程中的规律进行总结,建立了一种基于 抗体进化规律的计算机辅助设计方法, 以快速高效提高抗体的亲和力(准确 率大于 57% )。 为了证明本发明所述方法的通用性, 本发明用该方法进一步 进行融合蛋白受体的亲和力的提高试验, 获得相似的准确率。原则上, 本发 明的方法能够广泛应用于提高蛋白质复合物间的相互作用,加速研发具有生 物学和医学意义的蛋白质。同时,将抗体进化规律与计算机模拟技术相结合, 为以后进行计算机辅助设计提供了一种新的思路。
本发明的计算机辅助提高抗体亲和力的方法, 包括以下步驟:
一种通过计算机辅助获得高亲和力的抗体或蛋白分子的方法,包括以下 步驟:
1 )根据已知的抗体或蛋白分子复合物的共结晶结构确定候选的抗体或 蛋白分子的虚拟突变位点;
2 )依次将候选的虚拟突变位点上的氨基酸进行计算机模拟突变,获得 经过初步优化的分子结构;
3 )对获得的经过初步优化的分子结构, 采用计算机模拟的方法进行构 象搜索, 获得经过虚拟突变后的抗体或蛋白分子的模拟结构;
4 )将优化后的抗体或蛋白分子结构进行能量和均方根偏差分析,挑选 出总能量最低且均方根偏差数值较小的突变体构象进行与靶分子结合的结 合能分析, 同时获得其模拟结构;
5 )根据模拟结构,构建并表达预测能够提高抗体或蛋白分子亲和力的 突变体,分别进行与亲和力提高相关的实验脸证,获得具有高亲和力的抗体 或蛋白突变体。
其中步據 1 ) 中, 才艮据已知的抗体或蛋白的亲和力成熟过程中在晶体结 构上发生的变化的特点选取突变位点,并选取那些在蛋白质复合物接触面和 表面具有偏向性分布的氨基酸作为候选的突变氨基酸。选择的突变位点位于 抗体或蛋白分子与抗原或结合蛋白的接触面外围且不与抗原或结合蛋白形 成相互作用。
其中步骤 2 ) 中将所述虚拟突变位点突变为下述氨基酸:
Glu、 Arg、 Asn、 Ser、 Thr、 T r、 Lys、 Asp、 Pro和 /或 Ala。
其中步驟 4 ) 包括:
a )将步骤 3 ) 中获得的经过初步优化的抗体或蛋白分子, 按照总体 能量进行排序; b )根据抗体或蛋白分子复合物的晶体结构信息, 确定位于靶分子上 对结合起关键作用的氨基酸;;
c )对上述对结合起关键作用的氨基酸进行突变, 模拟优化后的结构 与晶体结构进行均方根偏差分析,选择那些总能量最低且均方根偏差数值相 对较小的突变体结构进行结合能的计算和分析并排序;
d )根据步驟 C)的排序结果, 获得高亲和力的抗体或蛋白分子的模拟 结构。 突变位点的选择
本发明中, 突变位点的选择主要是根据已知的关于抗体亲和力成熟过程 中在晶体结构上发生的变化的特点, 并选取那些偏向性分布在蛋白质复合 物接触面和表面的氨基酸;
选择突变的策略应首先满足以下方面: i )突变的位点最好位于 CDR区, 尽量避免可能产生的免疫原性; ii ) 突变的位点不要太多, 在有限的几个位 置上能够协同显著提高亲和力而又不过分的改变抗体的接触面; iii )最终的 方法必须高效, 准确率高, 能够通过有限的突变, 快速得到提高亲和力的抗 体。
本发明选取的突变位置具有以下两个特征: i ) 能够最大限度的保证单 点突变具有加大的可能的位置; ii ) 能够最大限度的保证组合突变具有最佳 的协同性, 极大地提高氨基酸抗体的亲和力。
Clark L A等人对 PDB数据库中的抗原抗体共结晶进行数理和统计上的 分析,通过信息挖掘技术得到了普遍分布于抗体接触面上的氨基酸组成的偏 向性 [见图 2, Clark LA, Ganesan S, Papp S, et al. Trends in antibody sequence changes during the somatic hypermutation process. [J]. J Immunol. 2006, 177(1): 333-340; Lo C L, Chothia C, Janin J. The atomic structure of protein-protein recognition sites.[J]. J Mol Biol. 1999, 285(5): 2177-2198]。 根据上述氨基酸分 布的偏向性 ,本发明选择那些具有较高概率出现在抗体接触面和表面的氨基 酸作为突变的选择氨基酸。在现有预测准确性的基础上,通过这种有目的性 的筛选,排除了那些很少出现在抗体接触面上的预测假阳性的氨基酸,从而 使得提高预测的准确性成为可能。
根据 Reichmann等人的研究,蛋白质接触面是呈簇分布的,位于簇中的 氨基酸突变往往不能形成很好的协同效应,而位于不同簇中的氨基酸突变能 够保证最大限度的氨基酸间的协同性。 同时, 由于抗体在经过亲和力成熟的 过程中,接触面的中心地带往往是对亲和力起较大贡献,也是进化较为完全 的地方;而对于接触面的四周,由于体内亲和力成熟的局限性,抗原的内吞, 导致抗体的亲和力不高, 且这些地方往往进化的不够完全。 因此, 本发明选 取位于抗原抗体接触面的四周的位置作为突变位点,且最好是没有和抗原发 生相互作用的氨基酸位点。
因此,本发明选择的抗体突变位点具有以下特征: ( 1 )选择的突变位点: 位于抗体接触面外围且最好没有与抗原物质形成相互作用;(2 )选择的突变 義基酸选自 Glu、 Arg、 Asn、 Ser、 Thr、 Tyr、 Lys、 Asp, Pro和 Ala。 计算机模拟突变的方法
通过 PDB数据库( PDB; Berman, Westbrook et al. (2000), Nucleic Acids Res. 28, 235-242; http://www.pdb.org/ ) 中得到的 PDB文件导入 Insightll
( accelrys公司 ),采用 CVFF ( Consistent Valence Force Field )力场 [Pnina D O. Structure and energetics of ligand binding to proteins: Escherichia coli dihydrofolate reductase-trimethoprim, a drug-receptor system[J]. Proteins:
Structure, Function, and Genetics. 1988, 4(1): 31-47], 通过 Biopolymer
( InsigMI软件包中的模块)模块加氢, 固定蛋白质所有的重原子对所加的 氢键进行 5000步的能量最小化(步长为 lfs )。 得到能量最小化优化后的结 构,设定距离抗原 6A的距离为接触面。在接触面周围 25A的距离加入水分 子。 将选取的突变位置进行氨基酸的突变, 对突变位点 6A距离的氨基酸分 子进行 auto—rotamer选取空间上的最优 起始位点 [Dunbrack R L. Rotamer Libraries in the 21st Century [J]. Current Opinion in Structural Biology. 2002, 12(4): 431-440. Ponder J W, Richards F M. Tertiary templates for proteins: Use of packing criteria in the enumeration of allowed sequences for different structural classes[J]. Journal of Molecular Biology. 1987, 193(4): 775-791.]。 将 蛋白质复合物外周的水分子和除蛋白盾复合物接触界面外的抗体分子进行 固定(constraint ), 进行模拟退火来寻找最有可能的接触模式。
首先采用 Quartic VDW (van der waals) with coulombic interactions off 的 方法进行初次筛选寻找可能的结合构象,降低此过程中范德华力和氢键的常 数为 0.5,每次进行 6000步的寻找, 最终产生 60个经过初步优化后的构象。 然后对初次生成的 60个构象分别采用 cell— mutipole的方法进行更加精细的 寻找 [Ding H Q, Karasawa N, Goddard 11. Atomic level simulations on a million particles: The cell multipole method for Coulomb and London nonbond interactions^]. J. Chem. Phys. 1992, 97(6): 4309-4315], 此时将范德华和库伦 力的选项的常数设置为 0.5, 从 500K到 280K进行 50个阶段, 每个阶段进 行 100fs, 最终产生的结构在进行 6000步的能量最小化 [Senderowitz H, Guarnieri F, Still W C. A Smart Monte Carlo Technique for Free Energy Simulations of M lticonformational Molecules. Direct Calculations of the
Conformational Populations of Organic Molecules [J], J. Am. Chem. Soc. 1995, 117(31): 8211-8219.]。将生成的结构进行结合能、总体能量和 root mean square deviation ( RMSD )的打分,将总能量最低且 RMSD值相对较小的构象挑出。
将选择出的复合物导入 charmm V34bl ( Bernard, R. B. and E. B. Robert, et al. (1983). "CHARMM: A program for macromolecular energy, minimization, and dynamics calculations." J Comput Chem. 4(2): 187-217. ), 使用 HBUILD 命令在 PDB结构的重原子上加氢, 采用 charmm力场( Becker, O. M. and M. Karplus (2005). Guide to Biomolecular Simulations (Focus on Structural
Biology) for charmm, Springer. )。 采用 Generalized Born with a simple
Switching ( GBSW ) [Im, W., Lee, M. S. & Brooks, C. L. Generalized born model with a simple smoothing function. J. Comput. Chem. 24, 1691-1702 (2003)] 隐 性水模型对整个体系进行能量最小化, 将达到平衡后的复合物采用
MM-PBSA的方法进行相对结合能的评价 [Kuhn, B., Gerber, P., Schulz-Gasch, T. & Stahl, M. Validation and use of the MM-PBSA approach for drug discovery. J. Med. Chem. 48, 4040-4048 (2005). Alonso, H., Bliznyuk, A. A. & Gready, J. E. Combining docking and molecular dynamic simulations in drug design. Med. Res. Rev. 26, 531-568 (2006).]。
结合自由能通过如下的公式进行评价:
AGbind = <Emm> + AGsolv -TAS ( Fogolari, F. and A.
Brigo, et al. (2003). "Protocol for MM/PBSA molecular dynamics simulations of proteins." Biophys J 85(1): 159-66. )
其中 Emm是采用 CVFF力场计算得来的分子力学能量, AGsolv是溶剂 化自由能, -TAS是溶质的熵。
<Emm > = <AEvdW> + <AEelec> + <AEint>
其中分子力学能量由分子内能、 范德华力和静电相互作用三部分组成。 由于每个抗体在其结合与非结合抗原的时候结构并未变化,因此分子力学能 量的内能部分对结合自由能的贡献为零。
AGsolv= AGPB +AGnp
AGPB表示静电溶剂化能, AGnp表示非极性溶剂化能;
由于仅仅是在原有抗体上进行点突变, 4艮小的改动, 因此 -TAS的变化 可以忽略不计; Kollman等人曾经对亲和力成熟抗体和其胚系抗体( germline antibody )进行动力学模拟和结合能的分析得出 AGnp和 -TAS在亲和力成熟 过程中其变化很小, 对结合能的贡献不大 [Chong L T, Duan Y5 Wang L, et al. Molecular dynamics and free-energy calculations applied to affinity maturation in antibody 48G7.[J]. Proc Natl Acad Sci U S A. 1999, 96(25): 14330-14335·]。 △GPB通常对蛋白质的结合起负作用,但是通过蛋白质之间的静电相互作用 的补偿, 使得蛋白质之间能够形成比较稳定的结合 [Novotny J, Sharp K.
Electrostatic fields in antibodies and antibody/antigen complexes. [J]. Prog
Biophys Mol Biol. 1992, 58(3): 203-224. Novotny J, Bruccoleri R E, Davis M, et al. Empirical free energy calculations: a blind test and further improvements to the method.[J]. J Mol Biol. 1997, 268(2): 401-411.]„ 因此, 在这里我们对评价 结合能的公式进行筒化, 仅仅计算分子力学对结合能的贡献。 对突变后的结构采用计算机模拟的方法进行构象搜索
首先 ,可采用 Quartic VDW (van der waals) with coulombic interactions off 方法对突变后的结构进行初次优化,生成满足条件的一定数量的初步优化后 的结构。
由于蛋白质分子分子数多, 自由度大,蛋白质分子的构象搜索仍然是结 构模拟的一个瓶颈。在初始构象的搜索中, 本发明首先采用筒单的刚性球体 模型来评价范德华力 (van der waals), 且不计算分子间的库伦力的影响。 进 而使得能量介面变得更加平滑, 能够相对容易地挑出局部能量最小值。
Quartic VDW (van der waals) with coulombic interactions off方法通常用来进 行初始的构象空间搜索。然后,可采用 cell_mutipole方法对生成的初始结构 进一步优化,进行最终精细的构象搜索,获得能量优化后的抗体或蛋白分子。
对于生物大分子来说,直接采用无限远的 cutoff的方法进行模拟需要耗 费大量的时间, 即使是最快的计算机现今也是不可行的。 Cell—mutipole (单 元多偶极法)是一种快速高效的方法, 具有与计算体系分子数呈线性关系的 计算规模和适度的内存需求量,专门发展来用于大分子的模拟。 [Ding, H. Q. and N. Karasawa, et al. (1992). "Atomic level simulations on a million particles: The cell multipole method for Coulomb and London nonbond interactions." J. Chem. Phys. 97(6): 4309-4315.] 对优化结构进行综合评价
将优化好的结构进行能量打分、 均方根偏差(RMSD )等指标的综 合评价, 获得预测的具有亲和力提高的抗体的突变点, 具体步骤包括: 首先 将上述经过能量优化后的抗体或蛋白分子,按照总体能量进行打分,从高到 低进行排序; 然后根据蛋白质复合物的晶体结构信息,确定位于靶分子上对 结合起关键作用的氨基酸;对这些对结合起关键作用的氨基酸进行突变模拟 后与晶体结构进行 RMSD分析 (重原子), 选择那些总能量最低且 RMSD 数值相对较小的突变体结构进行结合能的计算和分析;最终获得能够提高抗 体或蛋白分子亲和力的模拟结构。
构建并表达预测的能够提高抗体或蛋白分子亲和力的突变体,分别进行 与亲和力提高相关的实验验证, 获得能够提高抗体或蛋白亲和力的突变体。
本发明通过总结和尝试最终将从抗体亲和力成熟过程的规律与传统的 计算机模拟技术结合,开发了一种提高抗体或蛋白分子亲和力的方法。本发 明的方法显著性提高了计算机模拟预测提高蛋白亲和力的准确率,大大减少 了运算工作量, 降低了提高抗体亲和力所用的实验室成本,使得蛋白亲和力 的改变工作变得简单高效。 附图说明
图 1: 显示本发明方法的实验流程图;
图 2: 显示氨基酸分布的偏向性分析;
图 3: 显示实验验证能够提高 Trastuzumab亲和力的突变位点; 如图所 示, 为重链 55位 Asn, 重链 102位 Asp, 轻链 28位 Asp和轻链 93位 Thr。
图 4: 显示 Trastuzumab重链可变区 (VH )和轻链可变区 ( VL ) 的核 苷酸序列和氨基酸序列;
图 5: 显示实验验证能够提高 Rituximab亲和力的突变位点; 如图所示, 为 H57Asp和 H102Tyr;
图 6: 显示 Rituximab重链可变区 (VH )和轻链可变区 (VL ) 的核苷
^^列和氨基 列;
图 7: 显示在相同样品浓度下 biacore检测 Rituximab及 ituximab突变 体的 sensorgram图;
图 8: 显示 CTLA-4膜外区核苷酸序列和氨基酸序列;
图 9: 显示在相同样品浓度下 biacore检测 Abatacept及 CTLA-4/Ig突变体 的 sensorgram图。 具体实施方式
以下实施方式伴细描述了对成熟抗体 ( Trastuzumab和 Rituximab )和融 合蛋白受体(CTLA4-Ig )进行亲和力提高的试验方法, 通过这些实施方式 可以进一步理解本发明的特点和优点。
提高 Trastuzumab抗体亲和力的试验描述
曲妥珠单抗(Trastuzumab, Herceptin )是由美国 Genentech公司开发 的靶向 HER2 的人源化单克隆抗体, 对 HER2受体有高度亲和力, 用于治 疗 HER2/neu过表达的转移性乳腺癌。 本发明通过计算机进行体外模拟亲和力提高的过程,克服体内亲和力成 熟过程的限制, 进而得到表位相同但具有超高亲和力的 Trastuzumab。 通过 体内外的实验反复验证, 最终得到具有更强抗肿瘤活性的新型的 Tratuzumabo
计算机模拟预测 Trastuzumab亲和力的提高
为了评价计算机模拟的预测准确率, 首先选择 Trastuzumab的结合区域 所有的氨基酸位 进行虚拟突变, 依次分别突变成其他 19种氨基酸。 将 Trastuzumab与 Her2的共结晶 PDB文件 ( 1N8Z )导入 Insightll ( accelrys 公司), 载入 CVFF力场, 通过 Biopolymer加氢, 固定蛋白质所有的重原子 对所加的氢键进行能量最小化: 首先进行 Steepest descent method进行能量 最小化, 直到 maximum derivative小于 1000 kcal/mol/A,再采用 conjugate gradient method进行能量最小化, 总共进行 10000步(步长为 lfs ), 最终使 得收敛值 ( convergence )达到 0.01。 得到优化后的结构, 设定距离抗原 6A 的距离为接触面。 在接触面周围 25A的距离加入水分子。 将选取的突变位 置进行氨基酸的突变, 然后基于 Ponder和 Richards总结的的旋转异构体文 库, 对突变位点 6A距离的氨基酸分子进行 auto— rotamer选取空间上的最优 化起始位点。将外周的水分子和除接触界面外的抗体分子进行固定,进行模 拟退火来寻找最有可能的接触模式。
在选取最优结构上我们采用两步法进行寻找可能的构象: 首先采用 quartic_vdw— no— Coulomb的方法进行初次筛选寻找可能的结合构象,降低此 过程中范德华力的影响因子为 0.5, 每次进行 3000步的寻找, 最终产生 60 个想要的结果。 然后对初次生成的 60个结构采用 cell—mutipole的方法进行 进行 4000步( 1个步长 =lfs )能量最小化, 此时将范德华和库伦力的选项的 影响因子设置为 0.5 , 然后温度从 500K到 280K进行 50个阶段, 每个阶段 进行 100fs, 最终产生的结构在进行 8000步的能量最小化。将生成的结构进 行结合能、 总体能量和 RMSD的打分, 将最有可能的结构挑选出来, 进行 不同突变体间结合能的评价。如表 1所示,计算机预测方法的准确率近几年 达到 18.2%。
Trastuzumab亲和力提高的设计策略
首先, 对 Trastuzumab和 Her2抗原上的接触面进行分析: Trastuzumab 与 Her2抗原的接触溶剂化表面为 675A,具有较大的接触面。对接触面外周 的氨基酸依次进行虚拟突变。采用上述相同的计算机模拟步骤, 最终才艮据预 测, 选取预测提高最高的 10个点进行实验验证。
实施例 1 人抗体轻、 重链恒定区基因的克隆
用淋巴细胞分离液(鼎国生物技术发展公司产品)分离健康人淋巴细胞, 用 Trizol试剂( Invitrogen公司产品)提取总 RNA,才艮据文献( Cloned human and mouse kappa immunoglobulin constant and J region genes conserve homology in functional segments. Hieter PA, Max EE, Seidman JG, Maizel JV Jr, Leder R Cell. 1980 Nov;22(l Pt 1): 197-207 )和文献( The nucleotide sequence of a human immunoglobulin C gamma 1 gene. Ellison JW, Berson BJ, Hood LE. Nucleic Acids Res. 1982 Jul 10;10(13):4071-9 )报道的序列分别设计引物: HC sense: GCTAG CACCA AGGGC CCATC GGTCT TCC; HC antisense: TTTAC CGGGA GACAG GGAGA GGCTC TTC; Lc sense: ACTGT GGCTG CACCA TCTGT CTTCA TCT; Lc antisense: ACACT CTCCC CTGTT GAAGC TCTTT GTG。采用 RT-PCR反应扩增抗体重链和轻链恒定区基因。 PCR产物经琼脂 糖凝胶电泳純化回收并克隆到 pGEM-T载体(Promega公司)中, 测序验证 后确认获得了正确的克隆。 SEQ ID ΝΟ:1显示重链恒定区 (CH ) 的核苷酸 序列, SEQ ID NO:2显示重链恒定区 (CH ) 的氨基 列, SEQ ID NO: 3 和 SEQ ID NO: 4分别显示了轻链恒定区( CL )的核苷酸序列和氨基酸序列。 本实施例中的正确克隆记作 pGEM-T/CH和 pGEM-T/CL。
实施例 2抗 Her2人源化抗体 Trastuzumab的表达载体构建
参照 1992年发表在 PNAS上的抗人 Her2单抗资料及序列 ( Carter, P. and L. Presta, et al. (1992). Humanization of an anti-pl85HER2 antibody for human cancer therapy. Proc Natl Acad Sci U S A 89(10): 4285-9 ), 合成抗人 Her2单克隆抗体 Trastuzumab重链可变区基因 ( Her2VH )及轻链可变区 基因 (Her2VL ), 如图 4所示。
以 Her2VH基因和 pGEM-T/CH载体为模板通过重叠 PCR合成人源化 抗体重链基因, 反应条件为: 95TM5分钟; 94°C 50秒, 58°C50秒, 72°C 50秒, 30个循环; 72°C 10分钟。 并使此人源化重链基因的 5'端含有限制酶 位点 Hind III和信号肽基因序列, 3 '端含有翻译终止密码 TAA和限制酶位 点 EcoR I。信号肽基因序列为: ATG GAT TTT CAG GTG CAG ATT TTC AGC TTC CTG CTAATC AGT GCC TCA GTC ATAATA TCC AGA GGA。 最后琼 脂糖凝胶电泳分离 PCR扩增产物,回收目的条带并克隆到 pGEMT载体中, 筛选阳性克隆测序。 挑选测序正确的克隆用 ffindlll和 EcoR I酶切, 经琼脂 糖凝胶电泳纯化回收人源化抗体重链片段 Her2VHCH,与用 Hind III和 EcoR I酶切的盾粒 pcDNA3.1 ( + ) (美国 Invitrogen公司产品)进行连接, 构建成 人源化重链真核表达载体 pcDNA3.1 ( + ) ( Her2VHCH )。
以 Her2VL基因和 pGEM-T/CL载体为模板通过重叠 PCR合成人源化抗 体轻链基因, 反应条件为: 95°C 15分钟; 94°C 50秒, 58°C50秒, 72°C 50 秒, 30个循环; 72°C 10分钟, 得到 PCR产物 Her2VLCL, 其 5'端含有限制 酶位点 Hindlll和信号肽基因序列, 3 '端含有翻译终止密码 TAA和限制酶位 点 EcoR I。信号肽基因序列为: ATG GAT TTT CAG GTG CAG ATT TTC AGC 序正确的克隆用 Hind III和 EcoR I酶切,经琼脂糖凝胶电泳纯化回收人源化 抗体轻链片段 C2B8VLCL, 与用 Hind III和 EcoR I酶切的质粒 pcDNA3.1 载体(美国 Invitrogen公司产品)进行连接, 构建成人源化轻链真核表达载 体 pcDNA3.1 ( Her2VLCL )。
实施例 3 嵌合抗体的稳定表达与纯化
于 3.5cm组织培养皿中接种 3x105 CHO-K1 细胞( ATCC CRL-9618 ), 细胞培养至 90%-95%融合时进行转染: 取质粒 lO g (质粒 pcDNA3.1(+) ( Her2VHCH ) 4 g , 质粒 pcDNA3.1 ( Her2VLCL ) 6μδ ) 和 20μ1 Lipofectamine2000 Reagent ( Invitrogen公司产品)分别溶于 500μ1 无血清 DMEM培养基, 室温静置 5分钟, 将以上 2种液体混合, 室温孵育 20分钟 以使 DNA-脂质体复合物形成, 其间用 3ml无血清的 DMEM培养基替换培 养^:中的含血清培养基,然后将形成的 DNA-脂质体复合物加入到板中, C02 孵箱培养 4小时后补加 2ml含 10%血清的 DMEM完全培养基, 置于 C02 孵箱中继续培养。转染进行 24h后细胞换含 60(^g/ml G418选择培养基筛选 抗性克隆。取细胞培养上清用 ELISA检测筛选高表达克隆: 羊抗人 IgG (Fc) 包被于 ELISA板, 4。C过夜, 用 2 % BSA-PBS于 37。C封闭 2h, 加入待测的 抗性克隆培养上清或标准品(Human myeloma IgGl , κ ), 37°C温育 2h, 加 入 HRP-羊抗人 IgG ( κ )进行结合反应, 37。C温育 lh, 加入 TMB于 37。C 作用 5min, 最后用 H2S04终止反应, 测 A450值。将筛选得到的高表达克隆 用无血清培养基扩大培养, 用 Protein A亲和柱( GE公司产品)分离纯化人 源化抗体 trastuzumab。 将纯化抗体用 PBS进行透析, 最后以紫外吸收法定 量确定纯化后抗体的浓度。
实施例 4 Trastuzumab抗体突变体的构建及表达
采用 overlapPCR的方式进行 Trastuzumab抗体突变体的构建,其构建与 表达、 纯化的方法与 Trastuzumab人源化抗体相同。构建的抗体突变体共 10 个, 分别为 Hmutl到 HmutlO, 具体氨基酸序列分别见 SEQ ID NO:5 ~ SEQ
Figure imgf000011_0001
实施例 5 Trastuzumab突变体的 ELISA鉴定
将 Her2膜外区蛋白按照 Carter的方法进行表达纯化, 然后包被 ELISA 板, 37度, 孵育 2小时; 然后将固定浓度的抗体与等比稀释好的 Her2膜外 区蛋白室温孵育 1小时。然后通过鉴定孵育抗体抗原复合物中游离的抗体的 量, 最终计算出亲和力的大小。 具体请参见 [Carter P, et al. (1992) Humanization of an anti-pl85HER2 antibody for human cancer therapy. Proc Natl Acad Sci USA 89: 4285-4289; Friguet B, Chaffotte AF, Djavadi-Ohaniance antigen-antibody complexes by enzyme-linked immunosorbent assay. J Immunol Methods 77:305-319]. 最终, 十个实险组中总共有六个点可以提高亲和力, 准确率达到了 60%。如图 3所示,其中显示了实验证明能够提高 Trastuzumab 亲和力的四个位点。
表 1: Trastuzumab抗体亲和力的预测和实验结果
位置 突变位置 Kd^/Kd1 mutant
d WT
0.16 ± 0.02 nM
L28Asp Pro 0.83 ± 0.12
L28Asp Met 0.32 ± 0.07
L30Asn Ser ND
L30Asn Arg 1.74 ± 0.17
L32Ala Gin ND
L94Thr Tyr 0.87 ± 0.05
H55Asn Lys 2.01 ± 0.19
H55Asn Pro 0.08 ± 0.01
H57Tyr lie 0.06 ± 0.01
HI 02 Asp Met 0.54 ± 0.15
H103Lys Arg 0.04 ± 0.01
实验误差用 SD表示, 其来源于三次独立的实验; WT, 为 Trastuzumab抗体; ND, 表示 由于亲和力太弱无法检测。
表 2: 竟争性 ELISA检测抗体突变体的亲和力
KdWT/Kdmuta KdHerc/Kdm 突变体名称 位置 突变为氨基酸 nt utant
KdWT = 0.16 ± 0.02 nM KdHerc : 0.21 ± 0.04 nM
Hmutl L28Asp Arg 1.86 ± 0.09 2.44 ± 0.12
Hmut2 L28Asp Pro 0.83 ± 0.12 1.09 ± 0.16
Hmut3 L93Thr Tyr 1.64 ± 0.18 2.15 ± 0.24
Hmut4 L93Thr Asn 0.21± 0.08 0.28 ± 0.11
Hmut5 H55Asn Pro 0.08 ± 0.01 0.11 ± 0.01
Hmut6 H55Asn Lys 2.01 ± 0.19 2.64士 0.25
Hmut7 H59Arg Lys 0.75士 0.02 0.98 ± 0.03
Hmut8 H102Asp Thr 2.16 ± 0.16 2.84 ± 0.21
Hmut9 H102Asp Tyr 3.11 ± 0.28 4.09 ± 0.37
Hmutl 0 H102Asp Lys 2.31 ± 0.20 3.03士 0.26 误差用 SD表示, 来源于独立重复三次实验结果。 WT为未突变的抗体序列; Here表示 为市售 Herceptin. 提高 Rituximab抗体亲和力试验的描迷
Rituximab是基因工程人鼠嵌合单克隆抗体, 由鼠 Fab和人 Fc构成, 分子量约 150kDa, 可特异性地与 B淋巴细胞表面的 CD20抗原结合, 最终 导致 B淋巴细胞死亡, 用于治疗非霍奇金氏淋巴瘤等。
Rituximab定点突变的试验方法
Rituximab抗体突变的策略
首先, 对 Rituximab上的接触面进行分析: 通常短肽与蛋白接触的溶剂 化可接触面积在 400-700A, 通常要比蛋白与蛋白接触的溶剂化可接触面积 要小, 而 ituximab与 CD20短肽接触的 SAS为 440A, 在短肽与蛋白相互 作用中的 SAS 已经算是比较小的。 选择在接触面外周氨基酸依次进行虚拟 突变。
将 Rituximab与 CD20抗原肽的共结晶 PDB文件导入 Insightl accelrys 公司), 载入 CVFF力场, 通过 Biopolymer加氢, 固定蛋白质所有的重原子 对所加的氢键进行 10000 步的能量最小化 (步长为 lfs ) , 最终使得 convergence达到 0.01。得到优化后的结构,设定距离抗原 6A的距离为接触 面。 在接触面周围 25A的距离加入水分子。 将选取的突变位置进行氨基酸 的突变, 然后基于 Ponder和 Richards总结的的旋转异构体文库, 对突变位 点 6A距离的氨基酸分子进行 auto_rotamer选取空间上的最优化起始位点。 将外周的水分子和除接触界面外的抗体分子进行固定,进行模拟退火来寻找 最有可能的接触模式。在选取最优结构上我们采用两步法进行寻找可能的构 象: 首先采用 quartic_vdw— no—coul的方法进行初次筛选寻找可能的结合构 象, 降低此过程中范德华^"的影响因子为 0.5, 每次进行 6000步的寻找, 最 终产生 60个想要的结果。 然后对初次生成的 60个结构采用 cell—mutipole 的方法进行进行 4000步( 1个步长 =lfs )能量最小化, 此时将范德华和库伦 力的选项的影响因子设置为 0.5,然后温度从 500K到 280K进行 50个阶段, 每个阶段进行 100fs, 最终产生的结构在进行 8000步的能量最小化。将上述 过程生成的结构进行 RMSD ( Root mean square deviation )分析, 比较生成 的结构复合物中抗原肽上与抗体结合紧密的氨基酸与突变前的氨基酸的构 象变化(heavy atom )。 最终, 我们选择那些总能量最低且 RMSD相对比较 低的结构挑选出来。
将挑选出来的结构导入 charmm,进行能量最小化。采用 MM-PBSA的方 法进行能量评价。 为了评价计算机预测方法的准确性,我们在三个候选位点 分别选取了预测能够提高亲和力的氨基酸和预测亲和力下降的氨基酸进行 试验验证。
Rituximab抗体的构建 实施例 6人抗体轻、 重链恒定区基因的克隆
用淋巴细胞分离液(鼎国生物技术发展公司产品)分离健康人淋巴细胞, 用 Trizol试剂 ( Invitrogen公司产品)提取总 R A, 根据文献 Cloned human and mouse kappa immunoglobulin constant and J region genes conserve homology in functional segments. Hieter PA, Max EE, Seidman JG, Maizel JV Jr, Leder P. Cell. 1980 Nov; 22(1 Pt 1): 197-207 )和文献( The nucleotide sequence of a human immunoglobulin C gamma 1 gene. Ellison JW5 Berson BJ, Hood LE. Nucleic Acids Res. 1982 Jul 10;10(13):4071-9 )报道的序列分别设计引物: HC sense: GCTAG CACCA AGGGC CCATC GGTCT TCC; HC antisense: TTTAC CGGGA GACAG GGAGA GGCTC TTC; Lc sense: ACTGT GGCTG CACCA TCTGT CTTCA TCT; Lc antisense: ACACT CTCCC CTGTT GAAGC TCTTT GTG。 采用 RT-PCR反应扩增抗体重链和轻链恒定区基因。 PCR产 物经琼脂糖凝胶电泳纯化回收并克隆到 pGEM-T载体中, 测序^ r证后确认 获得了正确的克隆。 SEQ ID ΝΟ:1和 SEQ ID NO:2分别显示了重链恒定区 ( CH ) 的核苷酸序列和氨基酸序列。 SEQ ID NO:3和 SEQ ID NO:4分别显 示了轻链恒定区 (CL ) 的核苷酸序列和氨基酸序列。 本例中的正确克隆记 作 pGEM-T/CH和 pGEM-T/CL。
实施例 7抗 CD20嵌合抗体 Rituximab的表达载体构建 合成抗人 CD20单克隆抗体 Rituximab ( C2B8 )重链可变区基因( C2B8VH ) 及轻链可变区基因(C2B8VL )。 图 6显示了 C2B8重链和轻链可变区的核苷 列和氨基 列。
以 C2B8VH基因和 pGEM-T/CH载体为模板通过重叠 PCR合成人源化 抗体重链基因, 反应条件为: 95°C 15分钟; 94°C 50秒, 58°C50秒, 72°C 50秒, 30个循环; 72°C 10分钟。 并使此人源化重链基因的 5'端含有限制酶 位点 Hindlll和信号肽基因序列, 3 '端含有翻译终止密码 TAA和限制酶位点 EcoR l。 信号肽基因序列为: ATG GGATTC AGC AGGATC TTT CTC TTC CTC CTG TCA GTAACT ACA GGT GTC CAC TCC。最后琼脂糖凝胶电泳分 离 PCR扩增产物, 回收目的条带并克隆到 pGEMT载体中, 筛选阳性克隆 测序。 挑选测序正确的克隆用 Hindlll和 EcoR l酶切, 经琼脂糖凝胶电泳纯 化回收人源化抗体重链片段 C2B8VHCH, 与用 Hindlll和 EcoR I酶切的质 粒 pcDNA3.1(+) (美国 Invitrogen公司产品)进行连接, 构建成人源化重链真 核表达载体 PcDNA3.1 (+) (C2B8VHCH)„
以 C2B8VL基因和 pGEM-T/CL载体为模板通过重叠 PCR合成人源化 抗体轻链基因,反应条件为: 95°C 15分钟; 94 °C 50秒, 58°C50秒, 72°C 50 秒, 30个循环; ,2。C 10分钟, 得到 PCR产物 C2B8VLCL, 其 5'端含有限 制酶位点 Hindlll和信号肽基因序列, 3 '端含有翻译终止密码 TAA和限制酶 位点 EcoR I。 信号肽基因序列为 ATG GAT TTT CAA GTG CAG ATT TTC 选测序正确的克隆用 Hindlll和 EcoR I酶切, 经琼脂糖凝胶电泳纯化回收人 源化抗体轻链片段 C2B8VLCL,与用 Hindlll和 EcoR I酶切的质粒 pcDNA3.1 载体 (美国 Invitrogen公司产品)进行连接, 构建成人源化轻链真核表达载体 pcDNA3.1 (C2B8VLCL)。
实施例 8 嵌合抗体的稳定表达与纯化
于 3.5cm组织培养亚中接种 3 x l05 CHO-Kl 细胞( ATCC CRL-9618 ), 细胞培养至 90%-95%融合时进行转染: 取质粒 10 g(质粒 pcDNA3.1(+)(C2B8VHCH)4 g, 质粒 pcDNA3.1(C2B8VLCL)6 g)和 20μ1 Lipofectamine 2000 Reagent ( Invitrogen公司产品)分别溶于 500μ1无血清 DMEM培养基, 室温静置 5分钟, 将以上 2种液体混合, 室温孵育 20分钟 以使 DNA-脂质体复合物形成, 其间用 3ml无血清的 DMEM培养基替换培 养 JUL中的含血清培养基,然后将形成的 DNA-脂^:体复合物加入到板中, C02 孵箱培养 4小时后补加 2ml含 10%血清的 DMEM完全培养基, 置于 C02 孵箱中继续培养。 转染进行 24h后细胞换含 60(^g/ml G418选择培养基筛 选抗性克隆。取细胞培养上清用 ELISA检测筛选高表达克隆:羊抗人 IgG (Fc) 包被于 ELISA板, 4。C过夜, 用 2 % BSA-PBS于 37。C封闭 2h, 加入待测的 抗性克隆培养上清或标准品 (Human myeloma IgGl,K) , 37。C 温育 2h, 加入 HRP -羊抗人 IgG(K)进行结合反应, 37°C温育 lh,加入 TMB于 37°C作用 5min, 最后用 H2S04终止反应, 测 A450值。 将筛选得到的高表达克隆用 无血清培养基扩大培养, 用 Protein A亲和柱(GE公司产品)分离纯化嵌合 抗体 C2B8。 将纯化抗体用 PBS进行透析, 最后以紫外吸收法定量确定纯化 后抗体的浓度。
实施例 9 C2B8抗体突变体的构建及表达
采用 overlapPCR的方式进行 C2B8抗体突变体的构建, 其构建与表达、 纯化的方法与 C2B8 嵌合抗体相同。 构建的抗体突变体共 10 个, 分别为 Rmutl到 Rmut7, 具体氨基酸序列分别见 SEQ ID NO: 25 ~ SEQ ID NO: 38。 实施例 10 Rituximab及突变体的 biacore鉴定
将 SA芯片在 50μ1/πώι的 PBS溶液中 25°C平衡 30min, 然后用 lM NaCl 50mM NaOH的活化液活化 3次, 每次 lmin; 将 biotin标记的抗原肽(其为 人 CD20 分子膜外区的部分片段, 其来源参见文献( Structural Basis for Recognition of CD20 by Therapeutic Antibody Rituximab. Du, J.; Wang, H.; Zhong, C. (..·)· J Biol Chem, 2007, 282(20): 15073-15080 )稀释成最终浓度为 ^g/ml, ΙΟμΙ/min的流速包被 ARu=1000; 然后用 PBS緩冲液 50μ1/ηιίη平衡 10min。 将平衡后的芯片用 0.04%的生物素溶液封闭芯片。 将抗体等两倍比 稀释五个浓度, 50μ1/πώι上样 75 sec, 然后用 PBS解离 10min。 图 7显示了 在相同样品浓度下 biacore检测的 sensorgram ¾; 具体检测亲和力数值见表 3。 最终, C2B8抗体突变体 Rmut3亲和力提高了 6.08倍, 突变体 Rmut7亲 和力提高了 3.96倍。 其预测准确率达到了 71.4%。如图 5所示, 其中显示出 亲和力提高的突变位点为重链 57位 Asp和重链 102位 Tyr。
表 3: biacore检测抗体突变体的亲和力
突变位置及突变为
名称 KdWT/Kdmutant KdRitu/Kdmutant
的氨基酸
K 4.1 ± 0.30 nM Kdritu=56.1 ± 0.40 nM
Rmutl H55NE 0.54±0.21 0.69±0.27
Rmut2 H55NR 0.61±0.18 0.78±0.23
Rmut3 H57DE 6.08±1.48 7.73±1.88
Rmut4 H102YR 1.75±0.25 2.23±0.32
Rmut5 H102YS 1.85±0.35 2.35±0.45
Rmut6 H102YT 1.84±0.24 2.34±0.31
Rmut7 H102YK 3.96±0.39 5.04±0.50
ND表示没有采用 biacore检测; WT表示未突变的 C2B8; ritu表示市售 rituximab。 提高 CTLA4-Ig融合受体亲和力试验的描述
细胞毒 T细胞抗原 4 (Cytotoxic T-Lymphocyte Antigen 4, CTLA-4)为同 源二聚体, 主要表达于活化 T细胞, 与 CD28具有高度同源性。
阿巴西普(Abatacept )是 CTLA-4膜外区与免疫球蛋白的融合蛋白, 通 过与 B7分子结合抑制 T细胞的激活, 进而作为一种特异性的共刺激因子调 节剂, 用于治疗抗 TNF-α治疗无效的类风湿性关节炎。 Belatacept同样也是 由施贵宝公司开发,其与阿巴西普仅仅只有两个氨基酸的改变,但是显著提 高与配体(CD80、 CD86 ) 的亲和力。
CTLA4/Ig定点突变的试 ¾r方法
将 CTLA4/Ig与 CD86的共结晶 PDB文件( li85 )导入 Insightl accelrys 公司), 载入 CVFF力场, 通过 Biopol mer加氢, 固定蛋白质所有的重原子 对所加的氢键进行能量最小化: 首先进行 Steepest descent method进行能量 最小化 , 直到 maximum derivative小于 1000 kcal/mol/A,再采用 conjugate gradient method进行能量最小化, 总共进行 10000步(步长为 lfs ), 最终使 得 convergence达到 0.01。 得到优化后的结构, 设定距离抗原 6A的距离为 接触面。 在接触面周围 25A的距离加入水分子。 将选取的突变位置进行氨 基酸的突变, 然后基于 Ponder和 Richards总结的的旋转异构体文库, 对突 变位点 6A距离的氨基酸分子进行 auto— rotamer选取空间上的最优化起始位 点。将外周的水分子和除接触界面外的抗体分子进行固定,进行模拟退火来 寻找最有可能的接触模式。在选取最优结构上我们采用两步法进行寻找可能 的构象: 首先采用 quartic_vdw— no— Coulomb的方法进行初次筛选寻找可能 的结合构象, 降低此过程 范德华力的影响因子为 0.5,每次进行 3000步的 寻找, 最终产生 60 个想要的结果。 然后对初次生成的 60 个结构采用 cell— mutipole的方法进行进行 4000步( 1个步长 =lfs )能量最小化, 此时将 范德华和库伦力的选项的影响因子设置为 0.5,然后温度从 500K到 280K进 行 50个阶段, 每个阶段进行 100fs, 最终产生的结构在进行 8000步的能量 最小化。 将生成的结构进行结合能、 总体能量和 RMSD的打分, 将最有可 能的结构挑选出来,进行不同突变体间结合能的评价。为了评价计算机预测 方法的准确性,我们在三个候选位点分别选取了预测能够提高亲和力的氨基 酸进行试验验证。
CTLA4/Ig突变体的构建和功能检测
实施例 11 CTLA-4膜外区基因和 Fc区基因的克隆
用淋巴细胞分离液分离健康人淋巴细胞, 用 Trizol试剂(Invitrogen公司 产品)提取总 RNA,设计引物扩增 CTLA-4膜外区基因 (GenelD: 1493), 并用 引物 FC有义: GCCCAGATTCTGATCAGGAGCCCAAATCTTCTGAC和 FC反义: GAATTCTCATTTACCCGGAGACAGG扩增抗体 Fc区。 PCR反 应均采用热启动, 反应条件: 94°C 15分; 94°C45秒; 60°C 45秒; 72°C 1 分 10秒; 30个循环; 72°C 10分钟。 PCR产物经琼脂糖凝胶电泳纯化回收 并克隆到 pGEM-T(promega)载体中,测序验证后确认获得了正确的克隆。 图 8显示了 CTLA-4的核苷酸和氨基酸序列。 SEQ ID NO:39和 SEQ ID NO:40 分别显示了 Fc 区的核苷酸序列和氨基酸序列。 本例中的正确克隆记作 pGEM-T/CT和 pGEM-T/Fc。
实施例 12 CTLA-4/Ig融合蛋白的表达载体构建
设计引物将合成的信号肽序列 SEQ ID NO:41与克隆出来的 CTLA-4膜 外基因片段进行 overlapPCR, 将连接测序正确的片段与抗体 Fc 进行 overlapPCR, 装 pGEM-T载体进行测序。 4兆选测序正确的克隆用 Hindlll和 EcoR l酶切 CTLA-4/Ig融合受体蛋白基因, 经琼脂糖凝胶电泳纯化回收, 与用 Hindlll和 EcoR I酶切的质 pcDNA3.1(+) (美国 Invitrogen公司产品)进行 连接, 构建成人源化重链真核表达载体 pcDNA3.1 (+) , 记作 pcDNA3.1 (+) (CTLA-4/Ig)。
实施例 13 融合受体的稳定表达与纯化
于 3.5cm组织培养亚中接种 3 105 CHO-K1 细胞( ATCC CRL-9618 ), 细胞培养至 90%-95%融合时进行转染: 取质粒 10μβ(质粒 pcDNA3.1 (+) (CTLA-4/Ig) 和 20μ1 Lipofectamine2000 Reagent ( Invitrogen 公司产品)分别溶于 500μ1无血清 DMEM培养基, 室温静置 5分钟, 将以 上 2种液体混合, 室温孵育 20分钟以使 DNA-脂质体复合物形成, 其间用 3ml无血清的 DMEM培养基替换培养亚中的含血清培养基, 然后将形成的 DNA-脂质体复合物加入到板中, C02孵箱培养 4小时后补加 2ml含 10%血 清的 DMEM完全培养基, 置于 C02孵箱中继续培养。 转染进行 24h后细 胞换含 60(^g/ml G418选择培养基筛选抗性克隆。取细胞培养上清用 ELISA 检测筛选高表达克隆: 羊抗人 IgG (Fc)包被于 ELISA板, 4。C过夜, 用 2% BSA-PBS 于 37。C 封闭 2h , 加入待测的抗性克隆培养上清或标准品 (Abatacept), 37°C温育 2h,加入 HRP -羊抗人 Fc(CH2)进行结合反应, 37°C 温育 lh, 加入 TMB于 37。C作用 5min, 最后用 ¾S04终止反应, 测 A450 值。 将筛选得到的高表达克隆用无血清培养基扩大培养, 用 Protein A亲和 柱( GE公司产品)分离纯化嵌合抗体 C2B8。 将纯化抗体用 PBS进行透析, 最后以紫外吸收法定量。
实施例 14 融合受体突变体的构建及表达
采用 overlapPCR的方式对 CTLA-4/Ig突变体进行构建, 其构建(如图 8所示)与表达、 纯化的方法与 CTLA-4/Ig融合蛋白相同。 突变体氨基酸序 列见 SEQ ID NO:42 ~ SEQ ID NO:50。
实施例 15 Abatacept. CTLA-4/Ig突变体的 biacore鉴定
将 CM5芯片在 50μ1/ιηίη的磷酸盐缓冲液( PBS )溶液中 25°C平衡 30min, 然后用 ΙΟΟμΙ的 Ν-羟基琥珀酰亚胺 (NHS)和 ΙΟΟμΙ 1-乙基 -3-(3-二甲基氨丙 基) -碳化二亚胺 (EDC)混合, 以 ΙΟμΙ/ml 活化芯片 8min。 然后将终浓度为 5 g/ml 的 CD86-FC ( R&D公司)蛋白以 ΙΟμΙ/ml 的流速包被芯片, 最终 △Ru=100 Ru。 然后用 PBS緩冲液 50μ1/πΰη平衡 10min。 将待检测样品以等 两倍比稀释五个浓度, 50μ1/ηώι上样 75 sec, 然后用 PBS解离 10min。 图 9 显示了在相同样品浓度下 biacore检测的 sensorgmm图; 具体检测亲和力数 值见表 4。 其中, 我们构建的 CTLA-4/Ig的亲和力与 Abatacept的亲和力相 似; 提高亲和力程度较高的单点突变体为: 突变体 CTmutl和 CTmut2,亲和 力分别提高了 4.04和 3.98倍; 突变体 CTmut6, 亲和力提高了 2.29倍; 突 变体 CTmutlO, 亲和力提高了 2.68倍。 最终, 预测准确率达到了 70%。 表 4:
突变体名称 位置 突变为氨基酸
Figure imgf000019_0001
Κ/τ=44.1士 0.30 nM Kdritu=56.1 ± 0.40 nM
CTmutl D31Ala Tyr 3.98 ± 0.19 4.24 ± 0.20
CTmut2 D31Ala Lys 4.04 ± 0.90 4.31 ± 0.96
CTmut3 D53Thr Lys 0.55 ± 0.14 0.58 ± 0.15
CTmut4 D55Met Glu 1.75 ± 0.07 1.87 ± 0.08
CTmut5 D63Leu Lys 1.85 ± 0.16 1.97 ± 0.17
CTmut6 D63Leu Tyr 2.29 ± 0.31 2.44 ± 0.33
CTmut7 D35Arg Pro 0.55 ± 0.14 0.58 ± 0.15
CTmut8 D106Leu Glu 2.00 ± 0.39 2.13 ± 0.42
CTmut9 D106Leu Asn 0.88 ± 0.06 0.94 ± 0.06
CTmutl 0 D106Leu Ser 2.68 ± 1.14 2.86 ± 1.22 实验误差采用 SD表示, 通过三次不同的实验确定。 WT, 表示未突变的原本融合受体; abat,表示市售 Abatacept; 工业应用性
本发明的方法能够广泛应用于提高蛋白质复合物间的亲和力,加速研发 具有生物学和医学意义的高亲和力蛋白质分子。 同时,将抗体进化规律与计 算机模拟技术相结合, 为以后进行计算机辅助设计提供了一种新的思路。

Claims

权利要求书
1、 一种通过计算机辅助获得高亲和力的抗体或蛋白分子的方法, 包括 以下步骤:
1 据已知的抗体或蛋白分子复合物的共结晶结构确定候选的抗体或 蛋白分子的虚拟突变位点;
2 )依次将候选的虚拟突变位点上的氨基酸进行计算机模拟突变,获得 经过初步优化的分子结构;
3 )对获得的经过初步优化的分子结构,采用计算机模拟的方法进行构 象搜索 , 获得经过虚拟突变后的抗体或蛋白分子的模拟结构;
4 )将优化后的抗体或蛋白分子结构进行能量和均方根偏差分析,挑选 出总能量最低且均方根偏差数值较小的突变体构象进行与靶分子结合的结 合能分析, 同时获得其模拟结构;
5 )根据模拟结构,构建并表达预测能够提高抗体或蛋白分子亲和力的 突变体,分别进行与亲和力提高相关的实验验证,获得具有高亲和力的抗体 或蛋白突变体。
2、 权利要求 1所述的方法, 其中步骤 1 ) 中, 根据已知的抗体或蛋白 的亲和力成熟过程中在晶体结构上发生的变化的特点选取虚拟突变位点,并 选取那些在蛋白质复合物接触面和表面具有偏向性分布的氨基酸作为候选 的突变氨基酸。
3、 权利要求 2所述的方法, 其中根据抗体或蛋白分子复合物的晶体结 构进行步驟 1 )所述的突变位点选取, 选择的突变位点位于抗体或蛋白分子 与抗原或结合蛋白的接触面外围且不与抗原或结合蛋白形成相互作用。
4、 权利要求 2所述的方法, 其中步骤 2 ) 中将所述虚拟突变位点突变 为下述氨基酸:
Glu、 Arg、 Asn、 Ser、 Thr、 Tyr、 Lys、 Asp, Pro和 /或 Ala。
5、 权利要求 1所述的方法, 其中步骤 4 ) 包括:
a )将步骤 3 ) 中获得的经过初步优化的抗体或蛋白分子, 按照总体 能量进行排序;
b )根据抗体或蛋白分子复合物的晶体结构信息, 确定位于靶分子上 对结合起关键作用的氨基酸;;
c )对上述对结合起关键作用的氨基酸进行突变, 模拟优化后的结构 与晶体结构进行均方根偏差分析,选择那些总能量最低且均方根偏差数值相 对较小的突变体结构进行结合能的计算和分析并排序;
d )根据步骤 C)的排序结果, 获得高亲和力的抗体或蛋白分子的模拟 结构。
PCT/CN2009/001079 2009-09-25 2009-09-25 通过计算机辅助设计来获得高亲和力的蛋白质的方法 WO2011035456A1 (zh)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013153059A1 (en) 2012-04-11 2013-10-17 Politecnico Di Milano Co-crystals of 3-iodopropynyl butylcarbamate
CN116486906A (zh) * 2023-04-17 2023-07-25 深圳新锐基因科技有限公司 基于氨基酸残基突变提高蛋白质分子稳定性的方法及装置

Families Citing this family (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
SG11201507416WA (en) * 2013-03-15 2015-10-29 Amgen Inc Human pac1 antibodies
DK3736292T3 (da) 2013-12-17 2024-07-22 Genentech Inc Anti-CD3-antistoffer og fremgangsmåder til anvendelse
CA2925677A1 (en) * 2013-12-20 2015-06-25 F. Hoffmann-La Roche Ag Bispecific her2 antibodies and methods of use
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CN115975028B (zh) * 2022-11-02 2023-08-29 厦门康基生物科技有限公司 一种孕酮抗体、制备方法及其应用

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6399061B1 (en) 1992-11-13 2002-06-04 Idec Pharmaceutical Corporation Chimeric and radiolabelled antibodies specific to human CD20 antigen and use thereof for treatment of B-cell lymphoma
CN101228270A (zh) * 2005-07-21 2008-07-23 拜耳先灵医药股份有限公司 人可溶性腺苷酸环化酶的晶体结构
CN101496014A (zh) * 2006-06-06 2009-07-29 医疗研究局 流感病毒神经氨酸酶晶体结构和其用途
CN101501692A (zh) * 2006-08-10 2009-08-05 医疗研究局 P53突变体的晶体结构及它们的用途

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CA2264968A1 (en) * 1996-09-02 1998-03-12 Sumitomo Electric Industries, Ltd. Humanized immunoglobulin reacting specifically with fas ligand or active fragments thereof and region inducing apoptosis originating in fas ligand
JP2000319298A (ja) * 1999-03-04 2000-11-21 Seibutsu Bunshi Kogaku Kenkyusho:Kk 蛋白質複合体の結晶、構造座標、及び構造座標の使用
WO2003066849A2 (en) * 2002-02-04 2003-08-14 Affinium Pharmaceuticals, Inc. Novel purified polypeptides from staphylococcus aureus
US20040110226A1 (en) * 2002-03-01 2004-06-10 Xencor Antibody optimization
JP2005245202A (ja) * 2004-03-01 2005-09-15 Japan Science & Technology Agency ヒトTFIIEαの新規な亜鉛結合ドメインの構造的特徴および機能
EP1723964A1 (en) * 2005-05-20 2006-11-22 Institut Pasteur Use of penicillin-binding proteins or polynucleotides or antibodies thereof for preventing or treating bacterial infections

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6399061B1 (en) 1992-11-13 2002-06-04 Idec Pharmaceutical Corporation Chimeric and radiolabelled antibodies specific to human CD20 antigen and use thereof for treatment of B-cell lymphoma
CN101228270A (zh) * 2005-07-21 2008-07-23 拜耳先灵医药股份有限公司 人可溶性腺苷酸环化酶的晶体结构
CN101496014A (zh) * 2006-06-06 2009-07-29 医疗研究局 流感病毒神经氨酸酶晶体结构和其用途
CN101501692A (zh) * 2006-08-10 2009-08-05 医疗研究局 P53突变体的晶体结构及它们的用途

Non-Patent Citations (27)

* Cited by examiner, † Cited by third party
Title
ALONSO, H.; BLIZNYUK, A. A.; GREADY, J. E.: "Combining docking and molecular dynamic simulations in drug design", MED. RES. REV, vol. 26, 2006, pages 531 - 568, XP055159792, DOI: doi:10.1002/med.20067
BECKER, O. M.; M. KARPLUS: "Guide to Biomolecular Simulations (Focus on Structural Biology) for charmm", 2005, SPRINGER
BERMAN; WESTBROOK ET AL., NUCLEIC ACIDS RES., vol. 28, 2000, pages 235 - 242
BERNARD, R. B.; E. B. ROBERT ET AL.: "CHARMM.- A program for macromolecular energy, minimization, and dynamics calculations.", J COMPUT CHEM., vol. 4, no. 2, 1983, pages 187 - 217, XP008008192, DOI: doi:10.1002/jcc.540040211
CARTER P ET AL.: "Humanization of an anti-p185HER2 antibody for human cancer therapy", PROC NATL ACAD SCI USA, vol. 89, 1992, pages 4285 - 4289, XP000275844, DOI: doi:10.1073/pnas.89.10.4285
CARTER, P.; L. PRESTA ET AL.: "Humanization of an ahti p185HER2 antibody for human cancer therapy", PROC NATL ACAD SCI U S A, vol. 89, no. 10, 1992, pages 4285 - 9
CHONG L T; DUAN Y; WANG L ET AL.: "Molecular dynamics and free-energy calculations applied to affinity maturation in antibody 48G7.[J", PROC NATL ACAD SCI U S A., vol. 96, no. 25, 1999, pages 14330 - 14335
CLARK L A; GANESAN S; PAPP S ET AL.: "Trends in antibody sequence changes during the somatic hypermutation proccss.[11", JLMMUNOL., vol. 177, no. 1, 2006, pages 333 - 340
DING H Q; KARASAWA N; GODDARD I 1: "Atomic level simulations on a million particles: The cell multipole method for Coulomb and London nonbond interactions[J", J. CHEM. PHYS., vol. 97, no. 6, 1992, pages 4309 - 4315
DING, H. Q.; N. KARASAWA ET AL.: "Atomic level simulations on a million particles: The cell multipole method for Coulomb and London nonbond interactions", J. CHEM. PHYS., vol. 97, no. 6, 1992, pages 4309 - 4315
DU, J.; WANG, H; ZHONG, C.: "Structural Basis for Recognition of CD20 by Therapeutic Antibody Rituximab", J BIOL CHEM, vol. 282, no. 20, 2007, pages 15073 - 15080, XP055094566, DOI: doi:10.1074/jbc.M701654200
DUNBRACK R L.: "Rotamer Libraries in the 21st Century[J", CURRENT OPINION IN STRUCTURAL BIOLOGY, vol. 12, no. 4, 2002, pages 431 - 440, XP055108459, DOI: doi:10.1016/S0959-440X(02)00344-5
ELLISON JW; BERSON BJ; HOOD LE, NUCLEIC ACIDS RES., vol. 10, no. 13, 10 July 1982 (1982-07-10), pages 4071 - 9
ELLISON JW; BERSON BJ; HOOD LE., NUCLEIC ACIDS RES., vol. 10, no. 13, 10 July 1982 (1982-07-10), pages 4071 - 9
FOGOLARI, F.; A. BRIGO ET AL.: "Protocol for MM/PBSA molecular dynamics simulations ofproteins.", BIOPHYS J, vol. 85, no. 1, 2003, pages 159 - 66
FRIGUET B; CHAFFOTTE AF; DJAVADI-OHANIANCE L; GOLDBERG ME: "Measurements of the true affinity constant in solution of antigen-antibody complexes by enzyme-linked immunosorbent assay", J IMMUNOL METHODS, vol. 77, 1985, pages 305 - 319, XP023974579, DOI: doi:10.1016/0022-1759(85)90044-4
HIETER PA; MAX EE; SEIDMAN JG; MAIZEL JV JR; LEDER P., CELL, vol. 22, November 1980 (1980-11-01), pages 197 - 207
IM, W; LEE, M S.; BROOKS, C. L.: "Generalized born model with a simple smoothing function", J. COMPUT. CHEM., vol. 24, 2003, pages 1691 - 1702
IM, W; LEE, M. S.; BROOKS, C. L.: "Generalized born model with a simple smoothing function", J. COMPUT. CHEM., vol. 24, 2003, pages 1691 - 1702
KUHN, B.; GERBER, P.; SCHULZ-GASCH, T.; STAHL, M.: "Validation and use of the MM-PBSA approach for drug discovery", J. MED. CHEM., vol. 48, 2005, pages 4040 - 4048
LO C L; CHOTHIA C; JANIN J.: "The atomic structure of protein-protein recognition sites.[J", J MOL BIOL., vol. 285, no. 5, 1999, pages 2177 - 2198, XP004464323, DOI: doi:10.1006/jmbi.1998.2439
NOVOTNY J; BRUCCOLERI R E; DAVIS M ET AL.: "Empirical free energy calculations: a blind test andfurther improvements to the method.[J", JMOL BIOL., vol. 268, no. 2, 1997, pages 401 - 411, XP004454043, DOI: doi:10.1006/jmbi.1997.0961
NOVOTNY J; SHARP K.: "Electrostatic fields in antibodies and ahtibodyl antigen complexes.[J", PROG BIOPHYS MOL BIOL., vol. 58, no. 3, 1992, pages 203 - 224
PNINA D O.: "Structure and energetics of ligand binding to proteins: Escherichia coli dihydrofolate reductase-trimethoprim, a drug-receptor system[J", PROTEINS: STRUCTURE, FUNCTION, AND GENETICS, vol. 4, no. 1, 1988, pages 31 - 47
PONDER J W; RICHARDS F M.: "Tertiary templates for proteins : Use of packing criteria in the enumeration of allowed sequences for different structural classes [J", JOURNAL OF MOLECULAR BIOLOGY, vol. 193, no. 4, 1987, pages 775 - 791, XP024009929, DOI: doi:10.1016/0022-2836(87)90358-5
See also references of EP2482212A4 *
SENDEROWITZ H; GUARNIERI F; STILL W C.: "A Smart Monte Carlo Technique for Free Energy Simulations of Multiconformational Molecules. Direct Calculations of the Conformational Populations of Organic Molecules [J", J. AM. CHEM. SOC., vol. 117, no. 31, 1995, pages 8211 - 8219

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013153059A1 (en) 2012-04-11 2013-10-17 Politecnico Di Milano Co-crystals of 3-iodopropynyl butylcarbamate
CN116486906A (zh) * 2023-04-17 2023-07-25 深圳新锐基因科技有限公司 基于氨基酸残基突变提高蛋白质分子稳定性的方法及装置
CN116486906B (zh) * 2023-04-17 2024-03-19 深圳新锐基因科技有限公司 基于氨基酸残基突变提高蛋白质分子稳定性的方法及装置

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