WO2015192589A1 - 鼠多瘤病毒衣壳粒的亲和肽配基及其设计筛选方法 - Google Patents

鼠多瘤病毒衣壳粒的亲和肽配基及其设计筛选方法 Download PDF

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WO2015192589A1
WO2015192589A1 PCT/CN2014/090715 CN2014090715W WO2015192589A1 WO 2015192589 A1 WO2015192589 A1 WO 2015192589A1 CN 2014090715 W CN2014090715 W CN 2014090715W WO 2015192589 A1 WO2015192589 A1 WO 2015192589A1
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peptide
affinity
capsid
residues
screening method
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张麟
董晓燕
李艳英
刘晓丹
孙彦
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Tianjin University
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    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K7/00—Peptides having 5 to 20 amino acids in a fully defined sequence; Derivatives thereof
    • C07K7/04—Linear peptides containing only normal peptide links
    • C07K7/06—Linear peptides containing only normal peptide links having 5 to 11 amino acids
    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K14/00—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof
    • C07K14/005—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof from viruses
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B15/00—ICT specially adapted for analysing two-dimensional [2D] or three-dimensional [3D] molecular structures, e.g. structural or functional relations or structure alignment
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B15/00—ICT specially adapted for analysing two-dimensional [2D] or three-dimensional [3D] molecular structures, e.g. structural or functional relations or structure alignment
    • G16B15/30—Drug targeting using structural data; Docking or binding prediction
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    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
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    • C12N2710/00—MICROORGANISMS OR ENZYMES; COMPOSITIONS THEREOF; PROPAGATING, PRESERVING, OR MAINTAINING MICROORGANISMS; MUTATION OR GENETIC ENGINEERING; CULTURE MEDIA dsDNA viruses
    • C12N2710/00011—Details
    • C12N2710/22011—Polyomaviridae, e.g. polyoma, SV40, JC
    • C12N2710/22022—New viral proteins or individual genes, new structural or functional aspects of known viral proteins or genes

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  • the invention relates to an affinity peptide ligand technology for designing a target protein by computer simulation, and the purification of a target protein by affinity chromatography, and belongs to the technical field of computer simulation and protein separation and purification in biotechnology.
  • VLP Virus-Like Particles
  • VP1 major capsid structural protein
  • VP1 is expressed in prokaryotic cells and then exists in the form of capsid granules. It can be assembled into VLP with uniform morphology and structural stability under suitable conditions in vitro. This method of producing VLP in vitro is simple, efficient, and has broad application prospects.
  • N-terminal GST-tagged VP1 can be prepared by high cell density, pH-controlled flow-through culture, and its yield can reach 4.38 g L -1 .
  • GST tag can promote the soluble expression of VP1 protein and facilitate the purification of labeled precursor.
  • expensive thrombin cleavage is required to shed the GST tag, and the shed GST tag requires an additional separation and purification step to remove from the reaction system. As a result, the operation is cumbersome and the cost is increased, which is not conducive to the expansion of production, and limits the application of the polyomavirus-like particles of the mouse.
  • Affinity chromatography separates and purifies target molecules by interaction between biomacromolecules and specific ligands, and has the advantages of high selectivity, high efficiency, and mild operating conditions.
  • the implementation of affinity chromatography depends on the specific recognition between the target molecule and the ligand, so the ligand is the core of the affinity chromatography.
  • small molecule peptide ligands have the advantages of high affinity, high stability, low degradation and easy preparation, and have important development prospects.
  • it is possible to design high-specific affinity peptide ligands by simulating the interaction between target protein-ligands already existing in nature, which helps to improve affinity peptides. Base screening efficiency and accuracy.
  • the murine polyomavirus capsid particle and the minor capsid structural protein VP2 (35 kDa) complex are naturally occurring capsid-ligand conjugates in which the C-terminus (VP2-C) of VP2 acts by hydrophobic interaction
  • the special hairpin structure morphology is bonded to the inner surface of the capsid particles and can be used as the design basis for the affinity peptide ligand of the capsid particles.
  • the object of the present invention is to propose the application of a novel affinity ligand design and screening method for murine polyomavirus capsid particles.
  • the bionic design flow of the capsid affinity peptide ligand of the present invention was first established and verified to be effective.
  • the affinity peptide ligand has the advantages of strong specificity, good stability and simple operation.
  • Novel affinity peptide ligands for murine polyomavirus capsid DWDLRLLY, DWDLRLIY, DWNLRLIY, DWFLNLFY, DWSLKLVY, DWSLRLKY, and DWNLHLPY.
  • novel affinity peptide ligand of the murine polyomavirus capsid particle of the invention and the design screening method thereof are based on the crystal structure of the naturally occurring capsid particle and the minor capsid structural protein VP2-C complex, and the capsid particle is constructed.
  • a novel peptide ligand library, the characteristic sequence is DWXLXLXY, wherein X represents 19 amino acids other than cysteine; see the nucleotide sequence table.
  • Molecular dynamics simulation / Poisson-Boltzmann solvent accessible surface area is used to calculate the molecular mechanism of VP2-C and capsid particle complexes to determine the hydrophobic effect, while VP2-C plays an important role in the binding.
  • the key residues are V283, P285, D286, W287, L289, L293 and Y296.
  • the peptide library was constructed based on five key residues in VP2-C: D286, W287, L289, L293 and Y296; within the scope of the peptide library, the amino acid localization method was used to construct a library of candidate polypeptide molecules.
  • the peptide ligands in the peptide ligand library were sequentially ligated with the murine polyomavirus capsid particles using VINA molecular docking software, and a total of 1158 peptide ligands with a binding free energy lower than -6.5 kcal/mol were selected.
  • 334 peptide ligands were screened. 227 peptide ligands with C-terminal orientation consistent with VP2-C were selected for ROSETTA FlexPepDock docking experiments. The optimal 10 peptide ligands were selected for MD simulation.
  • the characteristic sequence is DWXLXLXY, wherein X represents a library of 19 amino acid polypeptides other than cysteine, and 2) is based on 5 key residues in VP2-C: D286, W287, L289, L293 and Y296 construct a library of candidate polypeptides by amino acid localization in the range of peptide library;
  • the modification strategy includes: adding 1 or more amino acid residues at the N-terminus; adding 1 or more amino acids at the C-terminus a residue; adding one or more amino acid residues between adjacent residues of the polypeptide; replacing one or more residues in the polypeptide with other amino acid residues.
  • the invention constructs a novel affinity peptide ligand library of capsid particles based on the VP2-C affinity model, which is based on five key residues in VP2-C: D286, W287, L289, L293 and Y296.
  • the polypeptide library sequence is characterized by: DWXLXLXY, wherein X represents 19 amino acids other than cysteine.
  • the peptide library was sequentially subjected to VINA docking, root mean square deviation comparison, C-terminal comparison, ROSETTA FlexPepDock docking, and molecular dynamics simulation combined with free energy calculation for re-screening to obtain seven peptide ligands with high affinity to capsid particles: DWDLRLLY, DWDLRLIY, DWNLRLIY, DWFLNLFY, DWSLKLVY, DWSLRLKY, and DWNLHLPY. Among them, the first screening DWDLRLLY was verified to be an effective affinity ligand for capsid particles.
  • the present invention utilizes molecular modeling and chromatographic experiments to obtain a capsid particle affinity peptide ligand, as shown in Figure 1, which is characterized by the following process:
  • the amino acid localization method was used to determine the polypeptide sequence pattern as DWXLXLXY (where X represents Remove 19 amino acids other than cysteine; use the perl script to call CHARMM software to construct a peptide library containing 6859 sequences.
  • VINA docking software 6859 peptide ligands in the peptide library were sequentially docked with the binding domain of the capsid granule surface. Then, based on the distribution of the scoring scores, polypeptide molecules with a combined free energy (scoring fraction) of less than -6.5 kcal/mol were selected, for a total of 1158 polypeptides.
  • g_rms program included in the GROMACS 4.5.3 software package the root mean square deviation (RMSD) between the five hotspot residues in VP2-C and the corresponding hotspot residues in the 1158 peptide sequences obtained from docking was calculated, and VINA was compared accordingly.
  • RMSD root mean square deviation
  • NPT regular (NVT) ensemble of 200 ps and the isothermal equal pressure (NPT) ensemble of 200 ps are sequentially used.
  • the kinetic equilibrium was followed by an unrestricted MD simulation of 20 ns comparing the changes in the conformation of the ten peptides before and after the simulation.
  • the final 3 ns extraction conformation was selected, and the free energy calculation and decomposition were performed by the MM/PBSA method to further evaluate the affinity and specificity of the polypeptide.
  • seven peptide ligands have higher affinity: DWDLRLLY, DWDLRLIY, DWNLRLIY, DWFLNLFY, DWSLKLVY, DWSLRLKY and DWNLHLPY.
  • the method firstly uses molecular dynamics simulation and MM/PBSA free energy calculation method to obtain hot-spot residues with high affinity to capsid particles in VP2-C, and to determine the simplified affinity model of VP2-C and capsid particles. Thereby, an affinity peptide ligand library of the capsid particles is constructed. The ligands were screened by molecular docking, molecular dynamics simulation and free energy calculation to obtain peptide ligands with higher affinity with the capsid particles. Furthermore, a series of experimental methods such as static adsorption, affinity chromatography and SDS-PAGE were used to verify the separation and purification efficiency of the obtained ligands.
  • the screening of the first DWDLRLLY has confirmed the effectiveness of separation and purification of capsid particles, and has the advantages of high specificity, high stability and easy operation, which proves the feasibility of the bionic design process of the affinity peptide ligand of the present invention.
  • DWDLRLLY is also found to be too hydrophobic, and in the subsequent experiments, the polypeptide and other polypeptides in the peptide library need to be modified to obtain a ligand with higher affinity and specificity.
  • Modification methods include adding one or more amino acids at the N-terminus or C-terminus of the polypeptide; adding one or more amino acids between adjacent residues in the polypeptide; and replacing one or more residues in the polypeptide with other amino acids, etc. .
  • Figure 1 shows the design and screening strategy of novel affinity peptide ligands for murine polyomavirus capsid particles.
  • the crystal structure of the VP2-C and capsid granule complexes used in this study was from the PDB database ( http://www.rcsb.org/pdb/ , number: 1CN3), in which the capsid particles contained 5 VP1 (34-316) Residue), VP2-C contains 19 residues (residues 279-297).
  • Molecular dynamics simulations were performed using GROMACS 4.5.3 and the CHARMM27 all-atom stand.
  • the VP2-C and capsid particle complexes were first dissolved in a box (12.163 ⁇ 12.163 ⁇ 12.163 nm) using the TIP3P water molecular model. Add 225 Na + and 190 Cl - .
  • the limiting kinetic equilibrium of the 200 ps regular (NVT) ensemble and the 200 ps isothermal isobaric (NPT) ensemble is performed in turn, and the system temperature is set to 298.15 K, and the temperature is maintained by the V-rescale method. All simulations use periodic boundary conditions. When the non-bonding effect is calculated, the distance is cut off by 1.2 nm, and the long-range electrostatic action is calculated by PME. The Lincs is used to limit all hydrogen atoms, and the time step is 2fs. The simulation time is 20 ns.
  • the simulation results show that the root mean square deviation (RMSD) of the composite appears at 5 ns, and the potential energy tends to be stable. Therefore, the 17-20 ns trajectory of the composite was sampled at intervals of 40 ps, resulting in a 75-frame conformation for free energy calculation analysis. It is calculated that the hydrophobic interaction of VP2-C and capsid granules is -79kcal/mol, and the electrostatic contribution is 3kcal/mol. Therefore, the affinity between capsid granules and VP2-C is mainly driven by hydrophobic interaction. This is the knot of the X-ray crystal diffraction structure On agreement.
  • RMSD root mean square deviation
  • Hotspot residues are defined as residues that contribute more to binding free energy and residues that participate in the formation of important intermolecular effects to compensate for unfavorable solvation.
  • a standard of ⁇ 2.5 kcal/mol is used to identify residues that contribute more to free energy.
  • Six hotspot residues in VP2-C were calculated, namely V283, P285, D286, W287, L289 and Y296.
  • L293 Although the contribution of L293 to free energy does not meet the criteria for hotspot residues, it has been reported in the literature that L181E on VP3 in SV40 virus causes a 33% decrease in the binding capacity of VP3 to capsid particles, whereas L181 corresponds to the polyomavirus VP2. L293. Considering that this sequence is a highly conserved region of polyomavirus, it is concluded that L293 also plays an important role in the binding of VP2 to capsid particles, so L293 is retained in the process of constructing a simplified affinity model.
  • VP2-C affinity simplified model was constructed, including V283, P285, D286, W287, L289, L293 and Y296.
  • the resulting polypeptide construction pattern is the octapeptide library: DWXLXLXY (X is a residue that does not contain Cys).
  • the CHARMM software was used to construct the peptide library using the perl script, which contained a total of 6859 sequences, each of which contained the above five hotspot residues.
  • This study used the g_rms program included in the GROMACS 4.5.3 software package to calculate the RMSD between the hot spot residues of 1158 peptide sequences and the corresponding hotspot residues in the capsid particles.
  • the smaller the RMSD value the closer the conformation of the hotspot residue contained in the polypeptide to the conformation of the corresponding hotspot residue in VP2-C.
  • the results show that the RMSD values are distributed between 0.3 and 0.6 nm. 334 polypeptide sequences with RMSD ⁇ 0.4 nm were selected for further analysis.
  • VP2-C enters the inner cavity from the bottom of the capsid granule from bottom to top, so its C-terminus is located at the bottom of the capsid granule.
  • the N-terminus is toward the bottom of the capsid, it is not considered.
  • 227 peptides were screened for further screening.
  • Polypeptide rescreening was performed using the ROSETTA FlexPepDock web server.
  • Flexpepdock consists mainly of two modules for optimizing the peptide backbone and rigid body orientation.
  • the initial structure was optimized with 200 rounds of independent Flexpepdock simulation. Among them, 100 rounds are strictly using high-resolution mode simulation, and the other 100 rounds are firstly simulated by low-resolution pre-optimization and high-resolution optimization.
  • a total of 200 model structures were generated and then scored according to the generic full-atom energy score, and each peptide obtained an optimal 10 conformations.
  • the top ten polypeptides finally screened were DWDLRLLY, DWDLRLIY, DWGLRLKY, DWSLKLVY, DWFLNLFY, DWSLDLWY, DWGLKLIY, DWNLRLIY, DWSLRLKY, DWNLHLPY according to the level of the scoring function.
  • the next step is to use a more accurate but also more time-consuming molecular dynamics simulation combined with the free energy calculation method. Investigate the affinity of the complex. Molecular dynamics simulation parameters are the same as in Example 1. The conformational changes of the polypeptides before and after the simulation were compared using the VMD plot.
  • the binding free energy of these peptide ligands to the inner surface of the capsid particles was calculated using the MM/PBSA method.
  • the simulation results are ranked from high to low in order of DWDLRLLY, DWDLRLIY, DWNLRLIY, DWFLNLFY, DWSLKLVY, DWSLRLKY, DWNLHLPY, DWSLDLWY, DWGLRLKY, DWGLKLIY.
  • the last three peptides in the ranking are three ligands that are unstable in binding to the conformation of the capsid particle in the molecular dynamics simulation.
  • the free energy calculation results show that the binding of the ten peptides to the capsid particles is dominated by hydrophobic interaction, which is consistent with the initial design idea, indicating the accuracy of rational design.
  • the free energy calculation optimal peptide is DWDLRLLY, which has a binding free energy of -61 kcal/mol to the capsid particles, and the binding free energy of VP2-C to the capsid particles is -76 kcal/mol, and the affinity is close.
  • DWDLRLLY may be a highly specific affinity ligand for capsid particles.
  • the Thiopropyl Sepharose 6B (GE Healthcare) medium was washed with membrane water and then pre-equilibrated with cross-linking buffer (0.5 M NaCl, 1 mM EDTA, 0.1 M PBS, pH 6.5) for 12 h, drained and weighed 1 g of wet medium.
  • the flask was thoroughly mixed into an Erlenmeyer flask containing 2.57 mg of the polypeptide and 10 mL of a crosslinking buffer, and shaken at 25 ° C for 170 hours in a water bath at 170 rpm.
  • An affinity polypeptide medium (designated DWDLRLLY-6B) having a ligand density of 2 ⁇ M/(g of dried wet medium) was finally obtained.
  • the pGEX-Ssp DnaB-Ser-VP1 plasmid was constructed and introduced into E. coli BL21 (DE3), and then inoculated into 25 mL of TB medium [100 mg/L ampicillin, 12 g/L peptone, 24 g/L yeast extract, 0.4% (v/). v) Glycerol, 2.31 g/L KH 2 PO 4 , 12.54 g/L K 2 HPO 4 ], cultured overnight at 37 ° C, 170 rpm.
  • the above bacterial solution was inoculated to 250 mL of TB medium at a ratio of 1:1000, and cultured at 37 ° C to an OD 600 ⁇ 0.5-0.6 at 37 ° C, and a final concentration of 0.3 mM isopropylthio- ⁇ -D-half was added.
  • the lactose (IPTG) was induced to culture for 24 h at 26 ° C, 170 rpm.
  • the cells were collected, resuspended, sonicated on ice, and the supernatant of E. coli was collected by centrifugation.
  • DWDLRLLY-6B medium was equilibrated with equilibration buffer (50 mM PBS, 200 mM NaCl, pH 6.0) for 12 h, then drained. Accurately weigh 0.1 g of medium into a 25 mL Erlenmeyer flask, add 5 mL of the lysate supernatant, and place the conical flask. The cells were placed in a water bath shaker, shaken at 170 ° C for 24 h at 25 ° C, centrifuged at 10,000 rpm for 1 min, and the supernatant was taken for SDS-PAGE analysis.
  • equilibration buffer 50 mM PBS, 200 mM NaCl, pH 6.0
  • the DWDLRLLY-6B affinity medium was loaded into a 1 mL Tricorn 5 x 5 column by gravity sedimentation, and the chromatogram was washed with equilibration buffer (50 mM PBS, 200 mM NaCl, pH 7.0) to a baseline. Load 200 ⁇ L of the lysate supernatant and rinse the column with equilibration buffer to baseline. The 5-10 column volumes were then rinsed with elution buffer (50 mM acetate buffer, pH 3.0). After the peak to be eluted was completely separated, the affinity medium was regenerated with 2-5 column volumes of regeneration buffer (100 mM Gly-HCl, pH 2.4).
  • equilibration buffer 50 mM PBS, 200 mM NaCl, pH 7.0
  • the flow rates for equilibration, washing, elution and regeneration were both 0.5 mL/min and the loading flow rate was 0.2 mL/min.
  • the elution peak and elution peak components in the isolated E. coli lysate supernatant were subjected to SDS-PAGE electrophoresis analysis.
  • the purity of VP1 was calculated using Gel-Pro analysis software. The results showed that the purity of VP1 in the E. coli lysate supernatant was increased from the initial 15.6% to 70.1% by one-step affinity chromatography.
  • affinity peptide ligand DWDLRLLY can effectively purify the target protein, which is a high-affinity peptide ligand of the murine polyomavirus capsid.
  • all 6859 sequences in the peptide ligand library have the same design idea (key residues of VP2-C: D286, W287, L289, L293 and Y296) and structural features, which are theoretically possible It is an affinity peptide ligand for capsid particles, and experimental data have been obtained indicating that the affinity peptide ligand in the peptide library is a potent affinity ligand for the murine polyomavirus capsid.
  • the invention provides a novel affinity peptide ligand of the murine polyomavirus capsid particles and a design screening method thereof.
  • the first affinity peptide ligand DWDLRLLY was screened and verified as an effective affinity ligand for capsid particles.
  • the capsid particles can be separated and purified from the E. coli lysate supernatant in the preparation of virus-like particles. with broadly application foreground.
  • problems with DWDLRLLY such as excessive hydrophobicity.
  • the polypeptide and other polypeptides in the peptide library need to be modified to obtain a ligand with higher affinity and specificity.
  • Modification methods include adding one or more amino acids at the N-terminus or C-terminus of the polypeptide; adding one or more amino acids between adjacent residues in the polypeptide; and replacing one or more residues in the polypeptide with other amino acids, etc. .

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Abstract

提供了鼠多瘤病毒衣壳粒的亲和肽配基及其设计筛选方法。所述亲和肽配基可用于所述衣壳粒的分离纯化。

Description

鼠多瘤病毒衣壳粒的新型亲和肽配基及其设计筛选方法 技术领域
本发明涉及利用计算机模拟设计目标蛋白质的亲和肽配基技术，以及利用亲和色谱技术纯化目标蛋白质，属于生物技术中的计算机模拟和蛋白质分离纯化技术领域。
背景技术
鼠多瘤病毒样颗粒(Virus-Like Particles,VLP)是由主要衣壳结构蛋白VP1(42kDa)自组装而形成的空心纳米颗粒，在疫苗、基因治疗、药物载体和材料科学等领域具有广阔的应用前景。鼠多瘤病毒VLP包含72个向右歪斜的呈T＝7d排布的衣壳粒，每个衣壳粒由5个VP1组成。
VP1在原核细胞中表达纯化后以衣壳粒形态存在，在体外适宜条件下能组装成形态均一、结构稳定的VLP。这种体外生产VLP的方法简单、高效，具有广阔的应用前景。目前，利用高细胞密度、pH控制流加培养可制备N端带有GST标签的VP1，其产量能够达到4.38g L-1。其中，GST标签既能够促进VP1蛋白的可溶性表达，又利于带标签前体的纯化。然而在纯化后处理时，需要昂贵的凝血酶切割使GST标签脱落，且脱落的GST标签还需要额外的分离纯化步骤从反应体系中去除。因而导致操作繁琐、成本增大，不利于生产扩大，限制鼠多瘤病毒样颗粒的应用。
亲和色谱利用生物大分子和特异性配基间的相互作用分离纯化目标分子，具有高选择性、高效率、操作条件温和等优点。亲和色谱的实现取决于目标分子与配基之间的特异性识别，因此配基是亲和色谱的核心。其中，小分子肽配基具有高亲和性高、高稳定性、不易降解及制备简便等优点，具有重要的开发前景。而近年来随着分子模拟技术的飞速发展，通过模拟自然界已存在的目标蛋白-配体之间的相互作用以设计筛选高特异性亲和肽配基成为可能，有助于提高亲和肽配基的筛选效率及准确性。
鼠多瘤病毒衣壳粒和次要衣壳结构蛋白VP2(35kDa)复合物是天然存在的衣壳粒-配体结合物，其中，VP2的C端(VP2-C)通过疏水作用以一种特殊的发卡结构形态结合到衣壳粒的内表面，可作为衣壳粒的亲和肽配基的设计基础。
发明内容
本发明的目的在于提出鼠多瘤病毒衣壳粒新型亲和配基设计及筛选方法的应用。本发明所述的衣壳粒亲和肽配基的仿生设计流程是首次建立的，并经验证是有效的。所述的亲和肽配基具有特异性强、稳定性好和操作简便等优点。
本发明的技术方案如下：
鼠多瘤病毒衣壳粒的新型亲和肽配基：DWDLRLLY、DWDLRLIY、DWNLRLIY、DWFLNLFY、DWSLKLVY、DWSLRLKY和DWNLHLPY。
本发明的鼠多瘤病毒衣壳粒的新型亲和肽配基及其设计筛选方法，是依据天然存在的衣壳粒和次要衣壳结构蛋白VP2-C复合物晶体结构，构建衣壳粒的新型肽配基库，特征序列为DWXLXLXY，其中X代表除去半胱氨酸以外的19种氨基酸；见核苷酸序列表。
利用分子动力学模拟/泊松-波尔兹曼溶剂可及表面积计算解析VP2-C与衣壳粒复合物的分子作用机理，确定疏水作用占主导，而VP2-C中对结合起重要贡献的关键残基为V283、P285、D286、W287、L289、L293和Y296。
多肽库构建依据为VP2-C中5个关键残基：D286、W287、L289、L293和Y296；在肽库的范围内，利用氨基酸定位法构建候选多肽分子库。
通过分子对接筛选、均方根偏差比较以及分子动力学模拟结合自由能计算，进行鼠多瘤病毒衣壳粒的高亲和性肽配基的筛选。
利用VINA分子对接软件将肽配基库中的肽配基依次与鼠多瘤病毒衣壳粒进行对接，选取结合自由能低于-6.5kcal/mol的肽配基，共计1158条。
利用GROMACS分子模拟软件自带的g_rms程序计算VINA对接得到的1158个肽配基与VP2-C中相应的关键残基之间的均方根偏差，选择334个肽配基进行研究。
根据C末端方向对334个肽配基继续筛选，选取C末端方向与VP2-C一致的227个肽配基进行ROSETTA FlexPepDock对接实验复筛，选取最优的10条肽配基进行MD模拟。
对筛选得到的10条肽配基与鼠多瘤病毒衣壳粒的复合物进行MD模拟，并利用MM/PBSA方法进行自由能计算和分解，进一步评价肽配基的亲和性和特异性，得到具有较高亲和性的7条肽配基：DWDLRLLY、DWDLRLIY、DWNLRLIY、DWFLNLFY、DWSLKLVY、DWSLRLKY和DWNLHLPY。
本发明所述的：1)特征序列为DWXLXLXY，其中X代表除去半胱氨酸以外的19种氨基酸多肽库、和2)依据为VP2-C中5个关键残基：D286、W287、L289、L293和Y296在肽库的范围内，利用氨基酸定位法构建候选多肽分子库；对其修饰改造策略包括：在其N端添加1或多个氨基酸残基；在其C端添加1或多个氨基酸残基；在多肽相邻残基之间添加1或多个氨基酸残基；将多肽中的某一个或某几个残基替换成其他氨基酸残基。
详细说明如下：
本发明基于VP2-C亲和模型构建衣壳粒新型亲和肽配基库，其依据为VP2-C中5个关键残基：D286、W287、L289、L293和Y296。该多肽库序列特征为：DWXLXLXY，其中X代表除去半胱氨酸以外的19种氨基酸。
将多肽库依次进行VINA对接、均方根偏差比较、C端比较、ROSETTA FlexPepDock对接以及分子动力学模拟结合自由能计算复筛，获得与衣壳粒具有较高亲和性的七条肽配基：DWDLRLLY、DWDLRLIY、DWNLRLIY、DWFLNLFY、DWSLKLVY、DWSLRLKY和DWNLHLPY。其中筛选排名第一的DWDLRLLY经实验验证是衣壳粒的有效亲和配基。
值得指出的是，虽然虚拟筛选能够快速精确的富集和筛选具有较高亲和性的多肽，但是由于计算机模拟的局限性(如利用不同软件或采用不同参数可能产生不同结果)，对生物分子间的相互作用预测还不能达到与实际情况完全相同，在实际筛选过程中可能会造成具有较高亲和性和特异性的多肽被漏筛，因此不排除多肽库中其余的6852条多肽分子也可能是衣壳粒的多肽亲和配基。
本发明利用分子模拟和色谱实验获得衣壳粒亲和肽配基的方法，如图1所示，其特征在于包括以下过程：
1.应用分子动力学模拟/泊松-波尔兹曼溶剂可及表面积(molecular mechanics-Poisson-Boltzmann surface area,MM/PBSA)方法计算VP2-C与衣壳粒复合物(晶体结构取自PDB：1CN3)的相对结合自由能。利用自由能分解方法解析VP2-C与衣壳粒的结合机理，分析确定VP2-C的热点残基。基于上述解析获得的分子机理和残基的空间排布特点，构建VP2-C的简化亲和结合模型。
2.根据VP2-C中位于α-螺旋上的5个热点残基(D286、W287、L289、L293和Y296)的构象和相对位置，利用氨基酸定位法，确定多肽序列模式为DWXLXLXY(其中X代表除去半胱氨酸以外的19种氨基酸)；利用perl脚本调用CHARMM软件构建含有6859条序列的多肽库。
3.利用VINA对接软件将多肽库中6859条肽配基依次与衣壳粒内腔表面结合域进行对接。然后根据打分分数的分布，选取结合自由能(打分分数)低于-6.5kcal/mol的多肽分子，共计1158个多肽。利用GROMACS 4.5.3软件包自带的g_rms程序计算VP2-C中5个热点残基与对接得到的1158条多肽序列中相应热点残基之间的均方根偏差(RMSD)，据此比较VINA对接后多肽中的热点残基与VP2-C中的热点残基构象之间的差异。RMSD值越小表示多肽包含的热点残基的对接构象与VP2-C中热点残基构象越接近。根据RMSD数值的分布，选择RMSD<0.4nm的334个多肽做进一步分析。在VP2-C与衣壳粒复合物的晶体结构中，VP2-C的C末端位于衣壳粒底部，因此候选多肽如果C端朝向与VP2-C不一致，即N端位于衣壳粒底部则不予考虑。由此得到227个多肽，再利用ROSETTA FlexPepDock进行对接实验复筛。对接实验在ROSETTA FlexPepDock服务器上进行(http://flexpepdock.furmanlab.cs.huji.ac.il/)，对接参数为默认参数，每条多肽与衣壳粒的复合物一共产生200个构象。选取对接打分分数(结合界面能量分数，I_sc)前十位的多肽进行下一步研究。
4.将步骤3中利用ROSETTA FlexPepDock对接获得的十条多肽与衣壳粒复合物的构象作为初始构象，利用GROMACS 4.5.3软件包，选用CHARMM27力场。将多肽与衣壳粒复合物置于12.16×12.16×12.16nm3的盒子中；水分子模型选择TIP 3P模型；然后加入平衡系统净电荷以及稳定缓冲液(200mM NaCl)溶液所需的Na+和Cl-；之后进行能量最小化，去除体系中的原子间的碰撞和不正确的几何构型；接下来用依次进行200ps的正则(NVT)系综和200ps的等温等压(NPT)系综下的限制动力学平衡，最后进行20ns的无限制MD模拟，比较十条多肽在模拟前后构象的变化。模拟结束后，选取最后3ns提取构象，利用 MM/PBSA方法进行自由能计算和分解，进一步评价多肽的亲和性和特异性。其中七条肽配基具有较高亲和性：DWDLRLLY、DWDLRLIY、DWNLRLIY、DWFLNLFY、DWSLKLVY、DWSLRLKY和DWNLHLPY。
5选取筛选排名第一的多肽DWDLRLLY，固定到Thiopropyl Sepharose 6B色谱介质上制成亲和介质，然后通过蛋白静态吸附、亲和色谱、聚丙烯酰胺凝胶电泳(SDS-PAGE)等一系列实验方法，确证DWDLRLLY是衣壳粒的有效亲和配基。
本方法首先利用分子动力学模拟和MM/PBSA自由能计算方法获得VP2-C中与衣壳粒具有高亲和性的热点残基，确定VP2-C与衣壳粒作用的简化亲和模型，藉此构建衣壳粒的亲和肽配基库。通过分子对接、分子动力学模拟和自由能计算进行配基筛选，获得与衣壳粒具有较高亲和性的肽配基。进而通过静态吸附、亲和色谱、SDS-PAGE等一系列实验方法验证所得配基对衣壳粒的分离纯化效能。其中，筛选排名第一的DWDLRLLY已经确证能有效分离纯化衣壳粒，且具有特异性强、稳定性高和操作简便等优点，证实本发明所述亲和肽配基的仿生设计流程的可行性。然而，实际使用中也发现DWDLRLLY存在疏水性过强等问题，在后续实验中还需对该多肽以及多肽库中其他多肽进行改造，以期获得具有更高亲和性和特异性的配基。改造方法包括在多肽N端或C端添加1个或多个氨基酸；在多肽内部相邻残基之间添加一个或多个氨基酸；将多肽中某个或某几个残基替换成其他氨基酸等。
附图说明
图1为鼠多瘤病毒衣壳粒的新型亲和肽配基设计及筛选策略。
具体实施方式
下面结合具体实施例对本发明作进一步的说明。
实施例1VP2-C与衣壳粒亲和作用机理解析及VP2-C简化亲和结合模型的构建
本研究采用的VP2-C与衣壳粒复合物晶体结构来自PDB数据库(http://www.rcsb.org/pdb/，编号：1CN3)，其中衣壳粒包含5条VP1(34-316号残基)，VP2-C上包含19个残基(279-297号残基)。分子动力学模拟采用GROMACS 4.5.3以及CHARMM27全原子立场。首先采用TIP3P水分子模型将VP2-C与衣壳粒复合物溶解于正方体盒子中(12.163×12.163×12.163nm)。添加225个Na+和190个Cl-。体系经能量最小化后，依次进行200ps的正则(NVT)系综和200ps的等温等压(NPT)系综下的限制动力学平衡，体系温度设为298.15K，采用V-rescale法维持恒温，所有的模拟都采用周期性边界条件。计算非键作用时采用1.2nm的距离截断，采用PME计算长程静电作用，采用Lincs用于限制所有氢原子，时间步长为2fs。模拟时间为20ns。
模拟结果显示在5ns处复合物的均方根偏差(RMSD)出现平台，且势能基本趋于稳定。因此对复合物的17-20ns的轨迹以40ps的间隔取样，得到75帧构象供自由能计算分析。计算得到VP2-C与衣壳粒复合物的疏水作用贡献为-79kcal/mol，而静电作用贡献为3kcal/mol，因此衣壳粒与VP2-C之间的亲和力主要以疏水作用为驱动力，这与X射线晶体衍射结构的结 论一致。对于静电作用，绝大部分对分子结合有利的分子间静电作用贡献(-171kcal/mol)被不利的静电溶剂化作用能(177kcal/mol)抵消，而导致总的静电作用能相对很小。
对VP2-C与衣壳粒复合物中VP2-C进行自由能分解来确定热点残基。热点残基被定义为对结合自由能贡献较大的残基以及参与形成重要分子间作用以补偿不利的溶剂化作用的残基。采用±2.5kcal/mol的标准来识别对自由能贡献较大的残基。计算得到VP2-C中的六个热点残基，分别是V283、P285、D286、W287、L289和Y296。L293对自由能的贡献虽然不符合热点残基的标准，但是有文献报道SV40病毒中VP3上的L181E会导致VP3与衣壳粒的结合能力下降33％，而L181恰好对应鼠多瘤病毒VP2的L293。考虑到该段序列是多瘤病毒的高度保守区，因此推断认为L293对VP2与衣壳粒的结合同样发挥重要作用，所以L293在构建简化亲和模型的过程中予以保留。最后根据VP2-C与衣壳粒的亲和机理和VP2-C的热点残基分布，构造了一个VP2-C的亲和简化模型，包含V283、P285、D286、W287、L289、L293和Y296。
实施例2多肽库的构建
选取距离衣壳粒底部最近的五个关键残基D286、W287、L289、L293和Y296作为多肽构建的起始点，能最大限度的避免实际操作中存在的空间位阻效应。W287、L289、L293和Y296几乎位于同一直线上的特点，也有利于短肽配基设计，且不需考虑VP2的空间构象。已知肽键的长度≈
Figure PCTCN2014090715-appb-000001
；氨基酸主链长度≈
Figure PCTCN2014090715-appb-000002
；插入一个氨基酸残基需2个肽键长度和一个氨基酸的主链长度≈2×1.33+2.78＝
Figure PCTCN2014090715-appb-000003
；利用VMD计算得到W287-L289＝
Figure PCTCN2014090715-appb-000004
,L289-L293＝
Figure PCTCN2014090715-appb-000005
，L293-Y296＝
Figure PCTCN2014090715-appb-000006
。因此每两个相邻热点残基之间可各插入一个氨基酸。最后得到的多肽构建模式为八肽库：DWXLXLXY(X为不包含Cys的残基)。利用perl脚本调用CHARMM软件构建多肽库，总共包含6859条序列，每条序列都包含上述5个热点残基。
实施例3多肽与衣壳粒的对接
1.VINA对接
利用VINA软件，分别将6859条多肽对接到衣壳粒内腔表面的结合域上，所有多肽的打分分数在-4～-8kcal/mol之间，此范围符合亲和配基的适中亲和力要求(结合常数在104～108M-1之间)。筛选时为避免漏选，根据经验值和分布结果，选取结合自由能低于-6.5kcal/mol的多肽，共计1158条。
2.RMSD计算
本研究利用GROMACS 4.5.3软件包自带的g_rms程序计算VINA对接得到的1158条多肽序列热点残基与衣壳粒中相应的热点残基之间的RMSD。RMSD值越小，表示多肽包含的热点残基的对接构象与VP2-C中相应热点残基的构象越接近。结果表明，RMSD值分布在0.3～0.6nm之间。选择RMSD<0.4nm的334个多肽序列作下一步分析。
3.C端朝向比较。
在VP2-C与衣壳粒复合物中，VP2-C从衣壳粒底部由下而上进入内腔，因此其C端位于衣壳粒的底部。对于朝向与VP2-C不一致的多肽，即N端朝向衣壳粒底部，则不在考虑范围。最终筛选出227条多肽作进一步筛选。
4.FlexPepDock复筛候选多肽
利用ROSETTA FlexPepDock网站服务器进行多肽复筛。Flexpepdock主要包含两个模块，分别用于优化肽骨架和刚体方向。初始结构通过200轮独立的Flexpepdock模拟进行优化。其中100轮是严格利用高分辨率模式模拟，另100轮先是通过低分辨率的预优化再进行高分辨率优化的模式模拟。总共产生200个模型结构，然后再根据generic full-atom energy score进行打分，每条多肽得到最优的10个构象。最终筛选出的前十名多肽，按照打分函数高低依次为DWDLRLLY、DWDLRLIY、DWGLRLKY、DWSLKLVY、DWFLNLFY、DWSLDLWY、DWGLKLIY、DWNLRLIY、DWSLRLKY、DWNLHLPY。
实施例4分子动力学(MD)模拟和MM/PBSA自由能计算
为了更加精确的利用计算机辅助配基设计预测衣壳粒与肽配基复合物之间的亲和作用力，接下来利用精度更高但也更耗时的分子动力学模拟结合自由能计算的方法考察复合物的亲和力大小。分子动力学模拟参数同实例1。利用VMD作图比较模拟前后多肽的构象变化。结果发现除了DWGLKLIY、DWGLRLKY和DWSLDLWY，其余七条多肽(DWDLRLLY、DWDLRLIY、DWSLKLVY、DWFLNLFY、DWNLRLIY、DWSLRLKY和DWNLHLPY)与衣壳粒在模拟过程中均表现出了稳定的结合构象，说明这七条多肽可能是衣壳粒的有效亲和配基。
利用MM/PBSA方法计算这些肽配基与衣壳粒内表面的结合自由能。模拟结果排名由高到低依次为DWDLRLLY、DWDLRLIY、DWNLRLIY、DWFLNLFY、DWSLKLVY、DWSLRLKY、DWNLHLPY、DWSLDLWY、DWGLRLKY、DWGLKLIY。排名最后的三条多肽是分子动力学模拟中与衣壳粒构象结合不稳定的三条配基。自由能计算结果表明该十条多肽与衣壳粒的结合都是以疏水作用为主导，这与初始设计思路相一致，表明理性设计的精确性。自由能计算最优的多肽为DWDLRLLY，它与衣壳粒的结合自由能为-61kcal/mol，而VP2-C与衣壳粒的结合自由能为-76kcal/mol，两者亲和力接近。因此DWDLRLLY可能是衣壳粒的高特异性亲和配基。
实施例5亲和色谱实验验证
1.DWDLRLLY-6B亲和介质的制备以及大肠杆菌裂解液的制备
将Thiopropyl Sepharose 6B(GE Healthcare)介质用过膜水清洗后再用交联缓冲液(0.5M NaCl,1mM EDTA,0.1M PBS，pH 6.5,)预平衡12h，抽干后称取1g湿介质加入到含有2.57mg多肽和10mL交联缓冲液的锥形瓶中，充分混合，25℃170rpm水浴摇床反应2小时。最终得到配基密度为2μM/(g抽干湿介质)的亲和多肽介质(命名为DWDLRLLY-6B)。
构建pGEX-Ssp DnaB-Ser-VP1质粒，导入大肠杆菌BL21(DE3)后，接种于25mL TB培养基[100mg/L氨苄青霉素，12g/L蛋白胨，24g/L酵母提取物，0.4％(v/v)glycerol，2.31g/LKH2PO4，12.54g/L K2HPO4]中，37℃,170rpm培养过夜。将上述菌液按照1：1000比例接种至250mL的TB培养基中，170rpm，37℃培养至OD600≈0.5-0.6时，加入终浓度为0.3mM的异丙基硫代-β-D-半乳糖苷(IPTG)，26℃，170rpm诱导培养24h。收集菌体，重悬，冰上超声破碎，离心收集大肠杆菌裂解上清液。
2、亲和介质与衣壳粒的静态吸附实验
将DWDLRLLY-6B介质用平衡缓冲液(50mM PBS,200mM NaCl,pH 6.0)平衡12h后抽干，准确称取0.1g介质置于25mL锥形瓶中，加入5mL裂解上清液，将锥形瓶置于水浴摇床中，25℃，170rpm振荡24h，取出10,000rpm离心1min，取上清液进行SDS-PAGE分析。结果表明亲和多肽介质几乎吸附了裂解上清液中全部的衣壳粒，而对照中的空白介质则不吸附。同时，大部分杂蛋白都被保留到上清液中，表明该亲和多肽介质能特异性识别衣壳粒。值得提出的是，吸附是在较高盐浓度下(200mM)进行的，表明DWDLRLLY与衣壳粒之间是以疏水作用为驱动力的，这与模拟结果相一致。
3.色谱分离纯化实验
采用重力沉降法将DWDLRLLY-6B亲和介质装入1mL Tricorn5×5柱中，用平衡缓冲液(50mM PBS,200mM NaCl,pH 7.0)冲洗色谱至基线平。上样200μL裂解上清液，再用平衡缓冲液冲洗色谱柱至基线平。然后用洗脱缓冲液(50mM醋酸盐缓冲液，pH3.0)冲洗5-10个柱体积。待洗脱峰完全分离后，用2-5个柱体积再生缓冲液(100mM Gly-HCl，pH2.4)进行亲和介质再生。平衡、清洗、洗脱和再生的流速均为0.5mL/min，上样流速为0.2mL/min。对分离大肠杆菌裂解上清液中的流出峰和洗脱峰组分进行SDS-PAGE电泳分析。利用Gel-Pro分析软件计算VP1的纯度。结果表明，通过一步亲和色谱纯化，大肠杆菌裂解上清液中VP1的纯度能够从最初的15.6％提高到70.1％。
因此，实验表明，亲和肽配基DWDLRLLY能够有效纯化目标蛋白，是鼠多瘤病毒衣壳粒的高亲和性肽配基。此外，值得提出的是，肽配基库中的全部6859个序列具有相同的设计思路(VP2-C的关键残基：D286、W287、L289、L293和Y296)和结构特征，理论上都有可能是衣壳粒的亲和肽配基，已取得的实验数据表明肽库中的亲和肽配基是鼠多瘤病毒衣壳粒的有效亲和配基。
本发明提出鼠多瘤病毒衣壳粒的新型亲和肽配基及其设计筛选方法。筛选所得排名第一的亲和肽配基DWDLRLLY，经实验验证是衣壳粒的有效亲和配基，能够从大肠杆菌裂解上清液中一步分离纯化衣壳粒，在病毒样颗粒的制备中具有广阔的应用前景。尽管如此，DWDLRLLY仍存在诸多问题，如疏水性过强等。在后续实验中还需对该多肽以及多肽库中其他多肽进行修饰改造，以期获得具有更高亲和性和特异性的配基。改造方法包括在多肽N端或C端添加1个或多个氨基酸；在多肽内部相邻残基之间添加一个或多个氨基酸；将多肽中某个或某几个残基替换成其他氨基酸等。

Claims (10)

  1. 鼠多瘤病毒衣壳粒的新型亲和肽配基，其特征为：DWDLRLLY、DWDLRLIY、DWNLRLIY、DWFLNLFY、DWSLKLVY、DWSLRLKY和DWNLHLPY。
  2. 权利要求1的鼠多瘤病毒衣壳粒的新型亲和肽配基的设计筛选方法，其特征是依据天然存在的衣壳粒和次要衣壳结构蛋白VP2-C复合物晶体结构，构建衣壳粒的新型肽配基库，特征序列为DWXLXLXY，其中X代表除去半胱氨酸以外的19种氨基酸。
  3. 如权利要求2所述的设计筛选方法，其特征是利用分子动力学模拟/泊松-波尔兹曼溶剂可及表面积计算解析VP2-C与衣壳粒复合物的分子作用机理，确定疏水作用占主导，而VP2-C中对结合起重要贡献的关键残基为V283、P285、D286、W287、L289、L293和Y296。
  4. 如权利要求2所述的设计筛选方法，其特征是多肽库构建依据为VP2-C中5个关键残基：D286、W287、L289、L293和Y296；在肽库的范围内，利用氨基酸定位法构建候选多肽分子库。
  5. 如权利要求2所述的设计筛选方法，其特征是通过分子对接筛选、均方根偏差比较以及分子动力学模拟结合自由能计算，进行鼠多瘤病毒衣壳粒的高亲和性肽配基的筛选。
  6. 如权利要求5所述的设计筛选方法，其特征是利用VINA分子对接软件将肽配基库中的肽配基依次与鼠多瘤病毒衣壳粒进行对接，选取结合自由能低于-6.5kcal/mol的肽配基，共计1158条。
  7. 如权利要求5所述的设计筛选方法，其特征是利用GROMACS分子模拟软件自带的g_rms程序计算VINA对接得到的1158个肽配基与VP2-C中相应的关键残基之间的均方根偏差，选择334个肽配基进行研究。
  8. 如权利要求5所述的设计筛选方法，其特征是根据C末端方向对334个肽配基继续筛选，选取C末端方向与VP2-C一致的227个肽配基进行ROSETTA FlexPepDock对接实验复筛，选取最优的10条肽配基进行MD模拟。
  9. 如权利要求5所述的设计筛选方法，其特征是对筛选得到的10条肽配基与鼠多瘤病毒衣壳粒的复合物进行MD模拟，并利用MM/PBSA方法进行自由能计算和分解，进一步评价肽配基的亲和性和特异性，得到具有较高亲和性的7条肽配基：DWDLRLLY、DWDLRLIY、DWNLRLIY、DWFLNLFY、DWSLKLVY、DWSLRLKY和DWNLHLPY。
  10. 如权利要求2、5所述的设计筛选方法的应用，其特征是所述的多肽库对其修饰改造策略包括：在其N端添加1或多个氨基酸残基；在其C端添加1或多个氨基酸残基；在多肽相邻残基之间添加1或多个氨基酸残基；将多肽中的某一个或某几个残基替换成其他氨基酸残基。
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