蛋白质复合物结构预测的集成分子对接方法

蛋白质分子间相互作用与识别是当前生命科学研究的热点,分子对接方法是研究这一问题的有效手段．为了推进分子对接方法的发展,欧洲生物信息学中心组织了国际蛋白质复合物结构预测（CAPRI）竞赛．通过参加CAPRI竞赛,逐步摸索出了一套用于蛋白质复合物结构预测的集成蛋白质一蛋白质分子对接方法HoDock,它包括结合位点预测、初始复合物结构采集、精细复合物结构采集、结构成簇和打分排序以及最终复合物结构挑选等主要步骤．本文以最近的CAPRI Target 39为例,具体说明该方法的主要步骤和应用．该方法在CAPRI Target 39竞赛中取得了比较好的结果,预测结构Model 10是所有参赛小组提交的366个结构中仅有的3个正确结构之一,其配体均方根偏差（L_Rmsd）为0．25nm．在对接过程中,首先用理论预测和实验信息相结合的方法来寻找蛋白质结合位点残基,确认CAPRI Target 39A链的A31TRP和A191HIS,B链的B512ARG和B531ARG为可能结合位点残基．同时,用ZDock程序做不依赖结合位点的初步全局刚性对接．然后,根据结合位点信息进行初步局部刚性对接,从全局和局部对接中挑出了11个初始对接复合物结构．进而,用改进的Rosetta Dock程序做精细位置约束对接,并对每组对接中打分排序前200的结构进行成簇聚类．最后,综合分析打分、成簇和结合位点三方面的信息,得到10个蛋白质复合物结构．竞赛结果表明,A191HIS,B512ARG和B531ARG三个结合位点残基预测正确,提交的10个蛋白质复合物结构中有5个复合物受体一配体界面残基预测成功率较高．与其他参赛小组的对接结果比较,表明HoDock方法具有一定优势．这些结果说明我们提出的集成分子对接方法有助于提高蛋白质复合物结构预测的准确率．     

蛋白质复合物结合自由能的预测

本文发展了一种合理的经验能量函数和结合自由能算法,并应用到２１个蛋白质复合物的结合自由能预测上。与现今发表的其他工作相比,我们的结果与实验的测定值符合得更好,平均预测精度为１．０ｋｃａｌ／ｍｏｌ,与实验值的相关达到９６％。应用本方法预测一个典型的蛋白质与其抑制剂复合物的结合自由能,在ＳＧＩ－ＩＭＰＡＣＴ Ｒ１００００工作站上约需２分钟。本文的结果还证实,与对蛋白折叠过程的认识不同,亲水原子在蛋白质     

蛋白质-蛋白质分子对接方法研究进展

蛋白质分子间相互作用与识别是21世纪生命科学研究的前沿和热点.分子对接方法是研究这一课题有效的计算机模拟手段.通常,蛋白质-蛋白质分子对接包括四个阶段:搜索受体与配体分子间的结合模式,过滤对接结构以排除不合理的结合模式,优化结构,用精细的打分函数评价、排序对接模式并挑选近天然构象.结合国内外研究蛋白质-蛋白质分子对接方法进展和本研究小组的工作,对以上四个环节做了详细的综述.另外,还分析了目前存在的主要问题,并提出对未来工作的展望.     

蛋白质柔性复合物的结构预测

将自洽系综最优化方法（ＳＣＥＯ）推广到主链可变的分子体系,并以此来实现蛋白质复合物结合界面的柔性优化。据此,提出了一种模拟蛋白质“诱导契合”过程的计算方法,来实现蛋白质柔性复合物的结构预测。经过三个蛋白质柔性复合物结构预测的检验,表明这种方法是可行的,并且达到了计算精度和计算速度上的兼顾     

蛋白质-蛋白质分子对接方法中分子柔性处理与近天然结构筛选的研究

蛋白质-蛋白质分子对接方法是研究蛋白质分子间相互作用与识别的重要理论方法。该方法主要涉及复合物结合模式的构象搜索和近天然结构的筛选两个问题。在构象搜索中,分子柔性的处理是重点也是难点,围绕这一问题,近年来提出了许多新的方法。针对近天然结构的筛选问题,目前主要采用三种解决策略:结合位点信息的利用、相似结构的聚类和打分函数对结构的评价。本文围绕以上问题,就国内外研究进展和本研究小组的工作作详细的综述,并对进一步的研究方向进行了展望。     

引入显式水分子对接提高蛋白质配体复合物结构的预测精度

在蛋白质复合物界面一般都会存在着一定量的水分子,这些水分子通过空间占据和氢键方式影响蛋白质与配体的位置关系。应用现有的计算机方法研究蛋白质-配体对接时,一般不会显式地考虑水分子的作用。本文显式地将水分子引入蛋白质-配体对接过程,考虑水分子空间占据和氢键能量对复合物对接结构的影响,提出了一种包含水分子的蛋白质-配体对接算法。实验结果表明引入水分子使蛋白质-配体对接质量有明显提高。     

蛋白质与极性配体复合物的绝对结合自由能计算

介绍了用分子动力学模拟与热力学积分法相结合,模拟蛋白质与配体的绝对结合自由能的方法.通过分子转换法,使蛋白质分子（包括水分子）与配体小分子之间的相互作用逐渐减弱 （或增强）至完全消失（或完全出现）. 运用体约束方法,计算了配体与受体结合后平动、转动自由度的丧失即熵效应所引起的自由能变化.以胰蛋白酶双突变体（D189G/G226D）与极性配体苯甲脒为例,研究了蛋白质活性部位与极性配体的相互作用对结合自由能的影响,该复合物绝对结合自由能的模拟结果(－15.5 kJ/mol)与实验值(－10.5 kJ/mol)相近.     

蛋白质与类药分子的柔性对接

本文利用“禁忌搜索”算法和Ｇｅｈｌｈａａｒ简化能量势函数实现蛋白质与类药分子之间的柔性对接。对包含１００个复合物的检验集进行了计算检验,得到了满意的结果,８９％预测复合物结构的误差小于０．２５ｎｍ。与利用遗传算法进行柔性对接的ＧＯＬＤ程序相比,本方法的成功率高,局限性小,计算时间也短。     

蛋白质- 核酸对接方法研究进展

分子对接技术作为预测蛋白质-核酸复合物结构的有效方法,为研究在生物学过程中蛋白质-核酸的相互作用提供了重要的工具。本文首先分析了当前蛋白质-核酸对接研究中的主要困难,例如构象变化和核糖磷酸骨架的带电性问题。然后从构象搜索、打分函数、柔性策略三个方面比较和总结了蛋白质-核酸对接中主要的计算方法。最后回顾了蛋白质-核酸对接计算模型的应用,并对未来的工作进行了展望。     

蛋白质-蛋白质对接中打分函数的研究

通过分析蛋白质－蛋白质间的静电、疏水作用和熵效应与相对于晶体结构的蛋白质主链原子的均方根偏差（RMSD）的相关性,定量地考查了它们在蛋白质－蛋白质对接中作为打分函数评价近天然构象的能力。对7个蛋白质复合物体系的分析表明,就水化能而言,原子接触势模型（ACE）优于原子水化参数模型（ASP）,且修正的ACE模型具有更好的评价近天然构象的能力;水化能与静电能结合对评价能力有进一步的提高。最后,我们将静电和修正的ACE水化能结合作为打分函数用于36个蛋白质复合物体系的对接研究,进一步证实了这两种能量项的组合能有效地将近天然结构从分子对接模式中区分出来。     

Geometric Recognition as a Tool for Predicting Structures of Molecular Complexes

Summary The structures of two binary complexes (the TEM-1/BLIP complex and the trypsin/amiloride complex) were predicted prior to their experimental determination and compared to the corresponding experimental structures when these became available. In both predictions the rigid-body geometric docking algorithm ranked the correct solution among the top ones. Additional information concerning the structure and chemical character of the binding site of one of the molecules in the complex was used to single out the correct solution. The results indicate that the combination of geometric surface matching with biochemical information produces a useful tool for structure prediction.     

Geometric Recognition as a Tool for Predicting Structures of Molecular Complexes

The structures of two binary complexes (the TEM-1/BLIP complex and the trypsin/amiloride complex) were predicted prior to their experimental determination and compared to the corresponding experimental structures when these became available. In both predictions the rigid-body geometric docking algorithm ranked the correct solution among the top ones. Additional information concerning the structure and chemical character of the binding site of one of the molecules in the complex was used to single out the correct solution. The results indicate that the combination of geometric surface matching with biochemical information produces a useful tool for structure prediction.     

Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations

Protein-protein docking algorithms provide a means to elucidate structural details for presently unknown complexes. Here, we present and evaluate a new method to predict protein-protein complexes from the coordinates of the unbound monomer components. The method employs a low-resolution, rigid-body, Monte Carlo search followed by simultaneous optimization of backbone displacement and side-chain conformations using Monte Carlo minimization. Up to 10(5) independent simulations are carried out, and the resulting "decoys" are ranked using an energy function dominated by van der Waals interactions, an implicit solvation model, and an orientation-dependent hydrogen bonding potential. Top-ranking decoys are clustered to select the final predictions. Small-perturbation studies reveal the formation of binding funnels in 42 of 54 cases using coordinates derived from the bound complexes and in 32 of 54 cases using independently determined coordinates of one or both monomers. Experimental binding affinities correlate with the calculated score function and explain the predictive success or failure of many targets. Global searches using one or both unbound components predict at least 25% of the native residue-residue contacts in 28 of the 32 cases where binding funnels exist. The results suggest that the method may soon be useful for generating models of biologically important complexes from the structures of the isolated components, but they also highlight the challenges that must be met to achieve consistent and accurate prediction of protein-protein interactions.     

Protein-protein interactions: hot spots and structurally conserved residues often locate in complemented pockets that pre-organized in the unbound states: implications for docking

Energetic hot spots account for a significant portion of the total binding free energy and correlate with structurally conserved interface residues. Here, we map experimentally determined hot spots and structurally conserved residues to investigate their geometrical organization. Unfilled pockets are pockets that remain unfilled after protein-protein complexation, while complemented pockets are pockets that disappear upon binding, representing tightly fit regions. We find that structurally conserved residues and energetic hot spots are strongly favored to be located in complemented pockets, and are disfavored in unfilled pockets. For the three available protein-protein complexes with complemented pockets where both members of the complex were alanine-scanned, 62% of all hot spots (DeltaDeltaG>2kcal/mol) are within these pockets, and 60% of the residues in the complemented pockets are hot spots. 93% of all red-hot residues (DeltaDeltaG>/=4kcal/mol) either protrude into or are located in complemented pockets. The occurrence of hot spots and conserved residues in complemented pockets highlights the role of local tight packing in protein associations, and rationalizes their energetic contribution and conservation. Complemented pockets and their corresponding protruding residues emerge among the most important geometric features in protein-protein interactions. By screening the solvent, this organization shields backbone hydrogen bonds and charge-charge interactions. Complemented pockets often pre-exist binding. For 18 protein-protein complexes with complemented pockets whose unbound structures are available, in 16 the pockets are identified to pre-exist in the unbound structures. The root-mean-squared deviations of the atoms lining the pockets between the bound and unbound states is as small as 0.9A, suggesting that such pockets constitute features of the populated native state that may be used in docking.     

Insights into protein-protein binding by binding free energy calculation and free energy decomposition for the Ras-Raf and Ras-RalGDS complexes

Absolute binding free energy calculations and free energy decompositions are presented for the protein-protein complexes H-Ras/C-Raf1 and H-Ras/RalGDS. Ras is a central switch in the regulation of cell proliferation and differentiation. In our study, we investigate the capability of the molecular mechanics (MM)-generalized Born surface area (GBSA) approach to estimate absolute binding free energies for the protein-protein complexes. Averaging gas-phase energies, solvation free energies, and entropic contributions over snapshots extracted from trajectories of the unbound proteins and the complexes, calculated binding free energies (Ras-Raf: -15.0(+/-6.3)kcal mol(-1); Ras-RalGDS: -19.5(+/-5.9)kcal mol(-1)) are in fair agreement with experimentally determined values (-9.6 kcal mol(-1); -8.4 kcal mol(-1)), if appropriate ionic strength is taken into account. Structural determinants of the binding affinity of Ras-Raf and Ras-RalGDS are identified by means of free energy decomposition. For the first time, computationally inexpensive generalized Born (GB) calculations are applied in this context to partition solvation free energies along with gas-phase energies between residues of both binding partners. For selected residues, in addition, entropic contributions are estimated by classical statistical mechanics. Comparison of the decomposition results with experimentally determined binding free energy differences for alanine mutants of interface residues yielded correlations with r(2)=0.55 and 0.46 for Ras-Raf and Ras-RalGDS, respectively. Extension of the decomposition reveals residues as far apart as 25A from the binding epitope that can contribute significantly to binding free energy. These "hotspots" are found to show large atomic fluctuations in the unbound proteins, indicating that they reside in structurally less stable regions. Furthermore, hotspot residues experience a significantly larger-than-average decrease in local fluctuations upon complex formation. Finally, by calculating a pair-wise decomposition of interactions, interaction pathways originating in the binding epitope of Raf are found that protrude through the protein structure towards the loop L1. This explains the finding of a conformational change in this region upon complex formation with Ras, and it may trigger a larger structural change in Raf, which is considered to be necessary for activation of the effector by Ras.     

The relationship between the flexibility of proteins and their conformational states on forming protein-protein complexes with an application to protein-protein docking

We investigate the extent to which the conformational fluctuations of proteins in solution reflect the conformational changes that they undergo when they form binary protein-protein complexes. To do this, we study a set of 41 proteins that form such complexes and whose three-dimensional structures are known, both bound in the complex and unbound. We carry out molecular dynamics simulations of each protein, starting from the unbound structure, and analyze the resulting conformational fluctuations in trajectories of 5 ns in length, comparing with the structure in the complex. It is found that fluctuations take some parts of the molecules into regions of conformational space close to the bound state (or give information about it), but at no point in the simulation does each protein as whole sample the complete bound state. Subsequent use of conformations from a clustered MD ensemble in rigid-body docking is nevertheless partially successful when compared to docking the unbound conformations, as long as the unbound conformations are themselves included with the MD conformations and the whole globally rescored. For one key example where sub-domain motion is present, a ribonuclease inhibitor, principal components analysis of the MD was applied and was also able to produce conformations for docking that gave enhanced results compared to the unbound. The most significant finding is that core interface residues show a tendency to be less mobile (by size of fluctuation or entropy) than the rest of the surface even when the other binding partner is absent, and conversely the peripheral interface residues are more mobile. This surprising result, consistent across up to 40 of the 41 proteins, suggests different roles for these regions in protein recognition and binding, and suggests ways that docking algorithms could be improved by treating these regions differently in the docking process.     

A holistic molecular docking approach for predicting protein-protein complex structure

A holistic protein-protein molecular docking approach, HoDock, was established, composed of such steps as binding site prediction, initial complex structure sampling, refined complex structure sampling, structure clustering, scoring and final structure selection. This article explains the detailed steps and applications for CAPRI Target 39. The CAPRI result showed that three predicted binding site residues, A191HIS, B512ARG and B531ARG, were correct, and there were five submitted structures with a high fraction of correct receptor-ligand interface residues, indicating that this docking approach may improve prediction accuracy for protein-protein complex structures.     

Docking study and free energy simulation of the complex between p53 DNA-binding domain and azurin

Molecular interaction between p53 tumor suppressor and the copper protein azurin (AZ) has been demonstrated to enhance p53 stability and hence antitumoral function, opening new perspectives in cancer treatment. While some experimental work has provided evidence for AZ binding to p53, no crystal structure for the p53-AZ complex was solved thus far. In this work the association between AZ and the p53 DNA-binding domain (DBD) was investigated by computational methods. Using a combination of rigid-body protein docking, experimental mutagenesis information, and cluster analysis 10 main p53 DBD-AZ binding modes were generated. The resulting structures were further characterized by molecular dynamics (MD) simulations and free energy calculations. We found that the highest scored docking conformation for the p53 DBD-AZ complex also yielded the most favorable free energy value. This best three-dimensional model for the complex was validated by using a computational mutagenesis strategy. In this structure AZ binds to the flexible L(1) and s(7)-s(8) loops of the p53 DBD and stabilizes them through protein-protein tight packing interactions, resulting in high degree of both surface matching and electrostatic complementarity.     

FRET技术及其在蛋白质-蛋白质分子相互作用研究中的应用

简要综述了FRET方法在活细胞生理条件下研究蛋白质-蛋白质间相互作用方面的最新进展.蛋白质-蛋白质间相互作用在整个细胞生命过程中占有重要地位,由于细胞内各种组分极其复杂,因此一些传统研究蛋白质-蛋白质间相互作用的方法,例如酵母双杂交、免疫沉淀等可能会丢失某些重要的信息,无法正确地反映在当时活细胞生理条件下蛋白质-蛋白质间相互作用的动态变化过程.荧光共振能量转移（fluorescence resonance energy transfer, FRET）是近来发展的一项新技术,此项技术的应用,为在活细胞生理条件下对蛋白质-蛋白质间相互作用进行实时的动态研究,提供一个非常便利的条件.