基于pose共享的蛋白质-配体构象并行搜索算法

RosettaLigand使用多次启动对接协议的方式对蛋白质-配体复合物构象空间进行采样,在串行或并行的构象搜索实例之间并不共享采样信息。因此并行对接与串行对接相比仅仅是增加了对接的速度,并不能改善对接的性能。我们对Rosetta 3.4版中的RosettaLigand算法进行了修改,在并行的对接实例之间共享采样信息,以实现多个对接实例协同优化采样进程。在一个包含11个目标的测试集合上进行的测试表明,共享采样信息在大多数对接实验中显著地提高了近天然构象在候选结构集合中的比例,同时还降低了整个候选结构集合的平均能量。     

反向虚拟筛选平台及应用

靶标确证是老药新用、药物毒副作用研究的关键。基于分子对接方法 Auto Dock Vina和内部构建的疾病靶标数据库,采用分布式架构,构建了反向虚拟筛选平台。应用该平台对药物吡斯的明进行靶标确证,最终成功找到其靶标乙酰胆碱酯酶,验证了平台的实用性和准确性。     

ATOM 1.0:基于GPU的电子断层重构软件

电子断层成像技术能够在纳米尺度下重构出不具有全同性的细胞或大分子的三维结构,正受到越来越广泛的重视。针对现有电子断层成像技术中重构软件的不足,特别是迭代重构算法速度慢的缺点,我们开发了一款基于Graphic Processor Unit(GPU)平台的电子断层重构软件——ATOM,实现了图像对位、重构参数计算、三维重构及数据可视化等电子断层重构的基本功能。其中,在二维对位方面,ATOM实现了迭代的无标记平移和旋转对位;在三维重构方面,实现了背投影和多种迭代重构算法,并实现了迭代重构在GPU平台上的并行加速,获得了良好的加速比,如SIRT算法得到了47倍加速比。ATOM是绿色开源软件,可以运行在支持Qt和CUDA的所有操作系统上。ATOM为图形界面软件,结合详尽的安装及使用文档,便于用户使用。     

蛋白质-配体柔性对接综述

蛋白质与配体的相互作用在药物发现与筛选、功能食品开发等方面,都具有重要的科学意义。研究蛋白质-配体对接的目的在于通过已知配体和目标蛋白质的三维结构,运用计算手段来预测和评估蛋白质-配体复合物的三维构象,从而更好地理解蛋白质-配体之间的相互作用。随着已解析蛋白质单体结构的数量和计算能力的不断增加,蛋白质-配体对接也越来越现实并可靠。作者对蛋白质-配体柔性对接过程中所涉及的蛋白质的柔性、配体的准备、构象空间的采样方法、打分函数及其后期处理等方面进行了综述。     

GPU机群系统上加速EMAN(英文)

近年来,高质量的三维重构对计算机系统的计算能力提出越来越高的需求。EMAN是对冷冻电子显微镜拍摄出来的图像进行单颗粒三维重构的流行软件包。由于GPU显示出优于CPU的性能水平,在GPU机群系统上对EMAN进行加速将有可能取得较好的效果。首先,有必要调查EMAN在计算方面的特点,包括计算密度,访存情况和并行潜力。结果显示其在GPU体系结构上有获得较高性能的潜力。然后,根据此特点完成一款并行EMAN软件,使用CUDA和MPI对EMAN实施不同粒度的并行处理。在一个拥有16颗Intel6核处理器的机群系统上,用8颗FermiGPU加速后的EMAN(CUDA-EMAN)相比于仅使用CPU的并行EMAN程序获得了2.5倍的加速比,也就是1颗FermiGPU相比一个Intel6核处理器可对EMAN加速5倍。     

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.     

计算机虚拟筛选技术在害虫行为调节剂研究中的应用

害虫行为调节剂是一种以嗅觉系统为靶标的绿色农药,在害虫的田间管理中发挥着重要的作用。然而,其先导化合物的发现通常依赖一系列生物测定的方法,不仅费时费力,且发现效率低。近年来,随着昆虫嗅觉功能数据的积累和结构生物学的飞速发展,以机器学习技术和分子对接为代表的2种基于计算机的药物虚拟筛选方法在害虫行为调节剂的先导化合物研究中发挥着重要的作用,极大地促进了先导化合物的发现效率,减少了筛选的盲目性。本文系统综述了2种虚拟筛选方法及其在害虫行为调节剂先导化合物研究中的应用,并对2种筛选策略在实际应用中存在的问题及应用前景进行了讨论。     

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。     

药物靶标配体高通量筛选的亲和质谱技术研究

疾病相关的药物靶标蛋白与小分子化合物的亲和作用研究是当今新药研发的热点领域,基于靶蛋白与配体亲和作用的筛选技术已成为与基于靶蛋白活性高通量筛选技术高度互补的药物先导化合物发现关键技术。本文综述了亲和质谱技术用于筛选和检测指定靶蛋白的小分子配体的基本原理和主要优势,详细介绍了该技术应用于大规模化合物库筛选、分子片段库筛选、天然产物粗提物筛选和蛋白质与胞内代谢物相互作用研究领域的主要进展。     

RGD三肽的潜在作用靶标预测与计算机模拟分析

化学基因组技术是药物作用靶标确认、药物分子在通路中的作用的确证等方面有重要应用,可为新药研发和老药新用提供理论依据,并可降低药物发现中的高额成本.精氨酸-甘氨酸-天冬氨酸(RGD)三肽被证明是与细胞粘附受体特异性结合的特征序列,在生理学上扮演者重要角色.本研究利用化学基因组学中的其中一种方法即基于反向对接和药效团反向匹配搜索技术来研究RGD三肽的潜在作用靶标,并进行计算机模拟分析.反向匹配搜索结果发现计算得到的关键性靶标及其涉及的相关疾病与实验报道的RGD的药理活性相吻合,包括具有抗凝血、抗肿瘤作用,与肾及心血管作用有关等,而且还发现RGD可能是一个潜在的神经氨酸酶的抑制剂.     

Normal-mode-analysis-monitored energy minimization procedure for generating small-molecule bound conformations

The energy minimization of a small molecule alone does not automatically stop at a local minimum of the potential energy surface of the molecule if the minimum is shallow, thus leading to folding of the molecule and consequently hampering the generation of the bound conformation of a guest in the absence of its host. This questions the practicality of virtual screening methods that use conformations at local minima of their potential energy surfaces (local minimum conformations) as potential bound conformations. Here we report a normal-mode-analysis-monitored energy minimization (NEM) procedure that generates local minimum conformations as potential bound conformations. Of 22 selected guest-host complex crystal structures with guest structures possessing up to four rotatable bonds, all complexes were reproduced, with guest mass-weighted root mean square deviations of <1.0 A, through docking with the NEM-generated guest local minimum conformations. An analysis of the potential energies of these local minimum conformations showed that 22 (100%), 18 (82%), 16 (73%), and 12 (55%) of the 22 guest bound conformations in the crystal structures had conformational strain energies of less than or equal to 3.8, 2.0, 0.6, and 0.0 kcal/mol, respectively. These results suggest that (1) the NEM procedure can generate small-molecule bound conformations, and (2) guests adopt low-strain-energy conformations for complexation, thus supporting the virtual screening methods that use local minimum conformations.     

High-Performance Drug Discovery: Computational Screening by Combining Docking and Molecular Dynamics Simulations

Virtual compound screening using molecular docking is widely used in the discovery of new lead compounds for drug design. However, this method is not completely reliable and therefore unsatisfactory. In this study, we used massive molecular dynamics simulations of protein-ligand conformations obtained by molecular docking in order to improve the enrichment performance of molecular docking. Our screening approach employed the molecular mechanics/Poisson-Boltzmann and surface area method to estimate the binding free energies. For the top-ranking 1,000 compounds obtained by docking to a target protein, approximately 6,000 molecular dynamics simulations were performed using multiple docking poses in about a week. As a result, the enrichment performance of the top 100 compounds by our approach was improved by 1.6–4.0 times that of the enrichment performance of molecular dockings. This result indicates that the application of molecular dynamics simulations to virtual screening for lead discovery is both effective and practical. However, further optimization of the computational protocols is required for screening various target proteins.     

F2Dock: fast Fourier protein-protein docking

The functions of proteins are often realized through their mutual interactions. Determining a relative transformation for a pair of proteins and their conformations which form a stable complex, reproducible in nature, is known as docking. It is an important step in drug design, structure determination, and understanding function and structure relationships. In this paper, we extend our nonuniform fast Fourier transform-based docking algorithm to include an adaptive search phase (both translational and rotational) and thereby speed up its execution. We have also implemented a multithreaded version of the adaptive docking algorithm for even faster execution on multicore machines. We call this protein-protein docking code F2Dock (F2 = Fast Fourier). We have calibrated F2Dock based on an extensive experimental study on a list of benchmark complexes and conclude that F2Dock works very well in practice. Though all docking results reported in this paper use shape complementarity and Coulombic-potential-based scores only, F2Dock is structured to incorporate Lennard-Jones potential and reranking docking solutions based on desolvation energy .     

How to choose relevant multiple receptor conformations for virtual screening: a test case of Cdk2 and normal mode analysis

Better treatment of protein flexibility is essential in structure-based drug design projects such as virtual screening and protein-ligand docking. Diversity in ligand-binding mechanisms and receptor conformational changes makes it difficult to treat dynamic features of the receptor during the docking simulation. Thus, the use of pregenerated multiple receptor conformations is applied today in virtual screening studies. However, generation of a small relevant set of receptor conformations remains challenging. To address this problem, we propose a new protocol for the generation of multiple receptor conformations via normal mode analysis and for the selection of several receptor conformations suitable for docking/virtual screening. We validated this protocol on cyclin-dependent kinase 2, which possesses a binding site located at the interface between two subdomains and is known to undergo significant conformational changes in the active site region upon ligand binding. We believe that the suggested rules for the choice of suitable receptor conformations can be applied to other targets when dealing with in silico screening on flexible receptors.     

Structural adaptation of extreme halophilic proteins through decrease of conserved hydrophobic contact surface

Background

Disrupting protein-protein interactions by small organic molecules is nowadays a promising strategy employed to block protein targets involved in different pathologies. However, structural changes occurring at the binding interfaces make difficult drug discovery processes using structure-based drug design/virtual screening approaches. Here we focused on two homologous calcium binding proteins, calmodulin and human centrin 2, involved in different cellular functions via protein-protein interactions, and known to undergo important conformational changes upon ligand binding.

Results

In order to find suitable protein conformations of calmodulin and centrin for further structure-based drug design/virtual screening, we performed in silico structural/energetic analysis and molecular docking of terphenyl (a mimicking alpha-helical molecule known to inhibit protein-protein interactions of calmodulin) into X-ray and NMR ensembles of calmodulin and centrin. We employed several scoring methods in order to find the best protein conformations. Our results show that docking on NMR structures of calmodulin and centrin can be very helpful to take into account conformational changes occurring at protein-protein interfaces.

Conclusions

NMR structures of protein-protein complexes nowadays available could efficiently be exploited for further structure-based drug design/virtual screening processes employed to design small molecule inhibitors of protein-protein interactions.     

Small molecule induction of MSH2-dependent cell death suggests a vital role of mismatch repair proteins in cell death

Avoidance of apoptosis is one of the hallmarks of cancer development and progression. Chemotherapeutic agents aim to initiate an apoptotic response, but often fail due to dysregulation. MSH proteins are capable of recognizing cisplatin damage in DNA and participate in the initiation of cell death. We have exploited this recognition and computationally simulated a MutS homolog (MSH) "death conformation". Screening and docking experiments based on this model determined that the MSH2-dependent cell-death pathway can be induced by a small molecule without DNA damage, reserpine. Reserpine was identified via virtual screening on structures obtained from molecular dynamics as a small molecule that selectively binds a protein "death" conformation. The virtual screening predicts that this small molecule binds in the absence of DNA. Cell biology confirmed that reserpine triggers the MSH2-dependent cell-death pathway. This result supports the hypothesis that the MSH2-dependent pathway is initiated by specific protein conformational changes triggered by binding to either DNA damage or small compound molecules. These findings have multiple implications for drug discovery and cell biology. Computational modeling may be used to identify and eventually design small molecules that selectively activate particular pathways through conformational control. Molecular dynamics simulations can be used to model the biologically relevant conformations and virtual screening can then be used to select for small molecules that bind specific conformations. The ability of a small molecule to induce the cell-death pathway suggests a broader role for MMR proteins in cellular events, such as cell-death pathways, than previously suspected.     

Protein docking using spherical polar Fourier correlations

We present a new computational method of docking pairs of proteins by using spherical polar Fourier correlations to accelerate the search for candidate low-energy conformations. Interaction energies are estimated using a hydrophobic excluded volume model derived from the notion of "overlapping surface skins," augmented by a rigorous but "soft" model of electrostatic complementarity. This approach has several advantages over former three-dimensional grid-based fast Fourier transform (FFT) docking correlation methods even though there is no analogue to the FFT in a spherical polar representation. For example, a complete search over all six rigid-body degrees of freedom can be performed by rotating and translating only the initial expansion coefficients, many unfeasible orientations may be eliminated rapidly using only low-resolution terms, and the correlations are easily localized around known binding epitopes when this knowledge is available. Typical execution times on a single processor workstation range from 2 hours for a global search (5 x 10(8) trial orientations) to a few minutes for a local search (over 6 x 10(7) orientations). The method is illustrated with several domain dimer and enzyme-inhibitor complexes and 20 large antibody-antigen complexes, using both the bound and (when available) unbound subunits. The correct conformation of the complex is frequently identified when docking bound subunits, and a good docking orientation is ranked within the top 20 in 11 out of 18 cases when starting from unbound subunits. Proteins 2000;39:178-194.     

Emerging frontiers in virtual drug discovery: From quantum mechanical methods to deep learning approaches

Virtual screening-based approaches to discover initial hit and lead compounds have the potential to reduce both the cost and time of early drug discovery stages, as well as to find inhibitors for even challenging target sites such as protein–protein interfaces. Here in this review, we provide an overview of the progress that has been made in virtual screening methodology and technology on multiple fronts in recent years. The advent of ultra-large virtual screens, in which hundreds of millions to billions of compounds are screened, has proven to be a powerful approach to discover highly potent hit compounds. However, these developments are just the tip of the iceberg, with new technologies and methods emerging to propel the field forward. Examples include novel machine-learning approaches, which can reduce the computational costs of virtual screening dramatically, while progress in quantum-mechanical approaches can increase the accuracy of predictions of various small molecule properties.     

Effects of initial settings on computational protein–ligand docking accuracies for several docking programs

In this study, the influences of initial settings, i.e. initial conformations, configurations and docking parameters, on docking results were investigated. The conformations used in the study were generated by the CAMDAS program. After the conformational search calculations, five structures were selected from the conformer groups according to their conformation energies and root mean square deviations against crystal structures; for example, the lowest energy conformer, as well as the closest and farthest conformers to the crystal structure, was retrieved. Several docking parameter settings were used (default, high speed, generating 50 poses). In this study, docking calculations were conducted using the GOLD, eHiTS, AutoDock, AutoDock vina, FRED and DOCK programs. The success rates of GOLD, eHiTS and FRED were better than those of AutoDock, AutoDock vina and DOCK. The docking results using the farthest conformations were worse than those obtained using other conformations, indicating that some conformation search for the ligand molecule should be performed before the docking calculations.     

A fast protein-ligand docking algorithm based on hydrogen bond matching and surface shape complementarity

With the rapid development of structural determination of target proteins for human diseases, high throughout virtual screening based drug discovery is gaining popularity gradually. In this paper, a fast docking algorithm (H-DOCK) based on hydrogen bond matching and surface shape complementarity was developed. In H-DOCK, firstly a divide-and-conquer strategy based enumeration approach is applied to rank the intermolecular modes between protein and ligand by maximizing their hydrogen bonds matching, then each docked conformation of the ligand is calculated according to the matched hydrogen bonding geometry, finally a simple but effective scoring function reflecting mainly the van der Waals interaction is used to evaluate the docked conformations of the ligand. H-DOCK is tested for rigid ligand docking and flexible one, the latter is implemented by repeating rigid docking for multiple conformations of a small molecule and ranking all together. For rigid ligands, H-DOCK was tested on a set of 271 complexes where there is at least one intermolecular hydrogen bond, and H-DOCK achieved success rate (RMSD<2.0?Å) of 91.1%. For flexible ligands, H-DOCK was tested on another set of 93 complexes, where each case was a conformation ensemble containing native ligand conformation as well as 100 decoy ones generated by AutoDock [1], and the success rate reached 81.7%. The high success rate of H-DOCK indicates that the hydrogen bonding and steric hindrance can grasp the key interaction between protein and ligand. H-DOCK is quite efficient compared with the conventional docking algorithms, and it takes only about 0.14 seconds for a rigid ligand docking and about 8.25 seconds for a flexible one on average. According to the preliminary docking results, it implies that H-DOCK can be potentially used for large scale virtual screening as a pre-filter for a more accurate but less efficient docking algorithm.