量子粒子群优化智能算法的高精度分子对接方法研究

分子对接是药物发现与设计的重要方法,采用计算机优化和模式识别方法在三维结构数据库中搜索几何、化学特性与特定药物结合位点相匹配分子的计算机辅助药物筛选是当前分子对接的研究热点,这种问题可以归为参数优化问题。本文提出了一种基于改进的量子粒子群(quantum-behaved particle swarm optimization,QPSO)算法的分子对接方法,用于处理大自由度的分子对接计算,并与基于标准QPSO算法和经典拉马克遗传算法的分子对接方法进行了比较,实验结果表明新方法无论是在对接能量还是对接准确性上,明显优于其它2种方法,尤其是在配体复杂性不断增加的情况下,非常适用于高柔性分子对接问题。     

An application of algebraic topology to solid modeling in molecular biology

A recurring problem in solid modeling, computer graphics, and molecular modeling is the computation of the intersection of two objects. A general solution to this problem is obtained by applying two ideas of algebraic topology: (1) a chain complex, and (2) a boundary formula for the intersection of two objects. A general data structure for a chain complex made up of piecewise polynomial cells is described, as are algorithms for connectivity, containment and intersection. The basic ideas of this work are abstract, topological, and for the most part, independent of the shape and dimensionality of the objects. An application to structural molecular biology is presented. The application identifies convex and concave features of protein surfaces.     

Exploiting multilevel parallelism on a many-core system for the application of hyperheuristics to a molecular docking problem

The solution of Protein–Ligand Docking Problems can be approached through metaheuristics, and satisfactory metaheuristics can be obtained with hyperheuristics searching in the space of metaheuristics implemented inside a parameterized schema. These hyperheuristics apply several metaheuristics, resulting in high computational costs. To reduce execution times, a shared-memory schema of hyperheuristics is used with four levels of parallelism, two for the hyperheuristic and two for the metaheuristics. The parallel schema is executed in a many-core system in “native mode,” and the four-level parallelism allows us to take full advantage of the massive parallelism offered by this architecture and obtain satisfactory fitness and an important reduction in the execution time.     

基于演化设计的遗传算法在分子对接中的应用

将自然界的物种动态模型引入到遗传算法当中,反映出物种的真实进化状态,开发了基于演化设计的遗传算法。算法采用自适应策略克服了确定交叉和变异概率值的问题,利用小种群策略和最优保留策略保证了种群的多样性,改善了算法的寻优能力,进而提高了计算效率。运用该遗传算法求解分子对接优化模型,给出基于演化设计的分子对接程序。对接实例表明,算法能有效应用于分子对接问题中。     

Homology modeling and molecular docking studies of Drosophila and Aedes sex peptide receptors

The Drosophila melanogaster sex peptide receptor (DrmSPR), which is a G protein-coupled receptor (GPCR), is known as the specific receptor for sex peptide (SP). It is responsible for the reproductive behavior in the Drosophila model system; in particular, it is involved in the post-mating responses such as the increase in egg-laying ability and decrease in receptivity in females. In a previous study, we discovered a small molecule agonist of DrmSPR for the first time, which could not, however, activate Aedes aegypti SPR (AedesSPR). To investigate the binding mechanism of the small molecule agonist of DrmSPR, the ensemble structures of low-lying packing structures of DrmSPR and AedesSPR were assembled using the GEnSeMBLE (GPCR Ensemble of Structures in Membrane BiLayer Environment) method. The generated homology models exhibited the typical pattern of inter-helical interactions of the class A GPCRs. The docking experiments of the small molecule agonist suggest that Tyr^5.35 and Phe^2.67 residues may be involved in a hydrophobic interaction and that Ser^3.25 forms a hydrogen bond with the agonist. Additionally, we found that the docking results were consistent with the experimental data of the reference compounds with variable agonistic activities. Moreover, a potential distinction of the putative binding sites in two GPCR models of DrmSPR and AedesSPR, which was determined in this study, can explain the selective action of the agonist for DrmSPR but not for AedesSPR.     

Adaptive molecular docking method based on information entropy genetic algorithm

Almost all the molecule docking models, using by widespread docking software, are approximate. Approximation will make the scoring function inaccurate under some circumstances. This study proposed a new molecule docking scoring method: based on force-field scoring function, it use information entropy genetic algorithm to solve the docking problem. Empirical-based and knowledge-based scoring function are also considered in this method. Instead of simple combination with fixed weights, coefficients of each factor are adaptive in the process of searching optimum solution. Genetic algorithm with the multi-population evolution and entropy-based searching technique with narrowing down space is used to solve the optimization model for molecular docking problem. To evaluate this method, we carried out a numerical experiment with 134 protein–ligand complexes of the publicly available GOLD test set. The results show that this study improved the docking accuracy over the individual force-field scoring greatly. Comparing with other popular docking software, it has the best average Root-Mean-Square Deviation (RMSD). The average computing time of this study is also good among them.     

tPSODock:基于化学得分函数和两层粒子群算法的计算机分子对接程序

药物分子对接是计算机辅助药物设计的主要方法之一。利用化学得分函数(Chemscor)作为能量函数,以及将一种新的优化算法一两层粒子群算法作为搜索算法,得到了一种新的计算机分子对接程序：tPSODock。利用tPSODock计算了100个蛋白质一配体的复合物,并且与Consdock和Autodock3．0计算结果进行了对比,结果显示88％的计算结果RMSD小于2．0A,优于Consdock以及Autodock的计算结果。说明tPSODock在是一种高效的分子对接软件,可以用于大规模数据库的筛选工作,适合新药的开发和研制。     

A homology modeling method of an icosahedral viral capsid: inclusion of surrounding protein structures

A methodological development is presented for homology modeling of an icosahedrally symmetric assembly of proteins. In the method, a main-chain structure of an asymmetric unit of a protein assembly is constructed and structure refinement is performed, taking the surrounding symmetry-related proteins into consideration with rotational symmetry boundary conditions. To test the procedure, three models of a poliovirus capsid were constructed with different modeling conditions based on the X-ray structure of a rhinovirus capsid. Model S and model N were constructed with and without considering surrounding proteins, respectively. Model N2 was obtained by refinement in rotational symmetry boundary conditions of the structure of model N. The three models were compared with the X-ray structure of a poliovirus capsid. Root mean square deviations and C alpha distances indicate that model S is the most accurate. Examination of the intermolecular short contacts indicates that model S and model N2 are superior to model N, because they do not make severe intermolecular short contacts. Symmetric intermolecular interactions are important for both the structural fragment search and energy minimization to predict better loop structures. The programs developed in this study are thus valuable in homology modeling of an icosahedral viral capsid.     

模型驱动的产品应用服务建模方法

为了将应用服务需求转换成模型,最终指导和实现产品应用服务系统的快速构建,提出一种模型驱动的产品应用服务建模方法。在元对象机制的元模型层建立可拓物元形式化描述与面向对象元模型元素的映射关系,给出UML可拓扩展机制,形成适合描述产品应用服务的可拓UML复合语言;分析产业链业务协作过程中的产品资源与组成服务要素,建立面向产品应用服务的四层模型驱动架构,研究架构的四层驱动模型之间的转换关系;通过案例验证了所提方法的可行性和有效性。     

改进的频域辨识方法及其在直升机建模中的应用

本文提出了一种改进的直升机状态空间模型的频域系统辨识方法.该方法根据飞行扫频数据,得到包含直升机动力学模型耦合特性的非参数频率响应.将模式识别中的K平均理论应用到搜索状态空间模型代价函数的最小值中,根据机理建模结果拟合频率响应得到线性的六自由度直升机状态空间模型中的待辨参数.频率响应的计算中应用了一种复合窗函数方法,该方法综合不同窗口长度的频率响应得到一组优化的结果,显著增加了动力学模型频带和频率响应的精度.比较辨识得到的模型和飞行试验数据响应结果表明,辨识得到的模型较好地反映了该型无人直升机在悬停状态下的动力学特性.     

PCA—RBF方法在聚丙烯熔融指数建模中的应用

针对聚丙烯的生产过程是一个大滞后、时变、非线性的复杂系统,提出了基于主成分分析(PCA)的RBF神经网络聚丙烯熔融指数建模方法。该方法用主元分析对高维输入变量进行预处理,构造反应过程信息的低维主元变量,再经径向基函数神经网络对主元变量进行建模。该方法不仅简化了神经网络的结构,而且可以借助主元分析方法对过程故障和过失误差进行侦破,避免导致模型的错误输出。理论分析和实验结果表明,基于PCA和RBF网络方法的聚丙烯熔融指数建模具有精度高、鲁棒性强的优点,有利于工业生产应用。     

The method of boundary condition transfer in application to modeling near-wall turbulent flows

Generalized wall functions in application to high-Reynolds-number turbulence models are derived. The wall functions are based on transfer of a boundary condition from a wall to some intermediate boundary near the wall (usually the first nearest to the wall mesh point but that is not obligatory). The boundary conditions on the intermediate boundary are of Robin-type and represented in a differential form. The wall functions are obtained in an analytical easy-to-implement form, can take into account source terms such as pressure gradient and buoyancy forces, and do not include free parameters. The log-profile assumption is not used in this approach. Both Dirichlet and Newman boundary-value problems are considered. A method for complementing solution near the wall is suggested. Although the generalized wall functions are obtained for the k– model, generalization to other turbulence models is straightforward. The general approach suggested is applicable to studying high-temperature regimes with variable laminar viscosity and density. A robust numerical algorithm is proposed for implementation of Robin-type wall functions. Test results made for a channel flow and axisymmetric impinging jet have showed reasonably good accuracy, reached without any case-dependent turning, and a weak dependence of the solution on the location of the intermediate boundary where the boundary conditions are set. It is demonstrated that the method of boundary condition transfer applied to low-Reynolds-number turbulence models can be used as a decomposition method.     

PostDock: A novel visualization tool for the analysis of molecular docking

“PostDock”, a new visualization tool for the analysis and comparison of molecular docking results is described. It processes a docking results database and displays an interactive pseudo-3D snapshot of multiple ligand docking poses such that their docking energies and docking poses are visually encoded for rapid assessment. The docking energies are represented by a transparency scale whereas the docking poses are encoded by a color scale. The applications of PostDock for ligand–protein docking and for a novel molecular design approach termed “reverse-docking” are presented.     

Discovering interesting inclusion dependencies: application to logical database tuning

Inclusion dependencies together with functional dependencies form the most important data dependencies used in practice. Inclusion dependencies are important for various database applications such as database design and maintenance, semantic query optimization and efficient view maintenance of data warehouse. Existing approaches for discovering inclusion dependencies consist in producing the whole set of inclusion dependencies holding in a database, leaving the task of selecting the interesting ones to an expert user.In this paper, we take another look at the problem of discovering inclusion dependencies. We exploit the logical navigation, inherently available in relational databases through workloads of SQL statements, as a guess to automatically find out only interesting inclusion dependencies. This assumption leads us to devise a tractable algorithm for discovering interesting inclusion dependencies. Within this framework, approximate dependencies, i.e. inclusion dependencies which almost hold, are also considered.As an example, we present a novel application, namely self-tuning the logical database design, where the discovered inclusion dependencies can be used effectively.     

面向方面的信息系统建模方法及应用研究

随着面向对象软件开发技术的不断发展以及软件规模的不断扩大,系统地分析和设计变得日益复杂。软件开发过程中很难利用现有的编程技术（如面向对象编程、面向过程编程）对横切系统多个模块的关注点进行鉴别、理解和模块化。为解决面向对象开发方法中的耦合性较高、可重用性较低和代码分散等问题,将面向方面的编程思想引人到系统分析和设计阶段,提出了一种面向方面的信息系统建模方法。     

新型抗流感病毒药物——三羟基甲氧基黄酮分子对接的研究

运用柔性分子对接程序Affinity,深入研究了5,7,4'-三羟基-8-甲氧基黄酮(MF)与N1、N9亚型神经氨酸酶之间的结合方式并阐明其作用机制.结果表明MF与N1亚型神经氨酸酶之间有一种作用模式,其结合能为-70.26 kcal·mol-1,而与N9亚型之间存两种竞争性的结合模式,最大结合能为-83.51 kcal·mol-1.进一步分析发现MF与这两种亚型神经氨酸酶相互作用的作用力类型、氢键作用及关键作用的氨基酸残基等有着明显的区别.现行药物奥斯米韦作用模式单一,MF则可以与各种亚型甚至变异的神经氨酸酶发生很好地相互作用.因此,MF是一种极具应用前景的新型抗流感病毒药物.结合前人的研究成果,本研究提出了以MF为底物的流感药物修饰方向.     

Tunable approximations to control time-to-solution in an HPC molecular docking Mini-App

The Journal of Supercomputing - The drug discovery process involves several tasks to be performed in vivo, in vitro and in silico. Molecular docking is a task typically performed in silico. It aims...     

Automated modeling of random inclusion composites

We present a parametric model for generating unit cells with randomly distributed inclusions. The proposed algorithm possesses (1) robustness by yielding unit cells with fiber volume fraction of up to 45 % for aspect ratios as high as 20, (2) computationally efficiency accomplished through a hierarchy of algorithms with increasing computational complexity, and (3) versatility by generating unit cells with different inclusion shapes. A statistical study aimed at determining the effective size of the unit cell is conducted. The method has been applied to various random inclusion microstructure composites, including: (1) two-dimensional chopped tow composites employed in automotive applications, (2) polyurea or polyethene coating consisting of hard and soft domains (segments) employed for energy absorption in military and industrial applications, and (3) fiber framework called fiberform embedded in or free from an amorphous matrix used as heat shield on space crafts to prevent structural damage during reentry into the atmosphere.     

用分子对接方法研究肝素与孕激素受体相互结合模式(英文)

用分子对接模拟软件研究了肝素与孕激素受体的相互作用。以肝素中的一糖单位作为探针对孕激素受体蛋白进行搜索,获得肝素组成单位与孕激素受体的特异性结合模式。结果发现,2-O-硫酸-α-L 艾杜糖醛酸(2-O-sulfated iduronic acid,IdoA(2S))作为肝素的核心组成单糖之一,与孕激素受体的结合能力最好。分子对接结果显示 IdoA(2S)深入到孕激素受体的 helix2 和 helix 11 所包围的结合口袋,与孕激素受体结合结构域关键残基 Asn 719 形成稳固的氢键;并与孕激素受体结合结构域的关键残基 Met 909 残基侧链近距离接触,揭示了 IdoA(2S)可能具有的孕激素受体拮抗效应的分子作用机制。本模拟实验所建立的模型能够部分解释肝素抑制孕激素依赖性乳腺癌的现象,同时推测了其相应机理。     

LigandFit: a novel method for the shape-directed rapid docking of ligands to protein active sites

We present a new shape-based method, LigandFit, for accurately docking ligands into protein active sites. The method employs a cavity detection algorithm for detecting invaginations in the protein as candidate active site regions. A shape comparison filter is combined with a Monte Carlo conformational search for generating ligand poses consistent with the active site shape. Candidate poses are minimized in the context of the active site using a grid-based method for evaluating protein-ligand interaction energies. Errors arising from grid interpolation are dramatically reduced using a new non-linear interpolation scheme. Results are presented for 19 diverse protein-ligand complexes. The method appears quite promising, reproducing the X-ray structure ligand pose within an RMS of 2A in 14 out of the 19 complexes. A high-throughput screening study applied to the thymidine kinase receptor is also presented in which LigandFit, when combined with LigScore, an internally developed scoring function, yields very good hit rates for a ligand pool seeded with known actives.