遗传算法在计算机辅助药物分子设计中的应用

作为一种重要的启发式优化算法,遗传算法在计算机辅助药物分子设计中得到了广泛的应用.本文介绍了遗传算法的基本概念以及工作原理,同时结合作者科研组的工作,就遗传算法在定量构效关系、构象分析、药效团模拟、分子对接以及虚拟组合化学等方面的应用做了系统的阐述。     

新药物分子设计的某些理论方法

新药物的先导物设计和新药物的优选设计是两个不同的概念和范畴，本文介绍了发现先导药物的组合化学、群集筛选和计算机筛选方法等最新进展。同时介绍了构效关系研究中的某些基本理论方法。讨论了新药物分子设计的某些问题及其弥补措施。     

基质金属蛋白酶抑制剂设计的研究进展*

基质金属蛋白酶(MMP) 是一类含锌的水解酶, 过量的MMP会加速细胞外基质的降解并导致一系列的疾病, 例如癌症、关节炎和多发性硬化症等。因此MMP抑制剂的研究已成为药物设计研究领域中的一个热门课题。近年来, 科学家们发展了三种分子设计的方法, 包括基于底物的药物设计、基于结构的药物设计和组合化学技术。本文介绍了这些方法的原理及其在MMP抑制剂设计中的应用和进展。     

遗传算法在分子图形显示中的应用

遗传算法在分子图形显示中的应用邵学广，蔡文生，张懋森，赵贵文（中国科学技术大学应用化学系，化学物理系，合肥２３００２６）分子图形和分子模型的研究是计算化学领域中研究的热门课题之一［１，２］，它对于结构一活性相关、有机合成路线设计、药物设计［３，４］等...     

基于药物数据报道数据库的虚拟组合片段库构建

对药物数据报道数据库中142553个药物分子进行统计分析, 提取得到了这些药物分子的共同结构特征. 根据药物分子的结构特征将其拆分为环结构、侧链和连接子, 共整理得到32017个片段结构, 其中环结构13642个、侧链10076个、连接子8299个. 为更好地指导全新药物设计, 利用拆分片段构建了三个虚拟组合片段数据库: 用环结构和侧链组合方式构建了药效基团库, 含有34244个片段; 用环结构的刚性特点构建了基本骨架库, 含有片段13574个; 直接利用连接子构建了连接片段库, 含有连接片段8051个. 库中所有片段都经过能量优化, 均具有合理的构型和构象, 可以用于虚拟组合库的构建和全新药物设计.     

动态组合化学研究进展及其在药物设计中的应用

动态组合化学利用可逆过程连接库内的各种组分,实现动态库的多样性.在库中加入靶标分子,通过分子识别、分子组装,诱导产生和靶标分子产生最强键合的化合物,推动化合物库的移动.介绍了动态组合化学的基本原理,并综述了近年来发现的动态可逆过程和动态组合化学在生物学、新药设计中的应用.     

药物分子胎盘屏障渗透的支持向量回归模型

药物分子透过胎盘屏障进入胎儿体内可能对胎儿造成不良影响,在临床及药物研发中评估药物分子的胎盘屏障渗透能力,对于保护受孕期的妇女以及胎儿,都有着十分重要的作用.本文使用了组合的遗传算法-共轭梯度-支持向量回归(GA-CG-SvR)方法,建立了一个药物分子胎盘屏障渗透的预测模型.对于所建模型,使用5重交叉验证和独立测试集方...     

基于改进遗传算法的蛋白质三维折叠模拟

根据氨基酸的序列预测蛋白质的空间结构在基因治疗药物分子设计等方面有巨大的潜在应用价值.本研究基于HP格子模型利用改进的遗传算法预测了蛋白质的三维空间结构.改进的遗传算法引入了克隆体数量限制策略、巢穴竞争选择策略及局部优化策略等.实验结果表明,改进的遗传算法显著地提高了蛋白质结构的预测效率,模拟的蛋白质结构紧凑,更接近真实蛋白质的构型.     

分子对接方法的应用与发展

分子对接方法加快了药物开发周期,具有快速、准确度高等优点.本文详述了分子对接方法的基本原理,及分子对接空间和能量的匹配要求和优化时的各种方法.综述了该方法在药物设计、药理分析和探测生命体系等方面的应用.     

化学库及分子差异性设计研究进展

组合化学是近年来发展起来的一种快速合成和平行筛选群体化合物的新方法。它可以用来设计先导化合物，也可以对药物分子进行结构改造。本文主要综述了化学库的合成以及计算机辅助组合化学的研究进展。     

A genetic algorithm for the automated generation of small organic molecules: Drug design using an evolutionary algorithm

Rational drug design involves finding solutions to large combinatorial problems for which an exhaustive search is impractical. Genetic algorithms provide a novel tool for the investigation of such problems. These are a class of algorithms that mimic some of the major characteristics of Darwinian evolution. LEA has been designed in order to conceive novel small organic molecules which satisfy quantitative structure-activity relationship based rules (fitness). The fitness consists of a sum of constraints that are range properties. The algorithm takes an initial set of fragments and iteratively improves them by means of crossover and mutation operators that are related to those involved in Darwinian evolution. The basis of the algorithm, its implementation and parameterization, are described together with an application in de novo molecular design of new retinoids. The results may be promising for chemical synthesis and show that this tool may find extensive applications in de novo drug design projects.     

萃取溶剂选择的计算机辅助分子设计中的数学方法

萃取精馏是分离沸点相近或具有恒沸组成混合物的一种重要方法。选择最优的萃取剂是提高生产能力和降低能耗的根本途径。萃取剂选择的计算机辅助分子设计（CAMD）是基于性质估算的方法即通过CAMD来生成一组具有期望性质的分子,然后再对候选分子进行筛选。目前,CAMD法的研究主要可分为生成一验证、数学优化和组合优化。生成一验证法通常使用启发式的策略,是基于知识的,无法克服基团的组合爆炸问题,也不能保证结果的最优性;数学优化方法,包括混合整数非线性规划（MINLP）和混合整数线性规划（MILP）,可用于表达非线性或线性的结构．性质关系,但准确表达结构-性质关系还有困难;组合优化法是使用遗传算法或模拟退火算法、禁忌搜索等的方法,理论上可克服以上问题。本文评述了以上三种方法在萃取精馏溶剂选择领域中的用途、原理及其工业化所面临的主要问题。     

Multi‐Objective Molecular De Novo Design by Adaptive Fragment Prioritization

We present the development and application of a computational molecular de novo design method for obtaining bioactive compounds with desired on‐ and off‐target binding. The approach translates the nature‐inspired concept of ant colony optimization to combinatorial building block selection. By relying on publicly available structure–activity data, we developed a predictive quantitative polypharmacology model for 640 human drug targets. By taking reductive amination as an example of a privileged reaction, we obtained novel subtype‐selective and multitarget‐modulating dopamine D₄ antagonists, as well as ligands selective for the sigma‐1 receptor with accurately predicted affinities. The nanomolar potencies of the hits obtained, their high ligand efficiencies, and an overall success rate of 90 % demonstrate that this ligand‐based computer‐aided molecular design method may guide target‐focused combinatorial chemistry.     

Application of self-organizing maps in compounds pattern recognition and combinatorial library design

In the computer-aided drug design, in order to find some new leads from a large library of compounds, the pattern recognition study of the diversity and similarity assessment of the chemical compounds is required; meanwhile in the combinatorial library design, more attention is given to design target focusing library along with diversity and drug-likeness criteria. This review presents the current state-of-art applications of Kohonen self-organizing maps (SOM) for studying the compounds pattern recognition, comparing the property of molecular surfaces, distinguishing drug-like and nondrug-like molecules, splitting a dataset into the proper training and test sets before constructing a QSAR (Quantitative Structural-Activity Relationship) model, and also for the combinatorial libraries comparison and the combinatorial library design. The Kohonen self-organizing map will continue to play an important role in drug discovery and library design.     

基于结构的组合库设计策略在新药创制中的应用

合理设计一些容量小的、针对特定靶标的化合物库(称为集中库,focused library),是当前组合库设计中的热点。当靶标的三维结构可以通过X射线衍射或NMR等手段确定后,人们就能采用几种不同的策略来进行组合库的设计。本文讨论了在靶标结合位点的约束下,进行组合库设计的主要方法及程序,同时强调了它们的优点与不足。通过这些方法的成功应用实例,显示了它们在新药创制中的广泛应用前景。     

Constructing virtual combinatorial fragment libraries based upon MDL Drug Data Report database

Structural analysis of known drugs or drug-like compounds provides important information for drug design. The 142553 drug molecules in the MDL Drug Data Report database were analyzed, and then the common structural features were extracted. According to the common structural features, drug molecules were segmented into 32017 fragments, including 13642 ring fragments, 10076 linker fragments, and 8299 side chain fragments. These fragments were further used to establish three types of virtual combinatorial fragment libraries: a basic framework library containing 13574 rings; a linker library of 8051 linkers and a pharmacophore library of 34244 fragments combined by rings and side chains. After energy minimization, all fragments in the above three libraries maintain reasonable geometrical features and spatial conformations, and would be useful for building a virtual combinatorial database and de novo drug design.     

Ultrafast algorithm for designing focused combinational arrays

A novel greedy algorithm for the design of focused combinatorial arrays is presented. The method is applicable when the objective function is decomposable to individual molecular contributions and makes use of a heuristic that allows the independent evaluation and ranking of candidate reagents in each variation site in the combinatorial library. The algorithm is extremely fast and convergent and produces solutions that are comparable to and often better than those derived from the substantially more elaborate and computationally intensive stochastic sampling techniques. Typical examples of design objectives that are amendable to this approach include maximum similarity to a known lead (or set of leads), maximum predicted activity according to some structure-activity or receptor binding model, containment within certain molecular property bounds, and many others.