COMPUTATIONAL RESOURCE FOR STRUCTURAL BIOLOGY

描述：结构计算资源的总体目标 生物学是发展和应用新的结构预测方法， 蛋白质的结构优化和机制研究 药物设计。提出了以下具体目标。 开发以下领域的计算模块和方法： 1)高效分析大型化学品的分子多样性/相似性 数据库在组合化学/数据库挖掘的背景下，通过 聚类和模式识别，以及描述符的开发。 2)用于精确预测和动态分析的模拟技术 和蛋白质-配体相互作用的热力学。这些将包括 溶剂化自由能的分子动力学模拟与计算 连续介质模型。 3)结合量子力学的分层分子模拟算法 力学和经典力学，包括密度泛函理论， 分子轨道方法和极化分子力学。新 发展将集中在经典和量子之间的新接口上 力学，以及计算方法和参数， 极化力场 4)基于统计的结构分析和细化的新工具 几何

DESCRIPTION: The overall goal of the Computational Resource for Structural Biology is to develop and apply new methods for structure prediction, structure refinement, and mechanistic studies in the context of protein and drug design. The following specific aims are proposed. Development of computational modules and methods in the following areas: 1) Efficient analysis of molecular diversity/similarity of large chemical databases in the context of combinatorial chemistry/database mining, via clustering and pattern recognition, and development of descriptors. 2) Simulation techniques for accurate prediction and analysis of dynamics and thermodynamics of protein-ligand interactions. These will consist of molecular dynamics simulations and computation of solvation free energy with the continuum dielectric model. 3) Hierarchical molecular simulation algorithms combining quantum mechanics and classical mechanics , including density functional theory, molecular orbital methods, and polarizable molecular mechanics. New development will focus on a new interface between classical and quantum mechanics, and computational methods and parameters for application of a polarizable force field. 4) New tools for structure analysis and refinement based on statistical geometry.