COMPUTATIONAL RESOURCE FOR STRUCTURAL BIOLOGY

描述：结构计算资源的总体目标 生物学是开发和应用新的结构预测方法， 蛋白质背景下的结构改进和机理研究 和药物设计。提出了以下具体目标。 在以下领域开发计算模块和方法： 1)大型化学品分子多样性/相似性的有效分析 组合化学/数据库挖掘背景下的数据库，通过 聚类和模式识别，以及描述符的开发。 2)用于准确预测和分析动力学的仿真技术 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 采用连续介质模型。 3)结合量子的层次化分子模拟算法 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。新的 开发的重点将是经典和量子之间的新接口 力学，计算方法和参数的应用 极化力场。 4)基于统计的结构分析和精化新工具 几何图形。

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.