Multiple Protein Structures in Computational Drug Design

计算药物设计中的多种蛋白质结构

• 批准号: 6464211
• 负责人: HEATHER A CARLSON
• 金额: $ 25.69万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-04-01 至 2007-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6464211
• 关键词: aspartic endopeptidases; chemical chain length; computer data analysis; computer program /software; computer simulation; computer system design /evaluation; dihydrofolate reductase; drug design /synthesis /production; enzyme inhibitors; informatics; intermolecular interaction; model design /development; molecular dynamics; molecular shape; pharmacology; physical model; protein structure function; proteomics; statistics /biometry; structural biology; tetrahydrofolylpolyglutamate synthase; virus protein

DESCRIPTION (provided by applicant): A method is presented for using multiple protein structures (MPS) in computational drug design. The initial goal of this proposal is to provide a solid technique for incorporating protein flexibility into structure-based drug discovery (SBDD). The modeling community needs methods that address this long-standing problem, and the task provides a measure of the strengths and weaknesses of using MPS before tackling the greater challenge of structural genomics. NIGMS has recently funded seven research centers as part of its Protein Structure Initiative. Drug discovery will be revolutionized with the explosion of information to come, but only if the tools exist to combine many related protein structures in a way that is useful for SBDD. The long-term goal of this work is to improve the field of computer-aided drug design by developing methods that more accurately model target proteins and exploit the vast amount of information available from proteomics. Better methods for drug design will speed the discovery of lead compounds and new pharmaceutical therapies. The specific aims for this project focus on (1) optimizing the protocol for using MPS from computer simulations and experimental sources, (2) extrapolating the use of MPS to exploit a subfamily of homologous proteins in the development of broad-spectrum therapeutics, and (3) applying the method to systems of biomedical importance. MPS will be used to create receptor-based pharmacophore models for several enzymatic systems. The models will be judged by searching a database of active and inactive inhibitory compounds from the literature. Successful models will present few false positives and will identify the most active compounds in the database. Collaborations with enzymologists are proposed to aid the development of novel inhibitors in the later stages of the project.

描述（由申请人提供）：提出了一种使用多个 蛋白质结构（MPS）在计算药物设计中的应用这个项目最初的目标是 建议是提供一种结合蛋白质柔性的可靠技术 基于结构的药物发现（SBDD）。模特界需要 解决这个长期存在的问题的方法，任务提供了一个 衡量采用强制性私营公积金计划的优点和缺点，然后才处理 结构基因组学的挑战。 NIGMS最近资助了七个研究中心，作为其蛋白质的一部分。 结构倡议。药物发现将随着爆炸发生革命性变化 但前提是要有联合收割机将许多相关的 蛋白质结构的方式是有益的SBDD。长期目标是 工作是通过开发来改进计算机辅助药物设计领域 更精确地模拟目标蛋白质并利用大量 从蛋白质组学中获得的信息。更好的药物设计方法将 加速先导化合物和新药物疗法的发现。 该项目的具体目标集中在（1）优化协议， 使用来自计算机模拟和实验来源的MPS，（2）外推 使用MPS开发同源蛋白质的亚家族， 以及（3）将该方法应用于以下系统： 生物医学的重要性MPS将用于创建基于受体的药效团 几种酶系统的模型。将通过搜索一个 来自文献的活性和非活性抑制化合物的数据库。 成功的模型将呈现很少的误报，并将识别最多的 数据库中的活性化合物与酶学家的合作是 建议在后期阶段帮助开发新的抑制剂， 项目