A Structural Systems Biology Approach to Drug Discovery

药物发现的结构系统生物学方法

• 批准号: 7982003
• 负责人: Rommie E Amaro
• 金额: $ 52万
• 依托单位: UNIVERSITY OF CALIFORNIA-IRVINE
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-30 至 2011-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7982003
• 关键词: Accounting; Algorithms; Binding; Biology; Computer Assisted; Computing Methodologies; Disease; Drug Design; Free Energy; Investigation; Length; Ligand Binding; Ligands; Methodology; Pathway interactions; Pharmaceutical Preparations; Physics; RNA-Binding Proteins; System; Systems Biology; Techniques; Therapeutic; Time; Vision; base; complex biological systems; computer studies; design; drug discovery; flexibility; frontier; novel; novel strategies; receptor; tool

DESCRIPTION (Provided by the applicant) Abstract: With petascale computing power on the immediate horizon, computational studies have the opportunity to make unprecedented contributions to drug discovery efforts. Although ligand flexibility is routinely accounted for in computer-aided drug design (CADD) methodologies, incorporating receptor flexibility and system complexity remains an important challenge. The next frontier in flexible receptor methodologies is the integration of cutting-edge physics-based computational methods into the CADD techniques, in conjunction with the use of more complex biological systems. The incorporation of powerful new predictive theoretical tools into flexible receptor methodologies for ligand discovery and design will provide an important shift to the CADD field, enabling the discovery of novel ligand-binding modes and expediting the estimation of more accurate ligand free energies of binding. My vision is to drive the computer-aided drug design field towards a systems biology approach, where multiple proteins, and the RNAs they bind, are targeted - thus challenging the "one-target, one- disease, one-drug" paradigm. The new approaches I envision will integrate multiple time and length scales and take explicit advantage of the new structural information yielded by these algorithms. These investigations will push important frontiers in our understanding of biology, ultimately opening new pathways to more effective therapeutics. Public Health Relevance: With petascale computing power on the immediate horizon, computational studies have the opportunity to make unprecedented contributions to drug discovery efforts. The next frontier in flexible receptor methodologies is the integration and streamlining of cuttingedge physics-based computational methods into computer-aided drug design. The results of this work will catalyze the broader use of these methods within the biomedical research community and be applicable to a wide range of drug targets that are extremely relevant to global health.

描述（由申请人提供） 摘要：随着千万级计算能力的出现，计算研究有机会为药物发现工作做出前所未有的贡献。尽管配体灵活性通常在计算机辅助药物设计（CADD）方法中得到考虑，但结合受体灵活性和系统复杂性仍然是一个重要的挑战。灵活受体方法的下一个前沿是将基于物理的尖端计算方法集成到 CADD 技术中，并结合使用更复杂的生物系统。将强大的新预测理论工具纳入用于配体发现和设计的灵活受体方法中，将为 CADD 领域带来重要转变，从而能够发现新的配体结合模式并加快更准确的配体结合自由能的估计。我的愿景是推动计算机辅助药物设计领域向系统生物学方法发展，以多种蛋白质及其结合的 RNA 为目标，从而挑战“单一目标、一种疾病、一种药物”的范式。我设想的新方法将整合多个时间和长度尺度，并明确利用这些算法产生的新结构信息。这些研究将推动我们对生物学理解的重要前沿，最终为更有效的治疗开辟新途径。 公共卫生相关性：随着千万级计算能力的出现，计算研究有机会为药物发现工作做出前所未有的贡献。灵活受体方法学的下一个前沿是将基于物理的尖端计算方法集成和简化到计算机辅助药物设计中。这项工作的结果将促进这些方法在生物医学研究界的更广泛应用，并适用于与全球健康极其相关的广泛药物靶标。