Structure Based Drug Discovery

基于结构的药物发现

• 批准号: 7058113
• 负责人: Stephen Kevin Burley
• 金额: $ 0.5万
• 依托单位: KEYSTONE SYMPOSIA
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-03-01 至 2007-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7058113
• 关键词: drug discovery /isolation; high throughput technology; intermolecular interaction; meeting /conference /symposium; nuclear magnetic resonance spectroscopy; travel

DESCRIPTION (provided by applicant): This conference will focus on several exciting new developments in Structure Based Drug Discovery, including: fragment based lead discovery/lead optimization, high-throughput X-ray and NMR structure determination of protein ligand complexes, computational analyses of ligand-receptor interactions and prediction of novel ligands, ligand binding selectivity, and ADME/toxicity properties. Major/pivotal problems facing both academic and industrial scientists include: (a) understanding precisely what constitutes a good starting point for lead optimization, (b) understanding how best to optimize selectivity and avoid problems with ADME/toxicity, (c) understanding the limitations of currently available in silico methods, (d) understanding how to combine the results of biophysical characterization of protein-ligand interactions with medicinal chemistry to produce potent/selective lead compounds, and (e) developing sufficient expertise/experience to bring membrane proteins and macromolecular interactions within the purview of structure based drug discovery. Upon completion of this conference, participants should: - Appreciate the challenges represented by membrane proteins and macromolecular interactions as targets for structure based drug discovery. - Understand current approaches to fragment based drug discovery. - Appreciate the state-of-the-art in automated approaches to determination of protein-ligand complex structures with solution NMR spectroscopy and X-ray crystallography. - Understand the roles that homology modeling and computational docking play in structure based drug discovery. - Appreciate the contributions that structural studies can make to lead optimization and our understanding of selectivity and ADME/Toxicity. - Understand the limitations of current in silico methods for de novo drug discovery. The 2006 Keystone Symposium entitled "Structure-Guided Drug Discovery" is intended to advance the use novel technologies to speed and improve the process of drug discovery and development. Specifically, use of atomic level structural information can accelerate discovery and optimization of new drugs and improve the "fit" between the drug molecule and the target, leading to better treatment effect and reduced incidence of side effects.

描述（由申请人提供）：本次会议将重点介绍基于结构的药物发现的几个令人兴奋的新发展，包括：基于片段的铅发现/铅优化，高通量X射线和NMR结构的蛋白质配体配合物的确定，计算分析，计算分析配体 - 受体相互作用以及新型配体，配体结合选择性和ADME/毒性特性的预测。 学术和工业科学家面临的主要/关键问题包括： （a）准确理解铅优化的良好起点， （b）了解如何最好地优化选择性并避免ADME/毒性问题， （c）了解当前可用的硅方法的局限性， （d）了解如何结合蛋白质 - 配体相互作用与药物化学的生物物理表征的结果，以产生有效/选择性的铅化合物和 （e）发展足够的专业知识/经验，以将膜蛋白和大分子相互作用带到基于结构的药物发现的范围内。 本会议结束后，参与者应： - 欣赏膜蛋白和大分子相互作用所代表的挑战，作为基于结构的药物发现的靶标。 - 了解当前基于碎片的药物发现的方法。 - 欣赏使用溶液NMR光谱和X射线晶体学确定蛋白质配体结构的自动化方法的最新方法。 - 了解同源性建模和计算对接在基于结构的药物发现中发挥的作用。 - 欣赏结构研究可以为领导优化以及我们对选择性和毒性的理解所做的贡献。 - 了解硅方法中电流的局限性。 2006年的Keystone研讨会标题为“结构引导的药物发现”旨在推进使用新型技术来加快和改善药物发现和发育的过程。具体而言，使用原子水平的结构信息可以加速新药的发现和优化，并改善药物分子与靶标之间的“拟合”，从而提高更好的治疗效果并降低副作用的发生率。