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Multiple Protein Structures in Computational Drug Design

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:
8053721
负责人:
HEATHER A CARLSON
金额:
$27.54万
依托单位国家:
美国
项目类别:
财政年份:
2002
资助国家:
美国
项目状态:
已结题
起止时间:
2002-04-01 至 2014-03-31

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中文摘要
翻译
描述(由申请人提供):本提案的重点是通过使用蛋白质构象的集合(多蛋白质结构,MPS)来代表固有的灵活性,将蛋白质的灵活性纳入药物发现。该方法克服了传统的刚性结构对接的一些局限性,从而提高了命中率,并增加了已识别抑制剂的化学多样性。更重要的是,目前的目标发展出一种想法,即蛋白质的构象行为可以用来识别新的抑制模式。这项工作的长期目标是通过开发更准确地模拟靶蛋白和结合结构蛋白质组学提供的大量信息的方法来改进基于结构的药物发现(SBDD)领域。这项研究是很好的整合,提供了方法发展和实际应用的关键生物医学重要性的系统,以证明技术的整体效用。第一个目标(SA1)检查MPS方法的各种改进。将使用其他MPS来源。提出了混合溶剂模拟,以增强对蛋白质表面的映射。来自多种溶剂晶体结构的基准数据将确定哪种算法策略在许多蛋白质中表现最佳。对变构部位的适用性将进行研究。SA2和SA3分别进行蛋白质动力学的计算研究,以推动发现新的HIV-1蛋白酶(HIVp)和b-分泌酶(BACE1)抑制剂。这两种蛋白都是天冬氨酸蛋白酶,它们的高度柔韧性极大地影响了配体的结合和抑制。MPS方法已被证明对具有大的、暴露的结合位点的系统是有利的,而传统的对接是有问题的。针对艾滋病毒的新抑制模式有望减少艾滋病治疗中的耐药性。我们对抑制BACE1的替代模式的追求将集中在识别更有可能穿过血脑屏障的较小先导化合物;这种药代动力学性质对治疗阿尔茨海默病是绝对必要的,但在文献中大多数抑制剂缺乏。MPS方法的实验验证是后期目标的关键组成部分,包括分析潜在的抑制剂和通过氘交换、晶体学和核磁共振进行关键结构研究。
英文摘要
DESCRIPTION (provided by applicant): This proposal focuses on incorporating protein flexibility into drug discovery by using ensembles of protein conformations (multiple protein structures, MPS) to represent inherent flexibility. This approach has been shown to overcome some limitations of traditional docking to rigid structures, resulting in higher hit rates and greater chemical diversity of identified inhibitors. More importantly, the current aims evolve the idea that a protein's conformational behavior can be used to identify new modes of inhibition. The long-term goal of this work is to improve the field of structure-based drug discovery (SBDD) by developing methods that more accurately model target proteins and incorporate the vast information available from structural proteomics. This study is well integrated, providing both methodological development and practical application to systems of critical biomedical importance to prove overall utility of the techniques. The first aim (SA1) examines various improvements to the MPS methodology. Alternative sources of MPS will be used. Mixed solvent simulations are proposed to enhance mapping the protein surface. Benchmark data from multiple solvent crystal structures will identify which algorithmic strategies perform best across many proteins. Applicability to allosteric sites will be examined. SA2 and SA3 conduct computational studies of protein dynamics to drive the discovery of new inhibitors for HIV-1 protease (HIVp) and b-secretase (BACE1), respectively. Both proteins are aspartyl proteases, and their large degree of flexibility greatly affects ligand binding and inhibition. The MPS approach has proven advantageous for systems with large, exposed binding sites that are problematic for traditional docking. Targeting new modes of inhibition for HIVp has the promise of reducing drug resistance in AIDS treatment. Our pursuit of alternative modes of inhibiting BACE1 will focus on identifying smaller lead compounds that are more likely to cross the blood-brain barrier; this pharmacokinetic property is absolutely essential to treat Alzheimer's disease but is lacking in most inhibitors in the literature. Experimental verification of the MPS methodology is a key component of the later aims, including assaying potential inhibitors and performing key structural studies by deuterium exchange, crystallography, and NMR. PUBLIC HEALTH RELEVANCE: Improved techniques for computer-aided drug discovery will be developed. Computers will be used to understand protein flexibility and find new ways to inhibit HIV-1 protease and b-secretase. Inhibitors with new mechanisms are needed to overcome drug resistance in AIDS and pharmacokinetic barriers in treating Alzheimer's disease, respectively.
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