Multiple Protein Structures in Computational Drug Design

描述（由申请人提供）：该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，将蛋白质灵活性纳入药物发现。这种方法已被证明可以克服传统对接到刚性结构的一些限制，从而提高识别抑制剂的命中率和化学多样性。更重要的是，目前的目标发展了这样一种想法，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并结合结构蛋白质组学提供的大量信息的方法来改善基于结构的药物发现（SBDD）领域。这项研究是很好的集成，提供了方法的发展和实际应用系统的关键生物医学的重要性，以证明整体效用的技术。第一个目标（战略咨询服务1）审查了对总计划方法的各种改进。将使用MPS的替代来源。混合溶剂模拟提出了增强映射的蛋白质表面。来自多种溶剂晶体结构的基准数据将确定哪些算法策略在许多蛋白质中表现最好。将检查变构位点的适用性。SA 2和SA 3分别进行蛋白质动力学的计算研究，以推动发现HIV-1蛋白酶（HIVp）和β-分泌酶（BACE 1）的新抑制剂。这两种蛋白质都是乙酰基蛋白酶，并且它们的大程度的灵活性极大地影响配体结合和抑制。MPS方法已被证明对于具有大的暴露的结合位点的系统是有利的，所述结合位点对于传统对接是有问题的。靶向HIVp抑制的新模式有望减少艾滋病治疗中的耐药性。我们对抑制BACE 1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的先导化合物上;这种药代动力学特性对于治疗阿尔茨海默病是绝对必要的，但在文献中缺乏大多数抑制剂。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NMR进行关键结构研究。 公共卫生相关性：将开发改进的计算机辅助药物发现技术。计算机将用于了解蛋白质的灵活性，并找到抑制HIV-1蛋白酶和β-分泌酶的新方法。需要具有新机制的抑制剂来分别克服艾滋病的耐药性和治疗阿尔茨海默病的药代动力学障碍。

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.