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: 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 2014-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8053721
• 关键词: Acquired Immunodeficiency Syndrome; Affect; Allosteric Site; Alzheimer' s Disease; Amyloid beta-Protein Precursor; Aspartic Endopeptidases; Behavior; Benchmarking; Binding; Binding Sites; Biological Assay; Blood - brain barrier anatomy; Chemicals; Cleaved cell; Complement; Computer Assisted; Computer Simulation; Computers; Computing Methodologies; Crystallography; Data; Databases; Deuterium; Development; Dimerization; Docking; Drug Design; Drug Kinetics; Drug resistance; Elbow; Enzymes; Eye; Fluorescence Resonance Energy Transfer; Goals; HIV-1; Hydrogen; Journals; Kinetics; Lead; Ligand Binding; Ligands; Literature; Maps; Mass Spectrum Analysis; Membrane Proteins; Methodology; Methods; Mining; Modeling; Molecular Conformation; National Institute of General Medical Sciences; Nature; Peptide Hydrolases; Peptides; Pharmaceutical Preparations; Property; Protein Conformation; Protein Dynamics; Proteins; Proteomics; Scheme; Screening procedure; Site; Solvents; Source; Speed; Structure; Surgical Flaps; System; Techniques; Work; base; beta-site APP cleaving enzyme 1; computer studies; design; dimer; drug discovery; flexibility; functional group; improved; inhibitor/antagonist; method development; molecular dynamics; monomer; news; novel; pharmacophore; practical application; protein structure; public health relevance; receptor; scaffold; secretase; simulation; success

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.

描述（由申请人提供）：该提案的重点是通过使用蛋白质构象（多个蛋白质结构，MPS）的集合来代表固有的灵活性，将蛋白质灵活性纳入药物发现中。这种方法已被证明可以克服传统对接刚性结构的一些限制，从而提高所识别抑制剂的命中率和化学多样性。更重要的是，当前的目标发展了这样的想法：蛋白质的构象行为可用于识别新的抑制模式。这项工作的长期目标是通过开发更准确地模拟靶蛋白并整合结构蛋白质组学中可用的大量信息的方法来改进基于结构的药物发现（SBDD）领域。这项研究整合得很好，为具有关键生物医学重要性的系统提供了方法开发和实际应用，以证明这些技术的整体效用。第一个目标 (SA1) 检查 MPS 方法的各种改进。将使用 MPS 的替代来源。建议使用混合溶剂模拟来增强蛋白质表面的绘图。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佳。将检查变构位点的适用性。 SA2 和 SA3 进行蛋白质动力学计算研究，以分别推动 HIV-1 蛋白酶 (HIVp) 和 b 分泌酶 (BACE1) 的新抑制剂的发现。这两种蛋白都是天冬氨酰蛋白酶，其高度的灵活性极大地影响配体结合和抑制。事实证明，MPS 方法对于具有大型、暴露的结合位点的系统具有优势，而这些结合位点对于传统对接来说是有问题的。针对 HIVp 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于识别更小的先导化合物，这些化合物更有可能穿过血脑屏障；这种药代动力学特性对于治疗阿尔茨海默氏病绝对必要，但文献中大多数抑制剂都缺乏这种药代动力学特性。 MPS 方法的实验验证是后续目标的关键组成部分，包括分析潜在的抑制剂以及通过氘交换、晶体学和 NMR 进行关键结构研究。 公共卫生相关性：将开发计算机辅助药物发现的改进技术。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 b 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。