Exploiting Solvation Structure and Thermodynamics for Prospective Drug Discovery and Rational Design

利用溶剂化结构和热力学进行前瞻性药物发现和合理设计

• 批准号: 9461105
• 负责人: Thomas Philip Kurtzman
• 金额: $ 12.38万
• 依托单位: HERBERT H. LEHMAN COLLEGE
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-10 至 2021-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9461105
• 关键词: Adoption; Adverse effects; Affinity; Binding; Binding Proteins; Binding Sites; Biological Assay; Chemicals; Code; Collaborations; Communities; Computer Assisted; Computing Methodologies; Data; Designer Drugs; Development; Docking; Dopamine D1 Receptor; Drug Addiction; Drug Design; Drug Targeting; Environment; Free Energy; Hydration status; Hydrogen Bonding; Hydrophobicity; Industrialization; Lead; Ligands; Liquid substance; Maps; Measures; Mediating; Mediation; Membrane Proteins; Methodology; Methods; Modeling; Modification; Molecular; Nature; Opioid Receptor; Pain; Pharmaceutical Preparations; Pharmacology; Physics; Play; Property; Protein Family; Proteins; Psychotropic Drugs; Resolution; Retrospective Studies; Risk; Role; Site; Specialist; Specificity; Structure; Testing; Thermodynamics; United States National Institutes of Health; Validation; Water; base; college; community college; cross reactivity; design; dopamine D3 receptor; drug discovery; experimental group; hydrophilicity; improved; inhibitor/antagonist; interest; lead optimization; member; mu opioid receptors; mu receptors; novel; open source; pharmacophore; professor; prospective; receptor; scaffold; screening; screening program; stepholidine; substance abuse treatment; targeted treatment; theories; tool; virtual; water treatment

The displacement of water from a protein surface upon the binding of a drug has a significant, if not dominant, contribution to the free energy of recognition, and hence plays a significant role in determining drug potency and specificity. Despite the importance of water in mediating drug- protein interactions, commonly used structure-based models do not explicitly treat water as a molecule. Instead, they indirectly hydration effects by categorizing ligand-protein contacts as either hydrophobic or hydrophilic or by modeling water as a continuum. Neither of these approaches accounts for the finite size and directed nature of water's hydrogen bonds, the physics of which is essential for describing the hydration of the diverse environment of confined protein binding sites. The adoption of simplified treatments of water in drug design applications has been made necessary by the complexity of hydration phenomena and the lack of a molecular-based framework for its structural and thermodynamic analysis. In recent years, the PI has been instrumental in developing two methodologies that utilize inhomogeneous fluid solvation theory (IST) to map out solvation structural and thermodynamic properties of water in molecular detail in protein binding sites: 1) A hydration site analysis (HSA) approach, which forms the basis for Schrodinger LLC's WaterMap and 2) A corresponding high-resolution grid- based implementation, GIST, now available in the freely distributed AmberTools. Each of these analysis tools maps out 24 independent measures of structure and thermodynamics. In this proposal we will incorporate solvation structure and thermodynamic maps into virtual screening and lead optimization methodologies to improve our ability to identify and design compounds that bind with high affinity and specificity to a targeted member of a family of proteins. We propose to optimize and apply these methods to two important drug targets: the dopamine receptor D3, a target for the treatment of drug addiction, and the μ-OR opioid receptor, an important target for pain alleviation. We have chosen these receptors because of the challenges of targeting them specifically. Off-target binding often results in either the inability to discover viable drugs (D3) or drugs which have significant undesirable side effects (μ -OR). Current methodologies have been ineffective in finding specific binders for these targets. Hence they remain drug targets of significant interest in both academic and industrial settings and the natural choice for the application of the new discovery methodologies proposed here.

当药物结合时，水从蛋白质表面的置换具有显著的，如果 不占主导地位，对识别的自由能有贡献，因此起着重要作用 来确定药物的效力和特异性。尽管水在介导药物中的重要性- 蛋白质相互作用，常用的基于结构的模型不明确对待水作为一个 分子。相反，他们通过将配体-蛋白质接触分类为 或者疏水的或者亲水的，或者通过将水建模为连续体。这两种 方法解释了水的氢键的有限大小和定向性质， 其物理学对于描述受限的不同环境的水合作用是必不可少的。 蛋白质结合位点。在药物设计应用中采用简化的水处理方法 由于水化现象的复杂性和缺乏一种 分子为基础的框架，其结构和热力学分析。近年来 PI在开发两种利用非均匀流体的方法方面发挥了重要作用 溶剂化理论（IST）绘制出溶剂化结构和水的热力学性质， 蛋白质结合位点的分子细节：1）水合位点分析（HSA）方法，其 形成了薛定谔有限责任公司的水地图的基础和2）相应的高分辨率网格- 基于GIST的实现，现在可以在免费分发的AmberTools中使用。这一切成功都 分析工具绘制了24个结构和热力学的独立测量。 在这个建议中，我们将溶剂化结构和热力学地图纳入虚拟 筛选和领先的优化方法，以提高我们的识别和设计能力 以高亲和性和特异性结合靶向的家族成员的化合物， proteins.我们建议优化并将这些方法应用于两个重要的药物靶点： 多巴胺受体D3，药物成瘾治疗的靶点，以及μ-OR阿片类药物 受体，是缓解疼痛的重要靶点。我们选择这些受体是因为 具体针对他们的挑战。脱靶结合通常会导致 发现可行的药物（D3）或具有显著不良副作用的药物（μ -OR）。 目前的方法在寻找这些目标的特定结合剂方面是无效的。因此 它们仍然是学术界和工业界都非常感兴趣的药物靶标， 自然选择的应用程序的新发现的方法在这里提出。