Development and Deployment of the Movable Type Method for Drug Discovery and Desi

用于药物发现和设计的可移动式方法的开发和部署

• 批准号: 8781973
• 负责人: Lance M Westerhoff
• 金额: $ 16.53万
• 依托单位: QUANTUMBIO, INC.
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-10 至 2015-03-09
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8781973
• 关键词: Active Sites; Address; Affinity; Binding; Binding Proteins; Biological; Biotechnology; Build-it; Calorimetry; Code; Collaborations; Complex; Computational Biology; Computer Simulation; Computer software; Coupled; Databases; Development; Docking; Drug Design; Drug Interactions; Environment; Feedback; Free Energy; Freedom; Goals; Grant; Hand; Health; Human; Internet; Laboratories; Letters; Life; Ligand Binding; Ligands; Marketing; Medicine; Methodology; Methods; Modeling; Molecular; Molecular Bank; Molecular Structure; Nature; Nuclear Magnetic Resonance; Online Systems; Performance; Pharmaceutical Preparations; Pharmacologic Substance; Phase; Physics; Play; Positioning Attribute; Printing; Probability; Process; Protein Binding; Proteins; Protocols documentation; Publications; Reporting; Research; Roentgen Rays; Role; Sampling; Site; Small Business Innovation Research Grant; Solutions; Statistical Mechanics; Structure; Surveys; System; Technology; Titrations; Validation; Water; Work; X-Ray Crystallography; base; design; drug discovery; graphical user interface; human disease; improved; insight; interest; intermolecular interaction; knowledge base; next generation; novel; novel therapeutics; phase 2 study; protein structure; public health relevance; receptor; small molecule; success; tool; validation studies; web based interface

DESCRIPTION (provided by applicant): Our long-term goal is to provide a solution to the protein-ligand binding affinity and pose prediction problems. The protein-ligand docking and scoring problem is one of the central problems in computational biology because of its importance in understanding intermolecular interactions, and because of its practical payoff. The transformative impact molecular docking and scoring can have in the design of next generation medicines cannot be overstated. If we could routinely and accurately design molecules using these approaches it would revolutionize drug discovery by winnowing out compounds with no activity while focusing more effort and scrutiny on highly active compounds. In this proposal we describe a novel method we call Movable Type (MT), which addresses the protein ligand binding and scoring problem using fundamental statistical mechanics combined with a novel way to generate the ensemble of a ligand in a protein binding pocket. Via a rapid assembly of the necessary partition functions we directly obtain binding free energies and the low free energy poses. Conceptually, the MT method is analogous to block and type set printing, which allows us to efficiently evaluate partition functions describing regions or systems of interest. In this approach we construct two databases that 1) describe the probability of certain pairwise interactions as a function of r obtained from a knowledge base (Protein Databank (PDB) or the Cambridge Structural Database (CSD)) and 2) the energetics of the pairwise interactions as a function of r obtained from empirical potentials, which can be either derived from the probabilities or can utilize extant pairwise potentials like AMBER. Overall, the MT method is a general one and can use a broad range of two-body potential functions and can be extended to higher-order interactions if so desired. In the present project we will extend and further validat the MT method and develop commercial quality software to deliver this methodology to users via the web and GUI. This will involve collaboration between the academic laboratory and the industrial laboratory, development of a new implementation of the method in order to commercially deploy the technology, construction of a graphical user interface based on MOE along with a web-based interface, and finally use of this software in real life structure-based drug discovery problems on-site with our pharmaceutical collaborators (see Letters of Support).

描述（由申请人提供）：我们的长期目标是提供蛋白质-配体结合亲和力的解决方案并提出预测问题。蛋白质-配体对接和计分问题是计算生物学中的核心问题之一，因为它在理解分子间相互作用中的重要性，并且因为它的实际收益。分子对接和评分在下一代药物设计中的变革性影响怎么强调都不过分。如果我们能够使用这些方法常规而准确地设计分子，那么通过筛选出没有活性的化合物，同时将更多的精力和审查集中在高活性化合物上，这将彻底改变药物发现。在这个建议中，我们描述了一种新的方法，我们称之为Movable Type（MT），它解决了蛋白质配体结合和评分问题，使用基本的统计力学结合一种新的方式来生成一个配体的合奏在蛋白质结合口袋。通过快速组装所需的配分函数，我们直接获得结合自由能和低自由能位姿。从概念上讲，MT方法类似于块和类型集打印，它允许我们有效地评估描述感兴趣的区域或系统的分区函数。在 该方法我们构建了两个数据库，1）描述某些成对相互作用的概率作为从知识库（蛋白质数据库（PDB）或剑桥结构数据库（CSD））获得的r的函数，和2）成对相互作用的能量作为从经验势获得的r的函数，所述经验势可以从概率导出或者可以利用现存的成对势如AMBER。总的来说，MT方法是一种通用的方法，可以使用广泛的两体势函数，如果需要的话，可以扩展到高阶相互作用。 在本项目中，我们将扩展并进一步验证MT方法，并开发商业质量软件，通过Web和GUI将此方法交付给用户。这将涉及学术实验室和工业实验室之间的合作，开发新的方法实施，以商业化部署该技术，构建基于莫伊的图形用户界面，沿着基于Web的界面，最后与我们的制药合作者一起在现场使用该软件解决基于真实的生命结构的药物发现问题（见支持信）。