Pre-computed free energy maps for rapid structure-based ligand design

预先计算的自由能图，用于快速基于结构的配体设计

• 批准号: 8832859
• 负责人: ALEXANDER D MACKERELL
• 金额: $ 15.72万
• 依托单位: SILCSBIO, LLC
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-03-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8832859
• 关键词: Address; Affinity; Binding; Binding Sites; Chemicals; Computer Assisted; Computer software; Computing Methodologies; Data; Data Set; Databases; Development; Disease; Drug Design; Elements; Emerging Technologies; Environment; Evaluation; Foundations; Free Energy; Generations; Goals; Hot Spot; Housing; Imagery; Lead; Licensing; Ligand Binding; Ligands; Maps; Marketing; Membrane Proteins; Methodology; Methods; Modeling; Modification; Outcome; Performance; Pharmaceutical Preparations; Pharmacologic Substance; Phase; Probability; Process; Production; Proteins; Quantitative Evaluations; RNA; Reading; Relative (related person); Reporting; Reproduction; Research Contracts; Research Infrastructure; Research Proposals; Sales; Site; Small Business Innovation Research Grant; Solutions; Structure; Surface; Technology; Time; Toxicology; Validation; Vendor; Work; aqueous; base; commercial application; commercialization; computational chemistry; computer cluster; cost; design; drug development; drug discovery; flexibility; functional group; graphical user interface; improved; interest; macromolecule; molecular dynamics; novel; novel strategies; novel therapeutics; open source; pharmacophore; preconditioning; protein complex; protein structure; public health relevance; scaffold; screening; simulation; solute; success

DESCRIPTION (provided by applicant): In the proposed study, a novel approach which has already generated multiple commercial sales for SilcsBio, LLC, Site-Identification by Ligand Competitive Saturation (SILCS), will be further developed to address customer requests and concerns around SILCS utility. Successful commercial application of computational methods for ligand design require a platform that provides both qualitative data to direct the design process and rapid production of quantitative data to allow for rigorous evaluation of specific ligand possibilities Both of those attributes form the core of SILCS technology. However, it is necessary to extend the SILCS technology to be accessible to a wide range of computational software packages and to be readily used in database screenings. Most importantly, while customers report large improvements in predictive capacity using SILCS technology (reduced time to lead from 12 months to 6 months, identification of unique scaffolds for an 'undruggable" target, better matches of scoring to actual performance), modest improvements in accuracy are requested by customers in order to have a large impact on the development of new therapeutics. For a given target, SILCS involves a one-time up-front preconditioning step where the target protein, RNA or any macromolecule target of interest, in the absence of any drug-like ligands, is immersed in an aqueous solution of small organic solutes and subjected to exhaustive molecular dynamics (MD) simulations. From these simulations 3D probability distributions of different chemical functional classes on the entire surface of the target are generated based on rigorous free energy criteria, including protein flexibility. These probability distributions are then converted to free energies based on a Boltzmann distribution yielding "Grid Free Energies (GFE)." The probability distributions are normalized with respect to the organic solutes in pure aqueous solution, such that the GFEs include energetic contributions from desolvation of both the solutes and the protein surface, as well as interactions of the solutes with the protein. The GFE distributions, termed FragMaps, may then be used in a qualitative fashion to identify regions on the protein surface that interact favorably with differet classes of functional groups ("hot spots"), thereby directing ligand design. The GFEs may also be used to estimate ligand relative free energies of binding thereby facilitating quantitative evaluation of specific design outcomes. As the SILCS method is based on one-time preconditioning simulations of the target molecule, a process that can be completed in several days on commodity computer clusters, the quantitative free energy binding estimates based on the FragMaps can be performed on large numbers of compounds in a matter seconds allowing for wide ranges of ligand modifications to be evaluated. Specific goals for the proposed SBIR include 1) extending SILCS technology and GFE FragMaps to formats accessible to computational chemistry software packages, 2) improving the accuracy of SILCS GFE FragMaps and 3) extending SILCS GFEs for use in database screening. Success of the Phase I aspect of the proposal will be based on the following milestones: i) SILCS computational platform: Ability to generate, read and visualize SILCS GFE FragMaps using publically and commercially available computational chemistry software, 2) SILCS accuracy: Improved prediction of relative binding energies of known ligand-protein complexes, and 3) SILCS database screening: Ability to identify known ligands from database screening using pharmacophore models based on SILCS GFEs. Commercialization of these substantial improvements to the SILCS technology will occur through SilcsBio's existing marketing channels which include partnering with computational chemistry software vendors to make the technology available for licensing for in-house use by pharmaceutical companies and SilcsBio acting as a contract research organization (CRO) performing structure-based ligand design. CRO work includes supplying and interpreting GFE FragMaps to customers, a product that can, importantly, be supplied without customers revealing their IP as the Fragmaps are generated in the absence of ligands. Successful completion of this Phase I proposal is anticipated to lay the foundation for a Phase II SBIR to improve and expand the SILCS platform by 1) extending the technology to occluded target ligand binding sites not accessible to the surrounding aqueous environment, such as those commonly found in many GPCRs, 2) extending SILCS into a product that will be marketable for in-house use by pharmaceutical companies and 3) developing the necessary infrastructure required for SilcsBio to be a successful CRO.

描述（由申请人提供）：在拟议的研究中，一种新型方法已经为Silcsbio，LLC产生了多个商业销售，将进一步开发出配体竞争饱和（SILC）的现场识别，以解决围绕Silcs公用事业的客户要求和疑虑。配体设计的计算方法的成功商业应用需要一个平台，该平台既提供定性数据，又可以引导设计过程和快速生产定量数据，以允许对特定配体可能性进行严格的评估，这两种属性构成了SILCS技术的核心。但是，有必要扩展SILCS技术，以便在广泛的计算软件包中访问，并很容易在数据库筛选中使用。最重要的是，虽然客户使用SILCS技术报告了预测能力的巨大提高（减少了12个月到6个月的时间，确定了“不可能”目标的独特脚手架，更好地得分与实际绩效的更好匹配），而准确性的适度提高是由客户要求的，以便对新的目标产生很大的影响。 RNA或任何感兴趣的大分子靶标在没有任何药物的情况下，都会浸入小的有机溶液的水溶液中，并从这些模拟中进行详尽的分子动力学（MD）模拟。基于玻尔兹曼的分布，产生了“网格自由能（GFE）”。然后可以以定性方式使用GFE分布，称为fragmaps，以识别蛋白质表面上与不同类别的官能团（“热点”）相互作用的区域，从而指导配体设计。 GFE还可以用于估计结合的配体相对自由能，从而促进对特定设计结果的定量评估。由于SILCS方法是基于目标分子的一次性预处理模拟，该过程可以在几天内在商品计算机簇上完成，因此可以基于片段的定量自由能结合估计值可以在大量化合物上进行大量化合物，从而允许在一件事上进行宽泛的修饰范围，以评估凸尺的范围。拟议的SBIR的具体目标包括1）将SILCS技术和GFE Fragmap扩展到可访问计算化学软件软件包的格式，2）提高SILCS GFE GFE Fragmaps的准确性，3）扩展SILCS GFES用于数据库筛选。 Success of the Phase I aspect of the proposal will be based on the following milestones: i) SILCS computational platform: Ability to generate, read and visualize SILCS GFE FragMaps using publically and commercially available computational chemistry software, 2) SILCS accuracy: Improved prediction of relative binding energies of known ligand-protein complexes, and 3) SILCS database screening: Ability to identify known ligands from database screening using基于SILCS GFE的药效团模型。 SILCS技术的这些重大改进的商业化将通过Silcsbio现有的营销渠道进行，其中包括与计算化学软件软件供应商合作，以使该技术可用于制药公司和Silcsbio在内部使用的技术，并用作合同研究组织（CRO）的表现基于结构结构的配件设计。 CRO的工作包括向客户提供和解释GFE Fragmaps，该产品重要的是，可以在不透露其IP的情况下提供该产品，因为在没有配体的情况下会生成fragmaps。 预计该阶段I阶段的成功完成将为II阶段SBIR奠定基础，以改善和扩展SILCS平台1）将技术扩展到闭塞的目标配体结合位点，无法访问周围水性环境，例如在许多GPCR中常见的水性环境，例如将其延伸到产品中，并将其延伸到Prongruct of Prongruct and formace Companial，并将其用于封装的公司。 Silcsbio是成功的Cro。