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

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:
9354499
负责人:
Sirish Kaushik Lakkaraju
金额:
$64.13万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-03-01 至 2018-08-31

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R43 GM109635 Pre-computed free energy maps for rapid structure-based ligand design. Project Summary Successful commercial application of computational methods for ligand design requires a platform that provides both qualitative data to direct the design process and rapid production of quantitative data to allow for evaluation of specific ligand possibilities. In the proposed study a novel approach, Site- Identification by Ligand Competitive Saturation (SILCS), will be further developed to improve its utility as such a platform in the context of the emerging computational chemistry company SilcsBio LLC. SILCS involves a one-time up-front pre-conditioning step where the protein, RNA or any macromolecular target is subjected to molecular dynamics (MD) simulations in an aqueous solution of small organic solutes that, following normalization and Boltzmann transformation, yields 3D Grid Free Energy (GFE) probability distributions, or GFE FragMaps, that encompass the entire target and may be used for both qualitative and quantitative ligand design approaches. Building upon our successes in the Phase I SBIR, this Phase II proposal will focus on development of tools to facilitate the application of SILCS to ligand design, further improving the accuracy of the methodology, and the extension of the technology to the prediction of macromolecular interactions, including protein-protein interactions. Aim 1 is the development of tools to perform a wide range of chemical transformations allowing for rapid, seamless quantitative evaluation of the 3D interaction of 1000s of ligands with a target on a daily basis. The tools will be integrated with the existing CHARMM General Force Field program to also provide fragment-based design capabilities for the development of novel chemical IP. Aim 2 is improvement in accuracy by: adding long-range electrostatics to our oscillating μex Grand-Canonical Monte Carlo (GCMC) technology that already successfully samples deep or occluded pockets such as in GPCRs and nuclear receptors; enhancing conformational sampling of the target protein by Hamiltonian Replica Exchange MD methods (HREMD); including electronic polarizability by using the classical Drude polarizable force field for calculation of SILCS GFE FragMaps; and improved conformational sampling of ligands in the field of the GFE FragMaps. Aim 3 will take advantage of the information encoded in the GFE FragMaps to develop a macromolecular docking utility that will account for monomer conformational heterogeneity during docking of one macromolecule with another, for the prediction of the 3D structure of complexes consisting of, for example, two or more proteins. Meeting the milestones associated with these scientific Aims will directly further our commercialization strategy for SilcsBio LLC by enhancing the value associated with all three of the major business Aims: 1) direct delivery of SILCS GFE FragMaps and/or the SILCS software directly to ligand-design (e.g. pharmaceutical) companies for in-house use, 2) partnering with computational chemistry software vendors to make the SILCS technology accessible to a wider range of ligand-design companies and 3) SilcsBio LLC acting as a contract research organization (CRO) performing structure-based ligand design.
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