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ADFR: A Modular Software Framework for Docking into Flexible Receptors

ADFR：用于对接灵活受体的模块化软件框架

基本信息

批准号：
9239951
负责人：
MICHEL F. SANNER
金额：
$ 39.66万
依托单位：
SCRIPPS RESEARCH INSTITUTE, THE
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-04-15 至 2020-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9239951
关键词：
Accounting Area Automated Abstracting Award Benchmarking Binding Binding Sites Biochemical Pathway Biological Biological Process Biomedical Research Cells Chemicals Clinical Research Communities Computer software Computers Data Set Descriptor Development Disease Docking Documentation Drug Design Environment Funding Infection Lead Life Ligand Binding Ligands Maintenance Malignant Neoplasms Metabolic Diseases Methods Modeling Molecular Molecular Conformation Motion Neighborhoods Pathway interactions Peptides Performance Pharmaceutical Preparations Proteins Research Research Support Resolution Scheme Scientist Side Software Engineering Software Framework Speed Staging Techniques Testing Torsion Training Translational Research Trees Vertebral column Weight Writing base computerized tools design flexibility graphical user interface improved insight interest macromolecule method development molecular assembly/self assembly novel novel therapeutic intervention object motion open source programs receptor research study response screening simulation software development success therapeutic target tool virtual

项目摘要

Project Summary/Abstract Automated docking is an important tool for gaining a mechanistic understanding of the molecular interactions underpinning most biological processes. It supports biomedical applications ranging from drug and chemical probes design to investigating chemical pathways and identifying therapeutic targets for diseases such as cancer and metabolic disorders. Two major challenges for automated docking remain the conformational changes occurring in macromolecules upon ligand binding and the docking highly flexible ligands such as peptides, an area that has gained a lot of interest recently. Most docking programs use rigid models of macromolecules because of the exponential increase of computational complexity and the decreased docking accuracy associated receptor flexibility. Under the previous award, we made significant progress towards docking with flexible receptors. We developed and released a software program allowing the successful cross- docking of flexible ligands into apo conformations of receptors with up to 14 flexible side-chains, and demonstrated that down-weighting the contribution of the receptor internal energy to the scoring function increased docking success rates. For the next award, we propose to: 1) extend the set of motion objects for describing ligand conformational changes beyond rotatable bonds, and motion objects for representing local and global receptor backbone motions such as flexible loops and domain motions; 2) enhance our current search technique and develop a new representation and associate search technique for docking peptides; 3) calibrate and optimize the scoring function sused during docking specifically in the context of docking with receptor flexibility; and 4) make the software useful and usable through clearly written documentation and intuitive graphical user interfaces. Datasets compiled under this project will also be made freely available to the community and provide a benchmark for evaluating docking methods. This Open-Source software development project will be based on best practices in software engineering and result in a modular, component-based software environment with pluggable search techniques and scoring functions, and an extensible set of molecular flexibility descriptors. This new docking engine will be part of the widely used and popular software suite AutoDock. It will be used on the World Community Grid for large virtual screens on therapeutically important targets. The ability to include receptor flexibility in docking simulations will extend the range of biological problems for which automated docking can be successfully applied. Hence, it will impact the research of many medicinal chemists and biologist, and extend the use of computational tools to a wider community of scientists thereby supporting the advancement of biomedical research.

项目总结/文摘