Addressing biomedical challenges with computational mechanics and big data

利用计算力学和大数据解决生物医学挑战

基本信息

批准号：
10612892
负责人：
RUBEN ABAGYAN
金额：
$ 38.43万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-05-01 至 2024-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10612892
关键词：
3-Dimensional Address Algorithms Amebiasis Antiviral Agents Area Big Data Bioinformatics Biological Biological Process Biological Response Modifier Therapy Cells Collaborations Complex Crystallography Data Disease Disease model Docking Drug Design Drug Targeting Drug resistance Head Health Sciences Homology Modeling Hookworms Human Institution Laboratories Laboratory Research Leishmaniasis Ligands Mass Spectrum Analysis Mechanics Methods Modeling Molecular Mechanisms of Action Molecular Structure National Center for Research Resources Pathway interactions Pharmaceutical Chemistry Pharmacologic Substance Pharmacology Pharmacy Schools Publishing Schistosomiasis Science Structural Models Systems Biology Therapeutic Trypanosomiasis United States National Institutes of Health Work biomacromolecule cancer genomics chemokine receptor drug action drug repurposing flexibility human disease medical schools molecular mechanics novel drug combination novel therapeutics programs resistance mutation screening therapeutic candidate

项目摘要

PROJECT SUMMARY The objective of this project is to develop better algorithms for molecular mechanics and flexible docking, incorporate new data, and use the methods to expand the set of three-dimensional atomic models of bio-macromolecules and their ligand complexes with predicted parts and homology models. These models will be used to identify new therapeutic candidates and predict mechanism of action of drugs. Since 2007 we collaborated and published with over sixty research laboratories and used structural models to understand biological function and therapeutic action. We will work in close collaboration with several laboratories at Skaggs School of Pharmacy and Pharmaceutical Sciences, UCSD, UCSD Medical School, Bioinformatics and Systems Biology Program at UCSD and several US Institutions. The SSPPS collaborators include Tracy Handel (chemokine receptors), James McKerrow (head of CDIPD center), Larissa Podust (crystallography, CDIPD), Conor Caffrey (schistosomiasis, hookworms), Jair L. Siqueira-Neto (HTS core, trypanosomiasis, leishmaniasis, antivirals), Anjan Debnath (amebiasis), Carlo Ballatore and Dionicio Siegel (medicinal chemistry) . Nuno Bandeira and Pieter Dorrestein (NIH/NCRR Center for Computational Mass Spectrometry), will help with incorporating or generating mass spectrometry data. We will also work on new treatments for several diseases, molecular mechanisms of action, and probes for new disease related pathways with the laboratories from UCSD Health Sciences Departments (Silvio Gutkind, Joseph Califano, Don Durden, Nunzio Bottini, Olivier Harismendy - oncogenomics, Pavel Pevzner, Lev Tsimring) and several US laboratories (Mark Yeager, UVa, Irina Artsimovich, OHSU, Andrei Osterman, SBP- Med.Res.Institute, Eric Debler, Jefferson Uni.). Better methods, better models, better data will help with new probes for disease-related pathways, drug repurposing and designing new drug combinations, understanding drug- resistance mutations, and understanding multi-target drug pharmacology. We will make all the data and programs produced during the project publicly available.

项目摘要该项目的目的是为分子开发更好的算法力学和灵活的对接，合并新数据，并使用这些方法扩展生物大分子的三维原子模型和他们的配体配合物具有预测的零件和同源模型。这些模型将用于识别新的治疗候选者并预测药物作用机理。自2007年以来，我们与超过60个研究实验室，并使用结构模型来了解生物功能和治疗作用。我们将在密切合作中工作在Skaggs药房和药学学院有几个实验室科学，UCSD，UCSD医学院，生物信息学和系统生物学在UCSD和美国几家机构的计划。 SSPPS合作者包括 Tracy Handel（趋化因子受体），James McKerrow（CDIPD中心负责人）， Larissa Podust（晶体学，CDIPD），Conor Caffrey（血吸虫病，，钩虫），Jair L. Siqueira-Neto（HTS核心，锥虫病，Leishmaniasis，抗病毒药），Anjan Debnath（Amebiasis），Carlo Ballatore和Dionicio Siegel （药物化学）。 Nuno Bandeira和Pieter Dorrestein（NIH/NCRR中心对于计算质谱法），将有助于合并或生成质谱数据。我们还将为几个疾病，作用的分子机制以及与新疾病有关的探针来自UCSD健康科学部门的实验室的途径（Silvio Gutkind，Joseph Califano，Don Durden，Nunzio Bottini，Olivier Harismendy- 致癌基因组学，Pavel Pevzner，Lev Tsimring）和几个美国实验室（Mark Yeager，UVA，Irina Artsimovich，OHSU，Andrei Osterman，SBP- Med.Res.Institute，Eric Debler，Jefferson Uni。）。更好的方法，更好的模型，更好的数据将有助于疾病相关途径，药物的新探针重新利用和设计新药组合，了解药物 - 抗性突变，并了解多目标药物学。我们将公开制作项目期间生产的所有数据和程序可用的。