Identifying Genetic Contributions to Adverse Drug Reactions

确定遗传因素对药物不良反应的影响

基本信息

批准号：
10730434
负责人：
SCOTT M REED
金额：
$ 46.79万
依托单位：
UNIVERSITY OF COLORADO DENVER
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-09-01 至 2026-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10730434
关键词：
6-Mercaptopurine Adopted Affect Affinity Arylesterase Back Binding Binding Sites Chemical Structure Clinical Clinical Data Clinical Trials Communities Darkness Data Data Set Databases Docking Dose Drug Binding Site Drug Design Drug Interactions Drug Side Effects Drug toxicity Enzymes Event Frequencies Genetic Genetic Polymorphism Genetic Variation Genome Goals Gulf War veteran Homology Modeling Immunosuppressive Agents In Vitro Individual Lead Literature Machine Learning Marketing Methods Modeling Molecular Mutate Mutation Pattern Pharmaceutical Preparations Pharmacogenetics Pharmacogenomics Pharmacologic Substance Physiological Population Process Proteins Research Research Personnel Screening procedure Single Nucleotide Polymorphism Sorting Source Speed Structure System Training Variant adverse drug reaction bioinformatics tool chemotherapeutic agent design drug repurposing drug sensitivity drug structure drug withdrawal genetic variant improved in silico nerve agent novel novel therapeutics protein structure rapid testing response side effect small molecule thiopurine thiopurine methyltransferase three dimensional structure tool web app web-based tool

项目摘要

Identifying Genetic Contributions to Adverse Drug Reactions Project Summary Bioinformatics tools will be created that facilitate searching the genome for variants that can elucidate previously unexplained adverse drug reactions (ADRs). Known protein targets for pharmaceuticals represent only a few percent of the genome and this is a missed opportunity in drug design and in finding genetic explanations for ADRs. We are seeking to create new bioinformatics tools for identifying the off-target binding sites of pharmaceuticals and their metabolites. Our goal is to build tools that help identify the underlying genetic causes of rare and unexplained ADRs so these effects can be avoided. Our initial focus will be on very large existing data sets on genetic variation and on ADRs that are currently not linked to identify possible new connections between the datasets. The first specific aim is to create a docking server using the best available protein structures so that variants of any protein can be used in docking studies and be examined as a source of possible side effects expanding into the dark genome. The second specific aim is to create online tools that identify specific ADRs and produce the three-dimensional structures of drugs and drug metabolites prepared for docking studies and create fast screening tools. Together these tools can be used by researchers to prioritize drug protein interactions for further in silico or in vitro studies. These tools will facilitate rapid testing of hypotheses about molecular causes of harmful drug side effects in both available drugs and drugs being designed today, a critical step toward eliminating ADRs and designing more effective drugs.

确定遗传因素对药物不良反应的影响项目概要将创建生物信息学工具，以促进在基因组中搜索可以先前阐明的变异无法解释的药物不良反应（ADR）。已知的药物蛋白质靶点仅代表其中的一小部分基因组的百分比，这在药物设计和寻找基因解释方面错失了机会美国存托凭证。我们正在寻求创建新的生物信息学工具来识别脱靶结合位点药物及其代谢物。我们的目标是构建有助于识别潜在遗传原因的工具罕见和无法解释的 ADR，因此可以避免这些影响。我们最初的重点将是现有的非常大的目前尚未链接到有关遗传变异和 ADR 的数据集，以识别可能的新联系数据集之间。第一个具体目标是使用最佳可用蛋白质创建对接服务器结构，以便任何蛋白质的变体都可以用于对接研究，并作为可能的来源进行检查副作用扩展到黑暗基因组。第二个具体目标是创建在线工具来识别特定的ADR并产生药物和药物代谢物的三维结构以供对接研究并创建快速筛选工具。研究人员可以一起使用这些工具来确定药物蛋白的优先顺序相互作用以进行进一步的计算机或体外研究。这些工具将有助于快速检验关于以下方面的假设现有药物和当今正在设计的药物中有害药物副作用的分子原因，一个关键朝着消除 ADR 和设计更有效的药物迈出了一步。