Drug Discovery Department, Research & Development Division, PharmaDesign, Inc,, Hatchobori 2-19-8, Chuo-ku, Tokyo, Japan.
BMC Bioinformatics. 2011 Feb 9;12:50. doi: 10.1186/1471-2105-12-50.
The amount of data on protein-protein interactions (PPIs) available in public databases and in the literature has rapidly expanded in recent years. PPI data can provide useful information for researchers in pharmacology and medicine as well as those in interactome studies. There is urgent need for a novel methodology or software allowing the efficient utilization of PPI data in pharmacology and medicine.
To address this need, we have developed the 'Druggable Protein-protein Interaction Assessment System' (Dr. PIAS). Dr. PIAS has a meta-database that stores various types of information (tertiary structures, drugs/chemicals, and biological functions associated with PPIs) retrieved from public sources. By integrating this information, Dr. PIAS assesses whether a PPI is druggable as a target for small chemical ligands by using a supervised machine-learning method, support vector machine (SVM). Dr. PIAS holds not only known druggable PPIs but also all PPIs of human, mouse, rat, and human immunodeficiency virus (HIV) proteins identified to date.
The design concept of Dr. PIAS is distinct from other published PPI databases in that it focuses on selecting the PPIs most likely to make good drug targets, rather than merely collecting PPI data.
近年来,公共数据库和文献中可获取的蛋白质-蛋白质相互作用(PPIs)数据量迅速增加。PPI 数据可以为药理学和医学研究人员以及相互作用组研究人员提供有用的信息。迫切需要一种新的方法或软件,以便在药理学和医学中有效地利用 PPI 数据。
为满足这一需求,我们开发了“可成药蛋白质-蛋白质相互作用评估系统”(Dr. PIAS)。Dr. PIAS 拥有一个元数据库,其中存储了从公共资源中检索到的各种类型的信息(三级结构、药物/化学物质以及与 PPIs 相关的生物学功能)。通过整合这些信息,Dr. PIAS 使用有监督的机器学习方法(支持向量机,SVM)来评估 PPI 是否可作为小分子配体的靶标。Dr. PIAS 不仅包含已知的可成药 PPIs,还包含迄今为止鉴定的人类、小鼠、大鼠和人类免疫缺陷病毒(HIV)蛋白的所有 PPIs。
Dr. PIAS 的设计理念与其他已发表的 PPI 数据库不同,它专注于选择最有可能成为良好药物靶标的 PPIs,而不仅仅是收集 PPI 数据。