Applying Knowledge of Enzyme Biochemistry to the Prediction of Functional Sites for Aiding Drug Discovery

计算生物学 药物发现 功能(生物学) 变构调节 范围(计算机科学) 领域(数学分析) 计算机科学 鉴定(生物学) 过程(计算) 生化工程 生物 生物信息学 生物化学 细胞生物学 工程类 数学分析 操作系统 植物 程序设计语言 数学
作者
Priyadarshini P. Pai,Sukanta Mondal
出处
期刊:Current Topics in Medicinal Chemistry [Bentham Science]
卷期号:17 (21) 被引量:3
标识
DOI:10.2174/1568026617666170329153858
摘要

Enzymes are biological catalysts that play an important role in determining the patterns of chemical transformations pertaining to life. Many milestones have been achieved in unraveling the mechanisms in which the enzymes orchestrate various cellular processes using experimental and computational approaches. Experimental studies generating nearly all possible mutations of target enzymes have been aided by rapid computational approaches aiming at enzyme functional classification, understanding domain organization, functional site identification. The functional architecture, essentially, is involved in binding or interaction with ligands including substrates, products, cofactors, inhibitors, providing for their function, such as in catalysis, ligand mediated cell signaling, allosteric regulation and post-translational modifications. With the increasing availability of enzyme information and advances in algorithm development, computational approaches have now become more capable of providing precise inputs for enzyme engineering, and in the process also making it more efficient. This has led to interesting findings, especially in aberrant enzyme interactions, such as hostpathogen interactions in infection, neurodegenerative diseases, cancer and diabetes. This review aims to summarize in retrospection - the mined knowledge, vivid perspectives and challenging strides in using available experimentally validated enzyme information for characterization. An analytical outlook is presented on the scope of exploring future directions.
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