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Computational chemical biology and drug design: Facilitating protein structure, function, and modulation studies
Author(s) -
Zheng Mingyue,
Zhao Jihui,
Cui Chen,
Fu Zunyun,
Li Xutong,
Liu Xiaohong,
Ding Xiaoyu,
Tan Xiaoqin,
Li Fei,
Luo Xiaomin,
Chen Kaixian,
Jiang Hualiang
Publication year - 2018
Publication title -
medicinal research reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.868
H-Index - 130
eISSN - 1098-1128
pISSN - 0198-6325
DOI - 10.1002/med.21483
Subject(s) - function (biology) , computer science , field (mathematics) , chemical biology , computational biology , drug discovery , computational model , systems biology , structural biology , mechanism (biology) , biochemical engineering , management science , biology , bioinformatics , physics , engineering , artificial intelligence , microbiology and biotechnology , biochemistry , mathematics , pure mathematics , quantum mechanics
Over the past quarter of a century, there has been rapid development in structural biology, which now can provide solid evidence for understanding the functions of proteins. Concurrently, computational approaches with particular relevance to the chemical biology and drug design (CBDD) field have also incrementally and steadily improved. Today, these methods help elucidate detailed working mechanisms and accelerate the discovery of new chemical modulators of proteins. In recent years, integrating computational simulations and predictions with experimental validation has allowed for more effective explorations of the structure, function and modulation of important therapeutic targets. In this review, we summarize the main advancements in computational methodology development, which are then illustrated by several successful applications in CBDD. Finally, we conclude with a discussion of the current major challenges and future directions in the field.