Computational chemical biology and drug design: Facilitating protein structure, function, and modulation studies. Issue 3 (11th January 2018)

• Record Type: Journal Article
• Authors: Zheng, Mingyue; Zhao, Jihui; Cui, Chen; Fu, Zunyun; Li, Xutong; Liu, Xiaohong; Ding, Xiaoyu; Tan, Xiaoqin; Li, Fei; Luo, Xiaomin; Chen, Kaixian; Jiang, Hualiang
• Editors: Tang, Xinjing; Wang, Shaoru
• Is Part Of: Medicinal research reviews. Volume 38:Issue 3(2018)
• Page Start: 914
• Page End: 950
• Publication Date: 2018-01-11
• Subjects: ADMET -- chemical biology -- drug design -- in silico -- lead optimization -- molecular dynamics -- polypharmacology -- virtual screening; Pharmacology -- Periodicals; Drugs -- Research -- Periodicals; 615
• DOI: 10.1002/med.21483
• Languages: English
• ISSNs: 0198-6325

Abstract

Abstract: 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.