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作 者:Mingyu Li Xiaobin Lan Xun Lu Jian Zhang
机构地区:[1]College of Pharmacy,Ningxia Medical University,Yinchuan,NingxiaHui Autonomous Region,China. [2]State Key Laboratory of Medical Genomics,National Research Center for Translational Medicine at Shanghai,Ruijin Hospital,Shanghai Jiao Tong University School of Medicine,Shanghai,China. [3]Medicinal Chemistry and Bioinformatics Center,Shanghai Jiao Tong University School of Medicine,Shanghai 200025,China.
出 处:《Health Data Science》2023年第1期90-101,共12页健康数据科学(英文)
基 金:the Shanghai Jiao Tong University School of Medicine and Ningxia Medical University for their support of this research project.Funding:This research was supported in part by grants from the National Key R&D Program of China(2022YFF1203005);the National Natural Science Foundation of China(22077082,21778037,81925034,91753117,and 81721004);the Innovation Program of Shanghai Municipal Education Commission(2019-01-07-00-01-E00036,China);the Shanghai Science and Technology Innovation(19431901600,China);the Shanghai Health and Family Planning System Excellent Subject Leader and Excellent Young Medical Talents Training Program(2018BR12,China).
摘 要:Importance:Allosteric drugs bound to topologically distal allosteric sites hold a substantial promise in modulating therapeutic targets deemed undruggable at their orthosteric sites.Traditionally,allosteric modulator discovery has predominantly relied on serendipitous high-throughput screening.Nevertheless,the landscape has undergone a transformative shift due to recent advancements in our understanding of allosteric modulation mechanisms,coupled with a significant increase in the accessibility of allosteric structural data.These factors have extensively promoted the development of various computational methodologies,especially for machine-learning approaches,to guide the rational design of structure-based allosteric modulators.Highlights:We here presented a comprehensive structure-based allosteric modulator design paradigm encompassing 3 critical stages:drug target acquisition,allosteric binding site,and modulator discovery.The recent advances in computational methods in each stage are encapsulated.Furthermore,we delve into analyzing the successes and obstacles encountered in the rational design of allosteric modulators.Conclusion:The structure-based allosteric modulator design paradigm holds immense potential for the rational design of allosteric modulators.We hope that this review would heighten awareness of the use of structure-based computational methodologies in advancing the field of allosteric drug discovery.
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