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Discovery of human coronaviruses pan-papain-like protease inhibitors using computational approaches

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摘要 The papain-like protease(PLpro)is vital for the replication of coronaviruses(Co Vs),as well as for escaping innate-immune responses of the host.Hence,it has emerged as an attractive antiviral drug-target.In this study,computational approaches were employed,mainly the structure-based virtual screening coupled with all-atom molecular dynamics(MD)simulations to computationally identify specific inhibitors of severe acute respiratory syndrome coronavirus 2(SARS-Co V-2)PLpro,which can be further developed as potential pan-PLprobased broad-spectrum antiviral drugs.The sequence,structure,and functional conserveness of most deadly human Co Vs PLprowere explored,and it was revealed that functionally important catalytic triad residues are well conserved among SARS-Co V,SARS-Co V-2,and middle east respiratory syndrome coronavirus(MERS-Co V).The subsequent screening of a focused protease inhibitors database composed of^7,000 compounds resulted in the identification of three candidate compounds,ADM13083841,LMG15521745,and SYN15517940.These three compounds established conserved interactions which were further explored through MD simulations,free energy calculations,and residual energy contribution estimated by MM-PB(GB)SA method.All these compounds showed stable conformation and interacted well with the active residues of SARS-Co V-2 PLpro,and showed consistent interaction profile with SARS-Co V PLproand MERS-Co V PLproas well.Conclusively,the reported SARS-Co V-2 PLprospecific compounds could serve as seeds for developing potent pan-PLprobased broad-spectrum antiviral drugs against deadly human coronaviruses.Moreover,the presented information related to binding site residual energy contribution could lead to further optimization of these compounds.
出处 《Journal of Pharmaceutical Analysis》 SCIE CAS CSCD 2020年第6期546-559,共14页 药物分析学报(英文版)
基金 the Starting Research Grant for High-level Talents from Guangxi University the Postdoctoral Project from Guangxi University。
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