Targeting RdRp of SARS-CoV-2 with De Novo Molecule Generation

被引:1
作者
Vijay, Amal [1 ]
Adury, Venkata Sai Sreyas [1 ]
Mukherjee, Arnab [1 ]
机构
[1] Indian Inst Sci Educ & Res, Dept Chem, Pune 411008, India
关键词
drug discovery; molecular dynamics; enhancedsampling; metadynamics; COVID-19; DRUG DISCOVERY; RNA-POLYMERASE; DYNAMICS; MECHANISM; SIMULATIONS; REMDESIVIR;
D O I
10.1021/acsabm.3c00339
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Viruses are known for their extremely high mutation rates,allowingthem to evade both the human immune system and many forms of standardmedicine. Despite this, the RNA dependent RNA polymerase (RdRp) ofthe RNA viruses has been largely conserved, and any significant mutationof this protein is unlikely. The recent COVID-19 pandemic presentsa need for therapeutics. We have designed a de novo drug design algorithmthat generates strong binding ligands from scratch, based on only the structure of the target protein's receptor. In this paper,we applied our method to target SARS-CoV-2 RdRp and generated severalde novo molecules. We then chose some drug molecules based on thestructural similarity to some of our strongest binding de novo molecules.Subsequently, we showed, using rigorous all-atom explicit-water freeenergy calculations in near-microsecond time scales using state-of-the-artwell-tempered metadynamics simulations, that some of our de novo generatedligands bind more strongly to RdRp than the recent FDA approved drugremdesivir in its active form, remdesivir triphosphate (RTP). We elucidatedthe binding mechanism for some of the top binders and compared itwith RTP. We believe that this work will be useful both by presentinglead structures for RdRp inhibition and by delivering key insightsinto the residues of the protein potentially involved in the binding/unbindingof these small molecule drugs, leading to more targeted studies inthe future.
引用
收藏
页码:609 / 616
页数:8
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