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Comput Struct Biotechnol J . Structural Insight into the Recognition of S-Adenosyl-L-Homocysteine and Sinefungin in SARS-CoV-2 Nsp16/Nsp10 RNA Cap 2

tetano

Editor, Senior Moderator
Comput Struct Biotechnol J


. 2020 Oct 1.
doi: 10.1016/j.csbj.2020.09.032. Online ahead of print.
Structural Insight into the Recognition of S-Adenosyl-L-Homocysteine and Sinefungin in SARS-CoV-2 Nsp16/Nsp10 RNA Cap 2'-O-Methyltransferase


Panupong Mahalapbutr[SUP] 1 [/SUP], Napat Kongtaworn[SUP] 2 [/SUP], Thanyada Rungrotmongkol[SUP] 2 3 [/SUP]



Affiliations

Abstract

The recent ongoing coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to rapidly spread across the world. To date, neither a specific antiviral drug nor a clinically effective vaccine is available. Among the 15 viral non-structural proteins (nsps), nsp16 methyltransferase has been considered as a potential target due to its crucial role in RNA cap 2'-O-methylation process, preventing the virus detection by cell innate immunity mechanisms. In the present study, molecular recognition between the two natural nucleoside analogs (S-adenosyl-L-homocysteine (SAH) and sinefungin (SFG)) and the SARS-CoV-2 nsp16/nsp10/[SUP]m7[/SUP]G[SUB]ppp[/SUB]AC[SUB]5[/SUB] was studied using all-atom molecular dynamics simulations and free energy calculations based on MM/GBSA and WaterSwap approaches. The binding affinity and the number of hot-spot residues, atomic contacts, and H-bond formations of the SFG/nsp16 complex were distinctly higher than those of the SAH/nsp16 system, consistent with the lower water accessibility at the enzyme active site. Notably, only SFG could electrostatically interact with the 2'-OH and N3 groups of RNA's adenosine moiety, mimicking the methyl transfer reaction of S-adenosyl-L-methionine substrate. The atomistic binding mechanism obtained from this work paves the way for further optimizations and designs of more specific SARS-CoV-2 nsp16 inhibitors in the fight against COVID-19.

Keywords: COVID-19; MD simulations; SARS-CoV-2; nsp16/nsp10; nucleoside analog; rational drug design.
 
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