An integrated metabolomic and proteomic approach for the identification of covalent inhibitors of the main protease (Mpro) of SARS-COV-2 from crude natural extracts.

Mpro represents one of the most promising drug targets for SARS-Cov-2, as it plays a crucial role in the maturation of viral polyproteins into functional proteins. HTS methods are currently used to screen Mpro inhibitors, and rely on searching chemical databases and compound libraries, meaning that they only consider previously structurally clarified and isolated molecules. A great advancement in the hit identification strategy would be to set-up an approach aimed at exploring un-deconvoluted mixtures of compounds such as plant extracts. Hence, the aim of the present study is to set-up an analytical platform able to fish-out bioactive molecules from complex natural matrices even where there is no knowledge on the constituents. The proposed approach begins with a metabolomic step aimed at annotating the MW of the matrix constituents. A further metabolomic step is based on identifying those natural electrophilic compounds able to form a Michael adduct with thiols, a peculiar chemical feature of many Mpro inhibitors that covalently bind the catalytic Cys145 in the active site, thus stabilizing the complex. A final step consists of incubating recombinant Mpro with natural extracts and identifying compounds adducted to the residues within the Mpro active site by bottom-up proteomic analysis (nano-LC-HRMS). Data analysis is based on two complementary strategies: (i) a targeted search applied by setting the adducted moieties identified as Michael acceptors of Cys as variable modifications; (ii) an untargeted approach aimed at identifying the whole range of adducted peptides containing Cys145 on the basis of the characteristic b and y fragment ions independent of the adduct. The method was set-up and then successfully tested to fish-out bioactive compounds from the crude extract of Scutellaria baicalensis, a Chinese plant containing the catechol-like flavonoid baicalin and its corresponding aglycone baicalein which are well-established inhibitors of Mpro. Molecular dynamics (MD) simulations were carried out in order to explore the binding mode of baicalin and baicalein, within the SARS-CoV-2 Mpro active site, allowing a better understanding of the role of the nucleophilic residues (i.e. His41, Cys145, His163 and His164) in the protein-ligand recognition process.