Discovery of SARS-CoV-2 Mpro peptide inhibitors from modelling substrate and ligand binding. Issue 41 (20th September 2021)

• Record Type: Journal Article
• Authors: Chan, H. T. Henry; Moesser, Marc A.; Walters, Rebecca K.; Malla, Tika R.; Twidale, Rebecca M.; John, Tobias; Deeks, Helen M.; Johnston-Wood, Tristan; Mikhailov, Victor; Sessions, Richard B.; Dawson, William; Salah, Eidarus; Lukacik, Petra; Strain-Damerell, Claire; Owen, C. David; Nakajima, Takahito; Świderek, Katarzyna; Lodola, Alessio; Moliner, Vicent; Glowacki, David R.; Spencer, James; Walsh, Martin A.; Schofield, Christopher J.; Genovese, Luigi; Shoemark, Deborah K.; Mulholland, Adrian J.; Duarte, Fernanda; Morris, Garrett M.
• Is Part Of: Chemical science. Volume 12:Issue 41(2021)
• Page Start: 13686
• Page End: 13703
• Publication Date: 2021-09-20
• Subjects: Chemistry -- Periodicals; 540.5
• DOI: 10.1039/d1sc03628a
• Languages: English
• ISSNs: 2041-6520

Abstract

Abstract : The main protease (M pro ) of SARS-CoV-2 is central to viral maturation and is a promising drug target. In silico methods reveal structural aspects of how it binds to its 11 natural cleavage sites, the design of novel peptide inhibitors, and insights into drug design. Abstract : The main protease (M pro ) of SARS-CoV-2 is central to viral maturation and is a promising drug target, but little is known about structural aspects of how it binds to its 11 natural cleavage sites. We used biophysical and crystallographic data and an array of biomolecular simulation techniques, including automated docking, molecular dynamics (MD) and interactive MD in virtual reality, QM/MM, and linear-scaling DFT, to investigate the molecular features underlying recognition of the natural M pro substrates. We extensively analysed the subsite interactions of modelled 11-residue cleavage site peptides, crystallographic ligands, and docked COVID Moonshot-designed covalent inhibitors. Our modelling studies reveal remarkable consistency in the hydrogen bonding patterns of the natural M pro substrates, particularly on the N-terminal side of the scissile bond. They highlight the critical role of interactions beyond the immediate active site in recognition and catalysis, in particular plasticity at the S2 site. Building on our initial M pro -substrate models, we used predictive saturation variation scanning (PreSaVS) to design peptides with improved affinity. Non-denaturing mass spectrometry and other biophysical analyses confirm these new and effective 'peptibitors' inhibit M pro competitively. Our combined results provide new insights and highlight opportunities for the development of M pro inhibitors as anti-COVID-19 drugs.