Non-covalent SARS-CoV-2 Mpro inhibitors developed from in silico screen hits.

Mpro, the main protease of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is essential for the viral life cycle. Accordingly, several groups have performed in silico screens to identify Mpro inhibitors that might be used to treat SARS-CoV-2 infections. We selected more than five hundred compounds from the top-ranking hits of two very large in silico screens for on-demand synthesis. We then examined whether these compounds could bind to Mpro and inhibit its protease activity. Two interesting chemotypes were identified, which were further evaluated by characterizing an additional five hundred synthesis on-demand analogues. The compounds of the first chemotype denatured Mpro and were considered not useful for further development. The compounds of the second chemotype bound to and enhanced the melting temperature of Mpro. The most active compound from this chemotype inhibited Mpro in vitro with an IC50 value of 1 µM and suppressed replication of the SARS-CoV-2 virus in tissue culture cells. Its mode of binding to Mpro was determined by X-ray crystallography, revealing that it is a non-covalent inhibitor. We propose that the inhibitors described here could form the basis for medicinal chemistry efforts that could lead to the development of clinically relevant inhibitors.

Modelling the structural and reactivity landscapes of tucatinib with special reference to its wavefunction-dependent properties and screening for potential antiviral activity.

HER-2 type breast cancer is one of the most aggressive malignancies found in women. Tucatinib is recently developed and approved as a potential medicine to fight this disease. In this manuscript, we present the gross structural features of this compound and its reactivity and wave function properties using computational simulations. Density functional theory was used to optimise the ground state geometry of the molecule and molecular docking was used to predict biological activity. As the electrons interact with electromagnetic radiations, electronic excitations between different energy levels are analysed in detail using time-dependent density functional theory. Various intermolecular and intermolecular interactions are analysed and reaction sites for attacking electrophiles and nucleophiles identified. Information entropy calculations show that the compound is inherently stable. Docking with COVID-19 proteins show docking score of - 9.42, - 8.93, - 8.45 and - 8.32 kcal/mol respectively indicating high interaction between the drug and proteins. Hence, this is an ideal candidate to study repurposing of existing drugs to combat the pandemic.