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1.
J Phys Chem Lett ; 12(17): 4195-4202, 2021 May 06.
Article in English | MEDLINE | ID: covidwho-1387119

ABSTRACT

The catalytic reaction in SARS-CoV-2 main protease is activated by a proton transfer (PT) from Cys145 to His41. The same PT is likely also required for the covalent binding of some inhibitors. Here we use a multiscale computational approach to investigate the PT thermodynamics in the apo enzyme and in complex with two potent inhibitors, N3 and the α-ketoamide 13b. We show that with the inhibitors the free energy cost to reach the charge-separated state of the active-site dyad is lower, with N3 inducing the most significant reduction. We also show that a few key sites (including specific water molecules) significantly enhance or reduce the thermodynamic feasibility of the PT reaction, with selective desolvation of the active site playing a crucial role. The approach presented is a cost-effective procedure to identify the enzyme regions that control the activation of the catalytic reaction and is thus also useful to guide the design of inhibitors.


Subject(s)
Drug Design , Protease Inhibitors/chemistry , SARS-CoV-2/enzymology , Viral Matrix Proteins/antagonists & inhibitors , Antiviral Agents/chemistry , Antiviral Agents/metabolism , Biocatalysis , COVID-19/pathology , COVID-19/virology , Catalytic Domain , Humans , Molecular Dynamics Simulation , Protease Inhibitors/metabolism , Protons , Quantum Theory , SARS-CoV-2/isolation & purification , Thermodynamics , Viral Matrix Proteins/metabolism
2.
J Phys Chem Lett ; 12(23): 5494-5502, 2021 Jun 17.
Article in English | MEDLINE | ID: covidwho-1258538

ABSTRACT

SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor in practically identical conformations, although several residues of the receptor-binding domain (RBD) differ between them. Herein, we have used molecular dynamics (MD) simulations, machine learning (ML), and free-energy perturbation (FEP) calculations to elucidate the differences in binding by the two viruses. Although only subtle differences were observed from the initial MD simulations of the two RBD-ACE2 complexes, ML identified the individual residues with the most distinctive ACE2 interactions, many of which have been highlighted in previous experimental studies. FEP calculations quantified the corresponding differences in binding free energies to ACE2, and examination of MD trajectories provided structural explanations for these differences. Lastly, the energetics of emerging SARS-CoV-2 mutations were studied, showing that the affinity of the RBD for ACE2 is increased by N501Y and E484K mutations but is slightly decreased by K417N.


Subject(s)
Angiotensin-Converting Enzyme 2/chemistry , Angiotensin-Converting Enzyme 2/metabolism , Machine Learning , Spike Glycoprotein, Coronavirus/chemistry , Spike Glycoprotein, Coronavirus/metabolism , Binding Sites , Humans , Models, Molecular , Molecular Dynamics Simulation
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