Identification of Some Dietary Flavonoids as Potential Inhibitors of TMPRSS2 Through Protein-ligand Interaction Studies and Binding Free Energy Calculations

The alarming increase in COVID-19 cases and deaths calls for an urgent cost-effective pharmacological approach. Here, we examine the inhibitory activity of a group of dietary bioactive flavonoids against the human protease TMPRSS2, which plays a major role in SARS CoV-2 viral entry. After the molecular docking studies of a large number of flavonoids, four compounds with high binding scores were selected and studied in detail. The binding affinities of these four ligands, Amentoflavone, Narirutin, Eriocitrin, and Naringin, at the active site of TMPRSS2 target were investigated using MD simulations followed by MM-PBSA binding energy calculations. From the studies, a number of significant hydrophobic and hydrogen bonding interactions between the ligands and binding site amino residues of TMPRSS2 are identified which showcase their excellent inhibitory activity against TMPRSS2. Among these ligands, Amentoflavone and Narirutin showed MM-PBSA binding energy values of -155.48 and -138.13 kJ/mol respectively. Our previous studies of the inhibitory activity of these compounds against main protease of SARS-COV2 and the present study on TMPRSS2 strongly highlighted that Amentoflavone and Naringin can exhibit promising multi-target activity against SARS-CoV-2. Moreover, due to their wide availability, no side effects and low cost, these compounds could be recommended as dietary supplements for COVID patients or for the development of SARS-CoV-2 treatments.

Large Scale Study of Ligand-Protein Relative Binding Free Energy Calculations: Actionable Predictions from Statistically Robust Protocols

The accurate and reliable prediction of protein-ligand binding affinities can play a central role in the drug discovery process as well as in personalised medicine. Of considerable importance during lead optimisation are the alchemical free energy methods that furnish estimation of relative binding free energies (RBFE) of similar molecules. Recent advances in these methods have increased their speed, accuracy and precision. This is evident from the increasing number of retrospective as well as prospective studies employing them. However, such methods still have limited applicability in real-world scenarios due to a number of important yet unresolved issues. Here, we report the findings from a large dataset comprising over 500 ligand transformations spanning over 300 ligands binding to a diverse set of 14 different protein targets which furnish statistically robust results on the accuracy, precision and reproducibility of RBFE calculations. We use ensemble-based methods which are the only way to provide reliable uncertainty quantification given that the underlying molecular dynamics is chaotic. These are implemented using TIES (Thermodynamic Integration with Enhanced Sampling) but are equally applicable to free energy perturbation calculations for which we expect essentially very similar results. Results achieve chemical accuracy in all cases. Ensemble simulations also furnish information on the statistical distributions of the free energy calculations which exhibit non-normal behaviour. We find that the “enhanced sampling” method known as replica exchange with solute tempering degrades RBFE predictions. We also report definitively on numerous associated alchemical factors including the choice of ligand charge method, flexibility in ligand structure and the size of the alchemical region including the number of atoms involved in transforming one ligand into another. Our findings provide a key set of recommendations that should be adopted for the reliable application of RBFE methods.

Compared with SARS-CoV2 wild type's spike protein, the SARS-CoV2 omicron's receptor binding motif has adopted a more SARS-CoV1 and/or bat/civet-like structure.

Our study focuses on free energy calculations of SARS-Cov2 spike protein receptor binding motives (RBMs) from wild type and variants-of-concern with particular emphasis on currently emerging SARS- CoV2 omicron variants of concern (VOC). Our computational free energy analysis underlines the occurrence of positive selection processes that specify omicron host adaption and bring changes on the molecular level into context with clinically relevant observations. Our free energy calculations studies regarding the interaction of omicron's RBM with human ACE2 shows weaker binding to ACE2 than alpha's, delta's, or wild type's RBM. Thus, less virus is predicted to be generated in time per infected cell. Our mutant analyses predict with focus on omicron variants a reduced spike-protein binding to ACE2--receptor protein possibly enhancing viral fitness / transmissibility and resulting in a delayed induction of danger signals as trade-off. Finally, more virus is produced but less per cell accompanied with delayed Covid-19 immunogenicity and pathogenicity. Regarding the latter, more virus is assumed to be required to initiate inflammatory immune responses.

Insight into the Binding Energetics of Targeted Reversible Covalent Inhibitors of the SARS-CoV-2 Main Protease

The main protease (Mpro) of the SARS-CoV-2 virus is an attractive therapeutic target for developing antivirals to combat COVID-19. Mpro is essential for the replication cycle of the SARS-CoV-2 virus, so inhibiting Mpro blocks a vital piece of the cell replication machinery of the virus. A promising strategy to disrupt the viral replication cycle is to design inhibitors that bind to the active site cysteine (Cys145) of the Mpro. Cysteine targeted covalent inhibitors are gaining traction in drug discovery owing to the benefits of improved potency and extended drug-target engagement. An interesting aspect of these inhibitors is that they can be chemically tuned to form a covalent, but reversible bond, with their targets of interest. Several small-molecule cysteine-targeting covalent inhibitors of the Mpro have been discovered—some of which are currently undergoing evaluation in early phase human clinical trials. Understanding the binding energetics of these inhibitors could provide new insights to facilitate the design of potential drug candidates against COVID-19. Motivated by this, we employed rigorous absolute binding free energy calculations and hybrid quantum mechanical/molecular mechanical (QM/MM) calculations to estimate the energetics of binding of some promising reversible covalent inhibitors of the Mpro. We find that the inclusion of enhanced sampling techniques such as replica-exchange algorithm in binding free energy calculations can improve the convergence of predicted non-covalent binding free energy estimates of inhibitors binding to the Mpro target. In addition, our results indicate that binding free energy calculations coupled with multiscale simulations can be a useful approach to employ in ranking covalent inhibitors to their targets. This approach may be valuable in prioritizing and refining covalent inhibitor compounds for lead discovery efforts against COVID-19 and future coronavirus infections.

Insight into the Binding Energetics of Targeted Reversible Covalent Inhibitors of the SARS-CoV-2 Main Protease

The main protease (Mpro) of the SARS-CoV-2 virus is an attractive therapeutic target for developing antivirals to combat COVID-19. Mpro is essential for the replication cycle of the SARS-CoV-2 virus, so inhibiting Mpro blocks a vital piece of the cell replication machinery of the virus. A promising strategy to disrupt the viral replication cycle is to design inhibitors that bind to the active site cysteine (Cys145) of the Mpro. Cysteine targeted covalent inhibitors are gaining traction in drug discovery owing to the benefits of improved potency and extended drug-target engagement. An interesting aspect of these inhibitors is that they can be chemically tuned to form a covalent, but reversible bond, with their targets of interest. Several small-molecule cysteine-targeting covalent inhibitors of the Mpro have been discovered—some of which are currently undergoing evaluation in early phase human clinical trials. Understanding the binding energetics of these inhibitors could provide new insights to facilitate the design of potential drug candidates against COVID-19. Motivated by this, we employed rigorous absolute binding free energy calculations and hybrid quantum mechanical/molecular mechanical (QM/MM) calculations to estimate the energetics of binding of some promising reversible covalent inhibitors of the Mpro. We find that the inclusion of enhanced sampling techniques such as replica-exchange algorithm in binding free energy calculations can improve the convergence of predicted non-covalent binding free energy estimates of inhibitors binding to the Mpro target. In addition, our results indicate that binding free energy calculations coupled with multiscale simulations can be a useful approach to employ in ranking covalent inhibitors to their targets. This approach may be valuable in prioritizing and refining covalent inhibitor compounds for lead discovery efforts against COVID-19 and future coronavirus infections.