Electrostatics Plays a Crucial Role in HIV-1 Protease Substrate Binding, Drugs Fail to Take Advantage

In silico identification and validation of phenolic lipids as potential inhibitor against bacterial and viral strains

The recurrence of coronavirus disease and bacterial resistant strains has drawn attention to naturally occurring bioactive molecules that can demonstrate broad-spectrum efficacy against bacteria as well as viral strains. The drug-like abilities of naturally available "anacardic acids" (AA) and their derivatives against different bacterial and viral protein targets through in-silico tools were explored. Three viral protein targets [P DB: 6Y2E (SARS-CoV-2), 1AT3 (Herpes) and 2VSM (Nipah)] and four bacterial protein targets [P DB: 2VF5 (Escherichia coli), 2VEG (Streptococcus pneumoniae), 1JIJ (Staphylococcus aureus) and 1KZN (E. coli)] were selected to evaluate the activity of bioactive AA molecules. The potential ability to inhibit the progression of microbes has been discussed based on the structure, functionality and interaction ability of these molecules on the selected protein targets for multi-disease remediation. The number of interactions, full-fitness value and energy of the ligand-target system were determined from the docked structure in SwissDock and Autodock Vina. In order to compare the efficacy of these active derivatives to that of commonly used drugs against bacteria and viruses, a few of the selected molecules were subjected to 100 ns long MD simulations. It was found that the phenolic groups and alkyl chains of AA derivatives are more likely to bind with microbial targets, that could be responsible for the improved activity against these targets. The results suggest that the proposed AA derivatives have demonstrated potential to become active drug ingredients against microbial protein targets. Further, experimental investigations are essential for clinical verification of the drug-like abilities of AA derivatives.Communicated by Ramaswamy H. Sarma.

Electrostatic Features for the Receptor Binding Domain of SARS-COV-2 Wildtype and Its Variants. Compass to the Severity of the Future Variants with the Charge-Rule

Electrostatic intermolecular interactions are important in many aspects of biology. We have studied the main electrostatic features involved in the interaction of the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein with the human receptor Angiotensin-converting enzyme 2 (ACE2). As the principal computational tool, we have used the FORTE approach, capable to model proton fluctuations and computing free energies for a very large number of protein-protein systems under different physical-chemical conditions, here focusing on the RBD-ACE2 interactions. Both the wild-type and all critical variants are included in this study. From our large ensemble of extensive simulations, we obtain, as a function of pH, the binding affinities, charges of the proteins, their charge regulation capacities, and their dipole moments. In addition, we have calculated the pK_as for all ionizable residues and mapped the electrostatic coupling between them. We are able to present a simple predictor for the RBD-ACE2 binding based on the data obtained for Alpha, Beta, Gamma, Delta, and Omicron variants, as a linear correlation between the total charge of the RBD and the corresponding binding affinity. This "RBD charge rule" should work as a quick test of the degree of severity of the coming SARS-CoV-2 variants in the future.

Mechanism of darunavir binding to monomeric HIV-1 protease: a step forward in the rational design of dimerization inhibitors

HIV protease (HIVPR) is a key target in AIDS therapeutics. All ten FDA-approved drugs that compete with substrates in binding to this dimeric enzyme's active site have become ineffective due to the emergence of drug resistant mutants. Blocking the dimerization interface of HIVPR is thus being explored as an alternate strategy. The latest drug, darunavir (DRV), which exhibited a high genetic barrier to viral resistance, is said to have a dual mode of action - (i) binding to the dimeric active site, and (ii) preventing the dimerization by binding to the HIVPR monomer. Despite several reports on DRV complexation with dimeric HIVPR, the mode and mechanism of the binding of DRV to the HIVPR monomer are poorly understood. In this study, we utilized all-atomic MD simulations and umbrella sampling techniques to identify the best possible binding mode of DRV to the monomeric HIVPR and its mechanism of association. The results suggest that DRV binds between the active site and the flap of the monomer, and the flap plays a crucial role in directing the drug to bind and driving the other protein domains to undergo induced fit changes for stronger complexation. The obtained binding mode of DRV was validated by comparing with various mutational data from clinical isolates to reported in vitro mutations. The identified binding pose was also able to successfully reproduce the experimental K_i value in the picomolar range. The residue-level information extracted from this study could accelerate the structure-based drug designing approaches targeting HIVPR dimerization.

Molecular dynamics of the viral life cycle: progress and prospects

Molecular dynamics (MD) simulations across spatiotemporal resolutions are widely applied to study viruses and represent the central technique uniting the field of computational virology. We discuss the progress of MD in elucidating the dynamics of the viral life cycle, including the status of modeling intact extracellular virions and leveraging advanced simulations to mimic active life cycle processes. We further remark on the prospects of MD for continued contributions to the basic science characterization of viruses, especially given the increasing availability of high-quality experimental data and supercomputing power. Overall, integrative computational methods that are closely guided by experiments are unmatched in the level of detail they provide, enabling-now and in the future-new discoveries relevant to thwarting viral infection.

Combining Molecular Dynamic Information and an Aspherical-Atom Data Bank in the Evaluation of the Electrostatic Interaction Energy in Multimeric Protein-Ligand Complex: A Case Study for HIV-1 Protease

Computational analysis of protein–ligand interactions is of crucial importance for drug discovery. Assessment of ligand binding energy allows us to have a glimpse of the potential of a small organic molecule to be a ligand to the binding site of a protein target. Available scoring functions, such as in docking programs, all rely on equations that sum each type of protein–ligand interactions in order to predict the binding affinity. Most of the scoring functions consider electrostatic interactions involving the protein and the ligand. Electrostatic interactions constitute one of the most important part of total interactions between macromolecules. Unlike dispersion forces, they are highly directional and therefore dominate the nature of molecular packing in crystals and in biological complexes and contribute significantly to differences in inhibition strength among related enzyme inhibitors. In this study, complexes of HIV-1 protease with inhibitor molecules (JE-2147 and darunavir) were analyzed by using charge densities from the transferable aspherical-atom University at Buffalo Databank (UBDB). Moreover, we analyzed the electrostatic interaction energy for an ensemble of structures, using molecular dynamic simulations to highlight the main features of electrostatic interactions important for binding affinity.

Understanding the mechanism of HIV-1 protease inhibition by monoclonal antibodies

HIV-1 protease is an essential enzyme in the life cycle of human immunodeficiency virus (HIV) and hence is one of the most important targets for antiviral drug design. Although there are ten FDA approved drugs against HIV protease (PR), their long term usage elicits mutations leading to drug resistance. As a result, novel therapeutic approaches are being explored including synthetic antibodies. Recently, a murine monoclonal antibody, mAB1696 (mAB) was reported to inhibit PR by preventing dimerization. Crystallographic data could reveal only six protease residues that interact with mAB. The present study employs a range of computational techniques, starting from protein-protein docking to all-atomic molecular dynamics simulations to generate plausible 3D structures of PR-mAB complex. Results show that mAB interacts very strongly with several PR dimer interface residues, such as Gln7, Arg8 (N-terminal), Cys95, Leu97 (C-terminal), Thr26, Gly27 (active site), Gly49, Ile50 (flap), apart from its interactions with the PR epitope region, Pro1-Trp6 (N-terminal). These observations support the hypothesis that binding of mAB prevents the dimerization of PR. The interactions and binding conformations identified in this study could form the basis for designing allosteric inhibitors preventing the dimerization of HIV-1 Protease.