Protein-protein interaction of RdRp with its co-factor NSP8 and NSP7 to decipher the interface hotspot residues for drug targeting: A comparison between SARS-CoV-2 and SARS-CoV

In this study we explored the molecular mechanism of RdRp (Non-Structural Protein, NSP12) interaction with its co-factors NSP7 and NSP8 which is the main toolbox for RNA replication and transcription of SARS-CoV-2 and SARS-CoV. The replication complex is a heterotetramer consists of one NSP12, one NSP7 and two NSP8. Extensive molecular dynamics (MD) simulations were applied on both the heterotetramer complexes to generate the conformations and were used to estimate the MMPBSA binding free energy (BFE) and per-residue energy decomposition of NSP12-NSP8 and NSP12-NSP7 and NSP7-NSP8 complexes. The BFE of SARS-CoV-2 heterotetramer complex with its corresponding partner protein was significantly higher as compared to SARS-CoV. Interface hotspot residues were predicted using different methods implemented in KFC (Knowledge-based FADA and Contracts), HotRegion and Robetta web servers. Per-residue energy decomposition analysis showed that the predicted interface hotspot residues contribute more energy towards the formation of complexes and most of the predicted hotspot residues are clustered together. However, there is a slight difference in the residue-wise energy contribution in the interface NSPs on heterotetramer viral replication complex of both coronaviruses. While the overall replication complex of SARS-CoV-2 was found to be slightly flexible as compared to SARS-CoV. This difference in terms of structural flexibility/stability and energetic characteristics of interface residues including hotspots at PPI interface in the viral replication complexes may be the reason of higher rate of RNA replication of SARS-CoV-2 as compared to SARS-CoV. Overall, the interaction profile at PPI interface such as, interface area, hotspot residues, nature of bonds and energies between NSPs, may provide valuable insights in designing of small molecules or peptide/peptidomimetic ligands which can fit into the PPI interface to disrupt the interaction.

A probable means to an end: exploring P131 pharmacophoric scaffold to identify potential inhibitors of Cryptosporidium parvum inosine monophosphate dehydrogenase

Compound P131 has been established to inhibit Cryptosporidium parvum's inosine monophosphate dehydrogenase (CpIMPDH). Its inhibitory activity supersedes that of paromomycin, which is extensively used in treating cryptosporidiosis. Through the per-residue energy decomposition approach, crucial moieties of P131 were identified and subsequently adopted to create a pharmacophore model for virtual screening in the ZINC database. This search generated eight ADMET-compliant hits that were examined thoroughly to fit into the active site of CpIMPDH via molecular docking. Three compounds ZINC46542062, ZINC58646829, and ZINC89780094, with favorable docking scores of - 8.3 kcal/mol, - 8.2 kcal/mol, and - 7.5 kcal/mol, were selected. The potential inhibitory mechanism of these compounds was probed using molecular dynamics simulation and Molecular Mechanics Generalized Poisson Boltzmann Surface Area (MM/PBSA) analyses. Results revealed that one of the hits (ZINC46542062) exhibited a lower binding free energy of - 39.52 kcal/mol than P131, which had - 34.6 kcal/mol. Conformational perturbation induced by the binding of the identified hits to CpIMPDH was similar to P131, suggesting a similarity in inhibitory mechanisms. Also, in silico investigation of the properties of the hit compounds implied superior physicochemical properties with regards to their synthetic accessibility, lipophilicity, and number of hydrogen bond donors and acceptors in comparison with P131. ZINC46542062 was identified as a promising hit compound with the highest binding affinity to the target protein and favorable physicochemical and pharmacokinetic properties relative to P131. The identified compounds can serve as a basis for conducting further experimental investigations toward the development of anticryptosporidials, which can overcome the challenges of existing therapeutic options. Graphical abstract P131 and the identified compounds docked in the NAD⁺ binding site of Cryptosporidium parvum IMPDH.

Could chroman-4-one derivative be a better inhibitor of PTR1? - Reason for the identified disparity in its inhibitory potency in Trypanosoma brucei and Leishmania major

Most notable Kinetoplastids are of the genus Trypanosoma and Leishmania, affecting several millions of humans in Africa and Latin America. Current therapeutic options are limited by several drawbacks, hence the need to develop more efficacious inhibitors. An investigation to decipher the mechanism behind greater inhibitory potency of a chroman-4-one derivative (compound 1) in Trypanosoma brucei pteridine reductase 1 (TbPTR1) and Leishmania major pteridine reductase 1 (LmPTR1) was performed. Estimation of ΔG_bind revealed that compound 1 had a greater binding affinity in TbPTR1 with a ΔG_bind value of -49.0507 Kcal/mol than -29.2292 Kcal/mol in LmPTR1. The ΔGbind in TbPTR1 were predominantly contributed by "strong" electrostatic energy compared to the "weak" van der Waals in LmPTR1. In addition to this, the NADPH cofactor contributed significantly to the total energy of TbPTR1. A characteristic weak aromatic π interaction common in PTR1 was more prominent in TbPTR1 than LmPTR1. The consistent occurrence of high-affinity conventional hydrogen bond interactions as well as a steady interaction of crucial active site residues like Arg14/Arg17, Ser95/Ser111, Phe97/Phe113 in TbPTR1/LmPTR1 with chroman-4-one moiety equally revealed the important role the moiety played in the activity of compound 1. Overall, the structural and conformational analysis of the active site residues in TbPTR1 revealed them to be more rigid than LmPTR1. This could be the mechanism of interaction TbPTR1 employs in exerting a greater potency than LmPTR1. These findings will further give insight that will be assistive in modifying compound 1 for better potency and the design of novel inhibitors of PTR1.

Application of per-residue energy decomposition to identify the set of amino acids critical for in silico prediction of COX-2 inhibitory activity

The enormous magnitude of scientific research carried out in the field of NSAIDs and cyclooxygenases (COXs) is known. They are crucial in pain management. COX-2 inhibitors have evolved over the years; from traditional NSAIDs to isoform-specific. The present study is aimed to identify a cluster of amino acids in the catalytic site whose energy contribution can better explain COX-2 inhibitory activity accurately than the binding energy of the whole protein. Initially, MD simulations (25 ns) and MM-PBSA calculations were performed for 8 diarylheterocyclic inhibitors. Per-residue energy decomposition studies were carried out to elucidate the energy contribution of each amino acid, and their correlation with COX-2 inhibitory activity was enumerated. A cluster of catalytic amino acids whose free energy sum has a high correlation with biological data was identified. The cluster of Gln178, Ser339, Tyr341, Arg499, Phe504, Val509 and Ala513 showed the correlation of -0.60. Further, the study was extended to a total of 26 COX-2 inhibitors belonging to different classes to validate the applicability of the cluster of amino acids identified. Results clearly suggest that the cluster of amino acids identified provide accurate screening method, and can be applied to predict COX-2 inhibitory activity of small molecules.

Broadening the horizon: Integrative pharmacophore-based and cheminformatics screening of novel chemical modulators of mitochondria ATP synthase towards interventive Alzheimer's disease therapy

The proven efficacy of J147 in the treatment of Alzheimer's disease (AD) has been emphatic, particularly since its selective modulatory roles towards mitochondrial ATP synthase (mATPase) were defined. This prospect, if methodically probed, could further pave way for the discovery of novel anti-AD drugs with improved pharmacokinetics and therapeutic potential. To this effect, for the first time, we employed a four-step paradigm that integrated our in-house per-residue energy decomposition (PRED) protocol coupled with molecular dynamics, cheminformatics and analytical binding free energy methods. This was geared towards the screening and identification of new leads that exhibit modulatory potentials towards mATPase in a J147-similar pattern. Interestingly, from a large-scale library of compounds, we funnelled down on three potential hits that demonstrated selective and high-affinity binding activities towards α-F1-ATP synthase (ATP5A) relative to J147. Moreover, these compounds exhibited higher binding propensity with a differential ΔGs greater than -1 kcal/mol comparative to J147, and also elicited distinct modulatory effects on ATP5A domain structures. More interestingly, per-residue pharmacophore modeling of these lead compounds revealed similar interactive patterns with crucial residues at the α-site region of ATP5A characterized by high energy contributions based on binding complementarity. Recurrent target residues involved in high-affinity interactions with the hit molecules relative to J147 include Arg1112 and Gln426. Furthermore, assessments of pharmacokinetics revealed that the lead compounds were highly drug-like with minimal violations of the Lipinski's rule of five. As developed in this study, the most extrapolative pharmacophore model of the selected hits encompassed three electron donors and one electron acceptor. We speculate that these findings will be fundamental to the reformation of anti-AD drug discovery procedures.

Optimisation of human VH domain antibodies specific to Mycobacterium tuberculosis heat shock protein (HSP16.3)

Mycobacterium tuberculosis (Mtb) 16.3 kDa heat shock protein 16.3 (HSP16.3) is a latency-associated antigen that can be targeted for latent tuberculosis (TB) diagnostic and therapeutic development. We have previously developed human V_H domain antibodies (dAbs; clone E3 and F1) specific against HSP16.3. In this work, we applied computational methods to optimise and design the antibodies in order to improve the binding affinity with HSP16.3. The V_H domain antibodies were first docked to the dimer form of HSP16.3 and further sampled using molecular dynamics simulation. The calculated binding free energy of the HSP16.3-dAb complexes showed non-polar interactions were responsible for the antigen-antibody association. Per-residue free energy decomposition and computational alanine scanning have identified one hotspot residue for E3 (Y391) and 4 hotspot residues for F1 (M394, Y396, R397 and M398). These hotspot residues were then mutated and evaluated by binding free energy calculations. Phage ELISA assay was carried out on the potential mutants (E3_Y391W, F1_M394E, F1_R397N and F1_M398Y). The experimental assay showed improved binding affinities of E3_Y391W and F1_M394E against HSP16.3 compared with the wild type E3 and F1. This case study has thus showed in silico methods are able to assist in optimisation or improvement of antibody-antigen binding.