Soumendranath Bhakat

Theory and Applications of Covalent Docking in Drug Discovery: Merits and Pitfalls

The present art of drug discovery and design of new drugs is based on suicidal irreversible inhibitors. Covalent inhibition is the strategy that is used to achieve irreversible inhibition. Irreversible inhibitors interact with their targets in a time-dependent fashion, and the reaction proceeds to completion rather than to equilibrium. Covalent inhibitors possessed some significant advantages over non-covalent inhibitors such as covalent warheads can target rare, non-conserved residue of a particular target protein and thus led to development of highly selective inhibitors, covalent inhibitors can be effective in targeting proteins with shallow binding cleavage which will led to development of novel inhibitors with increased potency than non-covalent inhibitors. Several computational approaches have been developed to simulate covalent interactions; however, this is still a challenging area to explore. Covalent molecular docking has been recently implemented in the computer-aided drug design workflows to describe covalent interactions between inhibitors and biological targets. In this review we highlight: (i) covalent interactions in biomolecular systems; (ii) the mathematical framework of covalent molecular docking; (iii) implementation of covalent docking protocol in drug design workflows; (iv) applications covalent docking: case studies and (v) shortcomings and future perspectives of covalent docking. To the best of our knowledge; this review is the first account that highlights different aspects of covalent docking with its merits and pitfalls. We believe that the method and applications highlighted in this study will help future efforts towards the design of irreversible inhibitors.

A perspective on targeting non-structural proteins to combat neglected tropical diseases: Dengue, West Nile and Chikungunya viruses

Neglected tropical diseases are major causes of fatality in poverty stricken regions across Africa, Asia and some part of America. The combined potential health risk associated with arthropod-borne viruses (arboviruses); Dengue virus (DENV), West Nile Virus (WNV) and Chikungunya Virus (CHIKV) is immense. These arboviruses are either emerging or re-emerging in many regions with recent documented outbreaks in the United States. Despite several recent evidences of emergence, currently there are no approved drugs or vaccines available to counter these diseases. Non-structural proteins encoded by these RNA viruses are essential for their replication and maturation and thus may offer ideal targets for developing antiviral drugs. In recent years, several protease inhibitors have been sourced from plant extract, synthesis, computer aided drug design and high throughput screening as well as through drug reposition based approaches to target the non-structural proteins. The protease inhibitors have shown different levels of inhibition and may thus provide template to develop selective and potent drugs against these devastating arboviruses. This review seeks to shed light on the design and development of antiviral drugs against DENV, WNV and CHIKV to date. To the best of our knowledge, this review provides the first comprehensive update on the development of protease inhibitors targeting non-structural proteins of three most devastating arboviruses, DENV, WNV and CHIKV.

Monoamine oxidase inhibitory activity of 2-aryl-4H-chromen-4-ones

A series of twenty 2-aryl-4H-chromen-4-one (flavones) derivatives (3a-3s) were synthesized and tested for hMAO inhibitory activity. Fifteen compounds (3a, 3c, 3e-3h, 3j-3p, 3r, 3s) were found to be selective towards MAO-B, while 3d was selective towards MAO-A, and 3b, 3i and 3q were non-selective. Experimental Selectivity Index for MAO-B ranges from 2.0 (3g, 3p) to 30.0 (3j). Compound 3j, which is carrying 3,4-di-OMeC6H3 groups at R position on the molecule, was found to be potent MAO-B inhibitor amongst the fifteen with Ki value for MAO-B of 0.16±0.01 μM comparable to that of standard drug, Selegiline (Ki for MAO-B is 0.16±0.01 μM). Compound 3j also appeared as the most selective MAO-B inhibitor according to its best selectivity index (30.0), which is comparable to that of Selegiline (SIMAO-B=35.0). Molecular docking and molecular dynamics simulation studies were carried out using Autodock-4.0 and Amber12 to understand the molecular level interaction and energy relation of MAO isoforms with selective inhibitors (3d and 3j). Simulation results are in good agreement with the experimental results. Leads identified may further be explored to develop potent isoform specific inhibitors of MAO.

Compensatory role of double mutation N348I/M184V on nevirapine binding landscape: insight from molecular dynamics simulation.

Non-nucleoside reverse transcriptase inhibitors (NNRTI) have emerged as gold standards in current anti-AIDS drug discovery and development by allosterically inhibiting HIV reverse transcriptase (HIV-RT). Connection sub-domain mutation, N348I and the M184V active site mutation decreases HIV-1 RT susceptibility to NNRTI, nevirapine (NVP), whereas concurrence of both mutations improves enzyme susceptibility to NVP. Molecular dynamics simulation and enhanced post-dynamics analyses were applied to gain molecular insight into occurrence of N348I, M184V and N348I/M184V double mutations and their effect on NVP binding landscape. Results showed that the presence of the double mutation (N348I/M184V) ameliorates the drastic effects of connection sub-domain mutation, N348I alone on NVP binding, which correlates with experimental findings. We showed that the binding of NVP to the NNRTI binding pocket (NNIBP) is drastically distorted in the presence of connection sub-domain mutation, N348I and may further explain the impaired motions of mutant RTs compared to the wild type. The residue based fluctuation further suggested that the occurrence of N348I decreased the overall flexibility of NVP-HIV-RT complex whereas concurrence of N348I/M184V double mutation restored the conformational flexibility as compared to single mutant. This phenomenon was further validated by the trends of binding free energy as well as the per-residue footprints which showed an increased ∆Gbind in case of N348I/M184V double mutant as compared to N348I variant. Further, for the first time residue interaction network highlighted the structural changes due to occurrence of M184V and N348I mutations which gives a conclusive evidence of these mutations. This work provides the most comprehensive analysis of NVP resistance and the impact of double (N348I/M184V) mutation to date from a dynamics perspective and provides information that should prove useful for understanding the drug resistance mechanism against NVP. The results also provide preliminary data which might prove useful for the design of novel inhibitors that are less susceptible to drug resistance.Graphical Abstract

Multi-drug resistance profile of PR20 HIV-1 protease is attributed to distorted conformational and drug binding landscape: molecular dynamics insights

The PR20 HIV-1 protease, a variant with 20 mutations, exhibits high levels of multi-drug resistance; however, to date, there has been no report detailing the impact of these 20 mutations on the conformational and drug binding landscape at a molecular level. In this report, we demonstrate the first account of a comprehensive study designed to elaborate on the impact of these mutations on the dynamic features as well as drug binding and resistance profile, using extensive molecular dynamics analyses. Comparative MD simulations for the wild-type and PR20 HIV proteases, starting from bound and unbound conformations in each case, were performed. Results showed that the apo conformation of the PR20 variant of the HIV protease displayed a tendency to remain in the open conformation for a longer period of time when compared to the wild type. This led to a phenomena in which the inhibitor seated at the active site of PR20 tends to diffuse away from the binding site leading to a significant change in inhibitor–protein association. Calculating the per-residue fluctuation (RMSF) and radius of gyration, further validated these findings. MM/GBSA showed that the occurrence of 20 mutations led to a drop in the calculated binding free energies (ΔGbind) by ~25.17 kcal/mol and ~5 kcal/mol for p2-NC, a natural peptide substrate, and darunavir, respectively, when compared to wild type. Furthermore, the residue interaction network showed a diminished inter-residue hydrogen bond network and changes in inter-residue connections as a result of these mutations. The increased conformational flexibility in PR20 as a result of loss of intra- and inter-molecular hydrogen bond interactions and other prominent binding forces led to a loss of protease grip on ligand. It is interesting to note that the difference in conformational flexibility between PR20 and WT conformations was much higher in the case of substrate-bound conformation as compared to DRV. Thus, developing analogues of DRV by retaining its key pharmacophore features will be the way forward in the search for novel protease inhibitors against multi-drug resistant strains.

Investigation of flap flexibility of β-secretase using molecular dynamic simulations

Flap motif and its dynamics were extensively reported in aspartate proteases, e.g. HIV proteases and plasmepsins. Herein, we report the first account of flap dynamics amongst different conformations of β-secretase using molecular dynamics simulation. Various parameters were proposed and a selected few were picked which could appropriately describe the flap motion. Three systems were studied, namely Free (BACEFree) and two ligand-bound conformations, which belonged to space groups P6122 (BACEBound1) and C2221 (BACEBound2), respectively and four parameters (distance between the flaps tip residue, Thr72 and Ser325, d1; dihedral angle, ϕ (Thr72-Asp32-Asp228-Ser325); TriCα angles, θ1 (Thr72-Asp32-Ser325), and θ2 (Thr72-Asp228-Ser325)) were proposed to understand the change in dynamics of flap domain and the extent of flap opening and closing. Analysis of, θ2, d1, θ1 and ϕ confirmed that the BACEFree adopted semi-open, open and closed conformations with slight twisting during flap opening. However, BACEBound1 (P6122) showed an adaptation to open conformation due to lack of hydrogen bond interaction between the ligand and flap tip residue. A slight flap twisting, ϕ (lateral twisting) was observed for BACEBound1 during flap opening which correlates with the opening of BACEFree. Contradictory to the BACEBound1, the BACEBound2 locked the flap in a closed conformation throughout the simulation due to formation of a stable hydrogen bond interaction between the flap tip residue and ligand. Analyses of all three systems highlight that d1, θ2 and ϕ can be precisely used to describe the extent of flap opening and closing concurrently with snapshots along the molecular dynamics trajectory across several conformations of β-secretase.

New paradigm of an old target: An update on structural biology and current progress in drug design towards plasmepsin II

Malaria is one of the major parasitic disease whose rapid spreading and mortality rate affects all parts of the world especially several parts of Asia as well as Africa. The emergence of multi-drug resistant strains hamper the progress of current antimalarial therapy and displayed an urgent need for new antimalarials by targeting novel drug targets. Until now, several promising targets were explored in order to develop a promising Achilles hill to counter malaria. Plasmepsin, an aspartic protease, which is involved in the hemoglobin breakdown into smaller peptides emerged as a crucial target to develop new chemical entities to counter malaria. Due to early crystallographic evidence, plasmepsin II (Plm II) emerged as well explored target to develop novel antimalarials as well as a starting point to develop inhibitors targeting some other subtypes of plasmepsins i.e. Plm I, II, IV and V. With the advancements in drug discovery, several computational and synthetic approaches were employed in order to develop novel inhibitors targeting Plm II. Strategies such as fragment based drug design, molecular dynamics simulation, double drug approach etc. were employed in order to develop new chemical entities targeting Plm II. But majority of Plm II inhibitors suffered from poor selectivity over cathepsin D as well as other subtypes of plasmepsins. This review highlights an updated account of drug discovery efforts targeting plasmepsin II from a medicinal chemistry perspective.

Heat-Shock Protein 90 (Hsp90) as Anticancer Target for Drug Discovery: An Ample Computational Perspective

There are over 100 different types of cancer, and each is classified based on the type of cell that is initially affected. If left untreated, cancer can result in serious health problems and eventually death. Recently, the paradigm of cancer chemotherapy has evolved to use a combination approach, which involves the use of multiple drugs each of which targets an individual protein. Inhibition of heat‐shock protein 90 (Hsp90) is one of the novel key cancer targets. Because of its ability to target several signaling pathways, Hsp90 inhibition emerged as a useful strategy to treat a wide variety of cancers. Molecular modeling approaches and methodologies have become ‘close counterparts’ to experiments in drug design and discovery workflows. A wide range of molecular modeling approaches have been developed, each of which has different objectives and outcomes. In this review, we provide an up‐to‐date systematic overview on the different computational models implemented toward the design of Hsp90 inhibitors as anticancer agents. Although this is the main emphasis of this review, different topics such as background and current statistics of cancer, different anticancer targets including Hsp90, and the structure and function of Hsp90 from an experimental perspective, for example, X‐ray and NMR, are also addressed in this report. To the best of our knowledge, this review is the first account, which comprehensively outlines various molecular modeling efforts directed toward identification of anticancer drugs targeting Hsp90. We believe that the information, methods, and perspectives highlighted in this report would assist researchers in the discovery of potential anticancer agents.

Flap Dynamics in Aspartic Proteases: A Computational Perspective

Recent advances in biochemistry and drug design have placed proteases as one of the critical target groups for developing novel small‐molecule inhibitors. Among all proteases, aspartic proteases have gained significant attention due to their role in HIV/AIDS, malaria, Alzheimers disease, etc. The binding cleft is covered by one or two β‐hairpins (flaps) which need to be opened before a ligand can bind. After binding, the flaps close to retain the ligand in the active site. Development of computational tools has improved our understanding of flap dynamics and its role in ligand recognition. In the past decade, several computational approaches, for example molecular dynamics (MD) simulations, coarse‐grained simulations, replica‐exchange molecular dynamics (REMD) and metadynamics, have been used to understand flap dynamics and conformational motions associated with flap movements. This review is intended to summarize the computational progress towards understanding the flap dynamics of proteases and to be a reference for future studies in this field.

Resolving the problem of trapped water in binding cavities: prediction of host–guest binding free energies in the SAMPL5 challenge by funnel metadynamics

The funnel metadynamics method enables rigorous calculation of the potential of mean force along an arbitrary binding path and thereby evaluation of the absolute binding free energy. A problem of such physical paths is that the mechanism characterizing the binding process is not always obvious. In particular, it might involve reorganization of the solvent in the binding site, which is not easily captured with a few geometrically defined collective variables that can be used for biasing. In this paper, we propose and test a simple method to resolve this trapped-water problem by dividing the process into an artificial host-desolvation step and an actual binding step. We show that, under certain circumstances, the contribution from the desolvation step can be calculated without introducing further statistical errors. We apply the method to the problem of predicting host–guest binding free energies in the SAMPL5 blind challenge, using two octa-acid hosts and six guest molecules. For one of the hosts, well-converged results are obtained and the prediction of relative binding free energies is the best among all the SAMPL5 submissions. For the other host, which has a narrower binding pocket, the statistical uncertainties are slightly higher; longer simulations would therefore be needed to obtain conclusive results.