The nepenthesin insert in the Plasmodium falciparum aspartic protease plasmepsin V is necessary for enzyme function.

Plasmepsin V (PM V) is a pepsin-like aspartic protease essential for growth of the malarial parasite Plasmodium falciparum. Previous work has shown PM V to be an endoplasmic reticulum-resident protease that processes parasite proteins destined for export into the host cell. Depletion or inhibition of the enzyme is lethal during asexual replication within red blood cells as well as during the formation of sexual stage gametocytes. The structure of the Plasmodium vivax PM V has been characterized by X-ray crystallography, revealing a canonical pepsin fold punctuated by structural features uncommon to secretory aspartic proteases; however, the function of this unique structure is unclear. Here, we used parasite genetics to probe these structural features by attempting to rescue lethal PM V depletion with various mutant enzymes. We found an unusual nepenthesin 1-type insert in the PM V gene to be essential for parasite growth and PM V activity. Mutagenesis of the nepenthesin insert suggests that both its amino acid sequence and one of the two disulfide bonds that undergird its structure are required for the insert's role in PM V function. Furthermore, molecular dynamics simulations paired with Markov state modeling suggest that mutations to the nepenthesin insert may allosterically affect PM V catalysis through multiple mechanisms. Taken together, these data provide further insights into the structure of the P. falciparum PM V protease.

Flap Dynamics in Pepsin-Like Aspartic Proteases: A Computational Perspective Using Plasmepsin-II and BACE-1 as Model Systems.

The flexibility of ß hairpin structure known as the flap plays a key role in catalytic activity and substrate intake in pepsin-like aspartic proteases. Most of these enzymes share structural and sequential similarity. In this study, we have used apo Plm-II and BACE-1 as model systems. In the apo form of the proteases, a conserved tyrosine residue in the flap region remains in a dynamic equilibrium between the normal and flipped states through rotation of the χ1 and χ2 angles. Independent MD simulations of Plm-II and BACE-1 remained stuck either in the normal or flipped state. Metadynamics simulations using side-chain torsion angles (χ1 and χ2 of tyrosine) as collective variables sampled the transition between the normal and flipped states. Qualitatively, the two states were predicted to be equally populated. The normal and flipped states were stabilized by H-bond interactions to a tryptophan residue and to the catalytic aspartate, respectively. Further, mutation of tyrosine to an amino-acid with smaller side-chain, such as alanine, reduced the flexibility of the flap and resulted in a flap collapse (flap loses flexibility and remains stuck in a particular state). This is in accordance with previous experimental studies, which showed that mutation to alanine resulted in loss of activity in pepsin-like aspartic proteases. Our results suggest that the ring flipping associated with the tyrosine side-chain is the key order parameter that governs flap dynamics and opening of the binding pocket in most pepsin-like aspartic proteases.

Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling.

Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method.

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.

Dynamic features of apo and bound HIV-Nef protein reveal the anti-HIV dimerization inhibition mechanism.

The first account on the dynamic features of Nef or negative factor, a small myristoylated protein located in the cytoplasm believes to increase HIV-1 viral titer level, is reported herein. Due to its major role in HIV-1 pathogenicity, Nef protein is considered an emerging target in anti-HIV drug design and discovery process. In this study, comparative long-range all-atom molecular dynamics simulations were employed for apo and bound protein to unveil molecular mechanism of HIV-Nef dimerization and inhibition. Results clearly revealed that B9, a newly discovered Nef inhibitor, binds at the dimeric interface of Nef protein and caused significant separation between orthogonally opposed residues, namely Asp108, Leu112 and Gln104. Large differences in magnitudes were observed in the radius of gyration (∼1.5 Å), per-residue fluctuation (∼2 Å), C-alpha deviations (∼2 Å) which confirm a comparatively more flexible nature of apo conformation due to rapid dimeric association. Compared to the bound conformer, a more globally correlated motion in case of apo structure of HIV-Nef confirms the process of dimeric association. This clearly highlights the process of inhibition as a result of ligand binding. The difference in principal component analysis (PCA) scatter plot and per-residue mobility plot across first two normal modes further justifies the same findings. The in-depth dynamic analyses of Nef protein presented in this report would serve crucial in understanding its function and inhibition mechanisms. Information on inhibitor binding mode would also assist in designing of potential inhibitors against this important HIV target.

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.

Theory and applications of covalent docking in drug discovery: merits and pitfalls.

he 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.

Accelerating Cryptic Pocket Discovery Using AlphaFold.

Cryptic pockets, or pockets absent in ligand-free, experimentally determined structures, hold great potential as drug targets. However, cryptic pocket openings are often beyond the reach of conventional biomolecular simulations because certain cryptic pocket openings involve slow motions. Here, we investigate whether AlphaFold can be used to accelerate cryptic pocket discovery either by generating structures with open pockets directly or generating structures with partially open pockets that can be used as starting points for simulations. We use AlphaFold to generate ensembles for 10 known cryptic pocket examples, including five that were deposited after AlphaFold's training data were extracted from the PDB. We find that in 6 out of 10 cases AlphaFold samples the open state. For plasmepsin II, an aspartic protease from the causative agent of malaria, AlphaFold only captures a partial pocket opening. As a result, we ran simulations from an ensemble of AlphaFold-generated structures and show that this strategy samples cryptic pocket opening, even though an equivalent amount of simulations launched from a ligand-free experimental structure fails to do so. Markov state models (MSMs) constructed from the AlphaFold-seeded simulations quickly yield a free energy landscape of cryptic pocket opening that is in good agreement with the same landscape generated with well-tempered metadynamics. Taken together, our results demonstrate that AlphaFold has a useful role to play in cryptic pocket discovery but that many cryptic pockets may remain difficult to sample using AlphaFold alone.

Collective variable discovery in the age of machine learning: reality, hype and everything in between.

Understanding the kinetics and thermodynamics profile of biomolecules is necessary to understand their functional roles which has a major impact in mechanism driven drug discovery. Molecular dynamics simulation has been routinely used to understand conformational dynamics and molecular recognition in biomolecules. Statistical analysis of high-dimensional spatiotemporal data generated from molecular dynamics simulation requires identification of a few low-dimensional variables which can describe the essential dynamics of a system without significant loss of information. In physical chemistry, these low-dimensional variables are often called collective variables. Collective variables are used to generate reduced representations of free energy surfaces and calculate transition probabilities between different metastable basins. However the choice of collective variables is not trivial for complex systems. Collective variables range from geometric criteria such as distances and dihedral angles to abstract ones such as weighted linear combinations of multiple geometric variables. The advent of machine learning algorithms led to increasing use of abstract collective variables to represent biomolecular dynamics. In this review, I will highlight several nuances of commonly used collective variables ranging from geometric to abstract ones. Further, I will put forward some cases where machine learning based collective variables were used to describe simple systems which in principle could have been described by geometric ones. Finally, I will put forward my thoughts on artificial general intelligence and how it can be used to discover and predict collective variables from spatiotemporal data generated by molecular dynamics simulations.

Pepsin-like aspartic proteases (PAPs) as model systems for combining biomolecular simulation with biophysical experiments.

Pepsin-like aspartic proteases (PAPs) are a class of aspartic proteases which shares tremendous structural similarity with human pepsin. One of the key structural features of PAPs is the presence of a ß-hairpin motif otherwise known as flap. The biological function of the PAPs is highly dependent on the conformational dynamics of the flap region. In apo PAPs, the conformational dynamics of the flap is dominated by the rotational degrees of freedom associated with χ1 and χ2 angles of conserved Tyr (or Phe in some cases). However it is plausible that dihedral order parameters associated with several other residues might play crucial roles in the conformational dynamics of apo PAPs. Due to their size, complexities associated with conformational dynamics and clinical significance (drug targets for malaria, Alzheimer's disease etc.), PAPs provide a challenging testing ground for computational and experimental methods focusing on understanding conformational dynamics and molecular recognition in biomolecules. The opening of the flap region is necessary to accommodate substrate/ligand in the active site of the PAPs. The BIG challenge is to gain atomistic details into how reversible ligand binding/unbinding (molecular recognition) affects the conformational dynamics. Recent reports of kinetics (K i, K d) and thermodynamic parameters (ΔH, TΔS, and ΔG) associated with macro-cyclic ligands bound to BACE1 (belongs to PAP family) provide a perfect challenge (how to deal with big ligands with multiple torsional angles and select optimum order parameters to study reversible ligand binding/unbinding) for computational methods to predict binding free energies and kinetics beyond typical test systems e.g. benzamide-trypsin. In this work, i reviewed several order parameters which were proposed to capture the conformational dynamics and molecular recognition in PAPs. I further highlighted how machine learning methods can be used as order parameters in the context of PAPs. I then proposed some open ideas and challenges in the context of molecular simulation and put forward my case on how biophysical experiments e.g. NMR, time-resolved FRET etc. can be used in conjunction with biomolecular simulation to gain complete atomistic insights into the conformational dynamics of PAPs.

Identification of Binding Mode and Prospective Structural Features of Novel Nef Protein Inhibitors as Potential Anti-HIV Drugs.

Human immunodeficiency virus (HIV)-negative factor (Nef) protein is an accessory pathogenic factor, which plays a significant role in acquired immune deficiency syndrome (AIDS). Nef deficient HIV virus took a longer time to progress into AIDS. Therefore, targeting Nef protein is considered as a key strategy towards HIV/AIDS treatment. Up-to-date, only few compounds were reported as Nef inhibitors. This has prompted us to provide a first account of an integrated computational framework in order to identify more potential Nef inhibitors. Herein, using a hybrid ligand (shape similarity and pharmacophore) and structure-(molecular docking) based virtual screening approaches combined with molecular dynamics as well as post dynamics analysis, potential new hits were identified as HIV-Nef inhibitors. The top ranked compounds of molecular docking from the shape similarity-based library (ZINC04177596, ∆ G bind= -28.7482 kcal/mol) and pharmacophore-based library (ZINC36617540, ∆ G bind= -20.2271 kcal/mol) possess comparatively better binding affinities than the reference molecule, B9 (∆ G bind = -18.0694 kcal/mol). Both these hits (ZINC04177596 and ZINC36617540) showed similar binding mode at the binding site as like the prototype, B9. Hydrophobic and electrostatic interactions seemed to be the prominent binding forces that hold these ligands at the dimer interface of Nef protein. Finally, a set of chemical structural features that can be used as a guide in the design of novel potential Nef inhibitors is also highlighted herein. We believe that the information gained from this study would be of great importance in the discovery and design of potential small molecules targeting HIV-Nef.

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, Alzheimer's disease, etc. The binding cleft is covered by one or two ß-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.

Investigation of flap flexibility of ß-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 ß-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 ß-secretase.

Single Active Site Mutation Causes Serious Resistance of HIV Reverse Transcriptase to Lamivudine: Insight from Multiple Molecular Dynamics Simulations.

Molecular dynamics simulations, binding free energy calculations, principle component analysis (PCA), and residue interaction network analysis were employed in order to investigate the molecular mechanism of M184I single mutation which played pivotal role in making the HIV-1 reverse transcriptase (RT) totally resistant to lamivudine. Results showed that single mutations at residue 184 of RT caused (1) distortion of the orientation of lamivudine in the active site due to the steric conflict between the oxathiolane ring of lamivudine and the side chain of beta-branched amino acids Ile at position 184 which, in turn, perturbs inhibitor binding, (2) decrease in the binding affinity by (~8 kcal/mol) when compared to the wild-type, (3) variation in the overall enzyme motion as evident from the PCA for both systems, and (4) distortion of the hydrogen bonding network and atomic interactions with the inhibitor. The comprehensive analysis presented in this report can provide useful information for understanding the drug resistance mechanism against lamivudine. The results can also provide some potential clues for further design of novel inhibitors that are less susceptible to drug resistance.

5' Adenosine Monophosphate-Activated Protein Kinase Modulators as Anticancer Agents.

In spite of tremendous advancement in the field of cancer therapy, it is still one of the leading causes of death worldwide. One of the newest targets in the field of cancer therapeutics is 5'Adenosine Mono Phosphate activated protein kinase (AMPK). In vitro and in vivo evidences suggest anti-cancer activity of AMPK. AMPK activation may promote catabolism while preventing the anabolic processes of cell. Thus it may modulate cellular protein and lipid metabolism and affect the growth and division of cell. Here we review the mechanisms of action of AMPK modulators as future anti-cancer agents.

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.

Insights on the structural perturbations in human MTHFR Ala222Val mutant by protein modeling and molecular dynamics.

Methylenetetrahydrofolate reductase (MTHFR) protein catalyzes the only biochemical reaction which produces methyltetrahydrofolate, the active form of folic acid essential for several molecular functions. The Ala222Val polymorphism of human MTHFR encodes a thermolabile protein associated with increased risk of neural tube defects and cardiovascular disease. Experimental studies have shown that the mutation does not affect the kinetic properties of MTHFR, but inactivates the protein by increasing flavin adenine dinucleotide (FAD) loss. The lack of completely solved crystal structure of MTHFR is an impediment in understanding the structural perturbations caused by the Ala222Val mutation; computational modeling provides a suitable alternative. The three-dimensional structure of human MTHFR protein was obtained through homology modeling, by taking the MTHFR structures from Escherichia coli and Thermus thermophilus as templates. Subsequently, the modeled structure was docked with FAD using Glide, which revealed a very good binding affinity, authenticated by a Glide XP score of -10.3983 (kcal mol(-1)). The MTHFR was mutated by changing Alanine 222 to Valine. The wild-type MTHFR-FAD complex and the Ala222Val mutant MTHFR-FAD complex were subjected to molecular dynamics simulation over 50 ns period. The average difference in backbone root mean square deviation (RMSD) between wild and mutant variant was found to be ~.11 Å. The greater degree of fluctuations in the mutant protein translates to increased conformational stability as a result of mutation. The FAD-binding ability of the mutant MTHFR was also found to be significantly lowered as a result of decreased protein grip caused by increased conformational flexibility. The study provides insights into the Ala222Val mutation of human MTHFR that induces major conformational changes in the tertiary structure, causing a significant reduction in the FAD-binding affinity.

Effect of T68A/N126Y mutations on the conformational and ligand binding landscape of Coxsackievirus B3 3C protease.

3C protease of Coxsackievirus B3 (CVB3) plays an essential role in the viral replication cycle, and therefore, emerged as an attractive therapeutic target for the treatment of human diseases caused by CVB3 infection. In this study, we report the first account of the molecular impact of the T68A/N126Y double mutant (Mutant(Bound)) using an integrated computational approach. Molecular dynamics simulation and post-dynamics binding free energy, principal component analysis (PCA), hydrogen bond occupancy, SASA, R(g) and RMSF confirm that T68A/N126Y instigated an increased conformational flexibility due to the loss of intra- and inter-molecular hydrogen bond interactions and other prominent binding forces, which led to a decreased protease grip on the ligand (3CPI). The double mutations triggered a distortion orientation of 3CPI in the active site and decreases the binding energy, ΔG(bind) (∼3 kcal mol(-1)), compared to the wild type (Wild(Bound)). The van der Waals and electrostatic energy contributions coming from residues 68 and 126 are lower for Mutant(Bound) when compared with Wild(Bound). In addition, variation in the overall enzyme motion as evident from the PCA, distorted hydrogen bonding network and loss of protein-ligand interactions resulted in a loss of inhibitor efficiency. The comprehensive molecular insight gained from this study should be of great importance in understanding the drug resistance against CVB3 3C protease; also, it will assist in the designing of novel Coxsackievirus B3 inhibitors with high ligand efficacy on resistant strains.

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.

Chikungunya virus (CHIKV) inhibitors from natural sources: a medicinal chemistry perspective.

Chikungunya virus (CHIKV) is one of the re-emerging "neglected" tropical diseases whose recent outbreak affected not only Africa and South-East Asia but also several parts of America and Europe. To date, despite its serious nature, no antivirals or vaccines were developed in order to counter this resurgent infectious disease. The recent advancement in crystallography and availability of crystal structures of certain domains of CHIKV initiates the development of anti-CHIKV agents using structure-based drug design or synthetic medicinal chemistry approach. Despite the fact that almost 50% of the new chemical entities against several biological targets were either obtained from natural products or natural product analogues, a very humble effort was directed towards identification of novel CHIKV inhibitors from natural products. In this review, besides a brief overview on CHIKV as well as the nature as a source of medicines, we highlight the current progress and future steps towards the discovery of CHIKV inhibitors from natural products. This report could pave the road towards the design of novel semi-synthetic derivatives with enhanced anti-viral activities.