The Mycobacterium tuberculosis PE_PGRS Protein Family Acts as an Immunological Decoy to Subvert Host Immune Response.

Mycobacterium tuberculosis (M.tb) is a successful pathogen that can reside within the alveolar macrophages of the host and can survive in a latent stage. The pathogen has evolved and developed multiple strategies to resist the host immune responses. M.tb escapes from host macrophage through evasion or subversion of immune effector functions. M.tb genome codes for PE/PPE/PE_PGRS proteins, which are intrinsically disordered, redundant and antigenic in nature. These proteins perform multiple functions that intensify the virulence competence of M.tb majorly by modulating immune responses, thereby affecting immune mediated clearance of the pathogen. The highly repetitive, redundant and antigenic nature of PE/PPE/PE_PGRS proteins provide a critical edge over other M.tb proteins in terms of imparting a higher level of virulence and also as a decoy molecule that masks the effect of effector molecules, thereby modulating immuno-surveillance. An understanding of how these proteins subvert the host immunological machinery may add to the current knowledge about M.tb virulence and pathogenesis. This can help in redirecting our strategies for tackling M.tb infections.

Predicting phosphorylation sites using machine learning by integrating the sequence, structure, and functional information of proteins.

BACKGROUND: Post-translational modification (PTM) is a biological process that alters proteins and is therefore involved in the regulation of various cellular activities and pathogenesis. Protein phosphorylation is an essential process and one of the most-studied PTMs: it occurs when a phosphate group is added to serine (Ser, S), threonine (Thr, T), or tyrosine (Tyr, Y) residue. Dysregulation of protein phosphorylation can lead to various diseases-most commonly neurological disorders, Alzheimer's disease, and Parkinson's disease-thus necessitating the prediction of S/T/Y residues that can be phosphorylated in an uncharacterized amino acid sequence. Despite a surplus of sequencing data, current experimental methods of PTM prediction are time-consuming, costly, and error-prone, so a number of computational methods have been proposed to replace them. However, phosphorylation prediction remains limited, owing to substrate specificity, performance, and the diversity of its features. METHODS: In the present study we propose machine-learning-based predictors that use the physicochemical, sequence, structural, and functional information of proteins to classify S/T/Y phosphorylation sites. Rigorous feature selection, the minimum redundancy/maximum relevance approach, and the symmetrical uncertainty method were employed to extract the most informative features to train the models. RESULTS: The RF and SVM models generated using diverse feature types in the present study were highly accurate as is evident from good values for different statistical measures. Moreover, independent test sets and benchmark validations indicated that the proposed method clearly outperformed the existing methods, demonstrating its ability to accurately predict protein phosphorylation. CONCLUSIONS: The results obtained in the present work indicate that the proposed computational methodology can be effectively used for predicting putative phosphorylation sites further facilitating discovery of various biological processes mechanisms.

PGRS Domain of Rv0297 of Mycobacterium tuberculosis Functions in A Calcium Dependent Manner.

Mycobacterium tuberculosis (M.tb), the pathogen causing tuberculosis, is a major threat to human health worldwide. Nearly 10% of M.tb genome encodes for a unique family of PE/PPE/PGRS proteins present exclusively in the genus Mycobacterium. The functions of most of these proteins are yet unexplored. The PGRS domains of these proteins have been hypothesized to consist of Ca2+ binding motifs that help these intrinsically disordered proteins to modulate the host cellular responses. Ca2+ is an important secondary messenger that is involved in the pathogenesis of tuberculosis in diverse ways. This study presents the calcium-dependent function of the PGRS domain of Rv0297 (PE_PGRS5) in M.tb virulence and pathogenesis. Tandem repeat search revealed the presence of repetitive Ca2+ binding motifs in the PGRS domain of the Rv0297 protein (Rv0297PGRS). Molecular Dynamics simulations and fluorescence spectroscopy revealed Ca2+ dependent stabilization of the Rv0297PGRS protein. Calcium stabilized Rv0297PGRS enhances the interaction of Rv0297PGRS with surface localized Toll like receptor 4 (TLR4) of macrophages. The Ca2+ stabilized binding of Rv0297PGRS with the surface receptor of macrophages enhances its downstream consequences in terms of Nitric Oxide (NO) production and cytokine release. Thus, this study points to hitherto unidentified roles of calcium-modulated PE_PGRS proteins in the virulence of M.tb. Understanding the pathogenic potential of Ca2+ dependent PE_PGRS proteins can aid in targeting these proteins for therapeutic interventions.

Computational models for the prediction of adverse cardiovascular drug reactions.

BACKGROUND: Predicting adverse drug reactions (ADRs) has become very important owing to the huge global health burden and failure of drugs. This indicates a need for prior prediction of probable ADRs in preclinical stages which can improve drug failures and reduce the time and cost of development thus providing efficient and safer therapeutic options for patients. Though several approaches have been put forward for in silico ADR prediction, there is still room for improvement. METHODS: In the present work, we have used machine learning based approach for cardiovascular (CV) ADRs prediction by integrating different features of drugs, biological (drug transporters, targets and enzymes), chemical (substructure fingerprints) and phenotypic (therapeutic indications and other identified ADRs), and their two and three level combinations. To recognize quality and important features, we used minimum redundancy maximum relevance approach while synthetic minority over-sampling technique balancing method was used to introduce a balance in the training sets. RESULTS: This is a rigorous and comprehensive study which involved the generation of a total of 504 computational models for 36 CV ADRs using two state-of-the-art machine-learning algorithms: random forest and sequential minimization optimization. All the models had an accuracy of around 90% and the biological and chemical features models were more informative as compared to the models generated using chemical features. CONCLUSIONS: The results obtained demonstrated that the predictive models generated in the present study were highly accurate, and the phenotypic information of the drugs played the most important role in drug ADRs prediction. Furthermore, the results also showed that using the proposed method, different drugs properties can be combined to build computational predictive models which can effectively predict potential ADRs during early stages of drug development.

Structural basis for isoniazid resistance in KatG double mutants of Mycobacterium tuberculosis.

The failure of drugs for effective treatment against infectious diseases can be attributed to resistant forms of causative agents. The evasive nature of Mycobacterium tuberculosis is partly associated to its physical features, such as having a thick cell wall and incorporation of beneficial mutations leading to drug resistance. The pro drug Isoniazid (INH) interacts with an enzyme catalase peroxidase to get converted into its active form and upon activation stops the cell wall synthesis thus killing the Mycobacterium. The most common mutation i.e. S315T leads to high degree of drug resistance by virtue of its position in the active site. Here, we have characterized the prominent attributes of two double mutant isolates S315 T/D194G and S315T/M624V which are multi drug resistant and extremely drug resistant, respectively. Protein models were generated using the crystal structure which were then subjected to energy minimization and long term molecular dynamics simulations. Further, computational analysis showed decreasing ability of INH binding to the mutants in order of: Native > S315T/D194G > S315T/M624V. Also, a trend was observed that as the docking score and binding area decreased, there was a significant increase in the distortion of the 3D geometry of the mutants as observed by PCA analysis.

Role of pncA gene mutations W68R and W68G in pyrazinamide resistance.

Mycobacterium tuberculosis (Mtb) resistance toward anti-tuberculosis drugs is a widespread problem. Pyrazinamide (PZA) is a first line antitubercular drug that kills semi-dormant bacilli when converted into its activated form, that is, pyrazinoic acid (POA) by Pyrazinamidase (PZase) enzyme coded by pncA gene. In this study, we conducted several analyses on native and mutant structures (W68R, W68G) of PZase before and after docking with the PZA drug to explore the molecular mechanism behind PZA resistance caused due to pncA mutations. Structural changes caused by mutations were studied with respect to their effects on functionality of protein. Docking was performed to analyze the protein-drug binding and comparative analysis was done to observe how the mutations affect drug binding affinity and binding site on protein. Native PZase protein was observed to have the maximum binding affinity in terms of docking score as well as shape complementarity in comparison to the mutant forms. Molecular dynamics simulation analyses showed that mutation in the 68th residue of protein results in a structural change at its active site which further affects the biological function of protein, that is, conversion of PZA to POA. Mutations in the protein thereby led to PZA resistance in the bacterium due to the inefficient binding.

Mechanistic Principles Behind Molecular Mechanism of Rifampicin Resistance in Mutant RNA Polymerase Beta Subunit of Mycobacterium tuberculosis.

Evolution of drug-resistant Mycobacterium strains threatens the TB treatment and control programs globally. Rifampicin (RIF) is an important first line antitubercular drug. Resistance to Rifampicin is caused mainly by mutations in its target RNA polymerase beta subunit protein (RpoB). RpoB contains a Rifampicin resistance determining region (RRDR) and has several potent sites for mutations. In this study, we have investigated mutations of a single site (H451) to eight different amino acids, involved in RIF resistance. Long-term molecular dynamics simulations were performed on wild type (WT) and mutant protein structures and various structural analysis were carried out to elucidate the dynamic behavior of WT and mutant forms. Essential dynamics uncovered the difference in conformational flexibility and collective modes of motions between WT and mutants. MMPBSA calculations and interaction pattern analysis revealed the binding site relocation in some mutants. This study presents an exhaustive analysis of RIF binding to the WT and mutant RpoB and clearly highlights structural mechanism for differences in stable binding of Rifampicin with WT than the mutant targets. J. Cell. Biochem. 118: 4594-4606, 2017. © 2017 Wiley Periodicals, Inc.

Double Mutants in DNA Gyrase Lead to Ofloxacin Resistance in Mycobacterium tuberculosis.

Fluoroquinolones are among the most important classes of highly effective antibacterial drugs, exhibiting wide range of activity to cure infectious diseases. Ofloxacin is second generation fluoroquinolone approved by FDA for the treatment of tuberculosis by selectively inhibiting DNA gyrase. However, the emergence of drug resistance owing to mutations in DNA gyrase poses intimidating challenge for the effective therapy of this drug. The double mutants GyrAA90V GyrBD500N and GyrAA90V GyrBT539N are reported to be implicated in conferring higher levels of OFX resistance. The present study was designed to unravel the molecular principles behind development of resistance by the bug against fluoroquinolones. Our results highlighted that polar interactions play critical role in the development of drug resistance and highlight the significant correlation between the free energy calculations predicted by MM-PBSA and stability of the ligand-bound complexes. Modifications at the OFX binding pocket due to amino acid substitution leads to fewer hydrogen bonds in mutants DNA gyrase-OFX complex, which determined the low susceptibility of the ligand in inhibiting the mutant protein. This study provides a structural rationale to the mutation-based resistance to ofloxacin and will pave way for development potent fluoroquinolone-based resistant-defiant drugs. J. Cell. Biochem. 118: 2950-2957, 2017. © 2017 Wiley Periodicals, Inc.

Novel group-based QSAR and combinatorial design of CK-1δ inhibitors as neuroprotective agents.

BACKGROUND: Tar DNA binding protein 43 (TDP-43) hyperphosphorylation, caused by Casein kinase 1 (CK-1) protein isoforms, is associated with the onset and progression of Amyotrophic Lateral Sclerosis (ALS). Among the reported isoforms and splice variants of CK-1 protein superfamily, CK-1δ is known to phosphorylate different serine and threonine sites on TDP-43 protein in vitro and thus qualifies as a potential target for ALS treatment. RESULTS: The developed GQSAR (group based quantitative structure activity relationship) model displayed satisfactory statistical parameters for the dataset of experimentally reported N-Benzothiazolyl-2-Phenyl Acetamide derivatives. A combinatorial library of molecules was also generated and the activities were predicted using the statistically sound GQSAR model. Compounds with higher predicted inhibitory activity were screened against CK-1δ that resulted in to the potential novel leads for CK-1δ inhibition. CONCLUSIONS: In this study, a robust fragment based QSAR model was developed on a congeneric set of experimentally reported molecules and using combinatorial library approach, a series of molecules were generated from which we report two top scoring, CK-1δ inhibitors i.e., CHC (6-benzyl-2-cyclopropyl-4-{[(4-cyclopropyl-6-ethyl-1,3-benzothiazol-2-yl)carbamoyl]methyl}j-3-fluorophenyl hydrogen carbonate) and DHC (6-benzyl-4-{[(4-cyclopropyl-6-ethyl-1,3-benzothiazol-2-yl)carbamoyl]methyl}-2-(decahydronaphthalen-1-yl)-3-hydroxyphenyl hydrogen carbonate) with binding energy of -6.11 and -6.01 kcal/mol, respectively.

Computational identification of novel natural inhibitors of glucagon receptor for checking type II diabetes mellitus.

BACKGROUND: Interaction of the small peptide hormone glucagon with glucagon receptor (GCGR) stimulates the release of glucose from the hepatic cells during fasting; hence GCGR performs a significant function in glucose homeostasis. Inhibiting the interaction between glucagon and its receptor has been reported to control hepatic glucose overproduction and thus GCGR has evolved as an attractive therapeutic target for the treatment of type II diabetes mellitus. RESULTS: In the present study, a large library of natural compounds was screened against 7 transmembrane domain of GCGR to identify novel therapeutic molecules that can inhibit the binding of glucagon with GCGR. Molecular dynamics simulations were performed to study the dynamic behaviour of the docked complexes and the molecular interactions between the screened compounds and the ligand binding residues of GCGR were analysed in detail. The top scoring compounds were also compared with already documented GCGR inhibitors- MK-0893 and LY2409021 for their binding affinity and other ADME properties. Finally, we have reported two natural drug like compounds PIB and CAA which showed good binding affinity for GCGR and are potent inhibitor of its functional activity. CONCLUSION: This study contributes evidence for application of these compounds as prospective small ligand molecules against type II diabetes. Novel natural drug like inhibitors against the 7 transmembrane domain of GCGR have been identified which showed high binding affinity and potent inhibition of GCGR.

Structural insights into mode of actions of novel natural Mycobacterium protein tyrosine phosphatase B inhibitors.

BACKGROUND: Tuberculosis has become a major health problem being the second leading cause of death worldwide. Mycobacterium tuberculosis secretes a virulence factor, protein tyrosine phosphatase B (mPTPB) in the cytoplasm of host macrophage which suppresses its natural innate immune response and helps the pathogen survive and proliferate in the phagosome. The present study aims at indentifying potent inhibitors of mPTPB by using computational approaches of ligand based molecular modeling and docking studies. RESULTS: A 3D QSAR model was developed using a set of benzofuran salicylic acid based mPTPB inhibitors with experimentally known IC50 values. The model was generated using the statistical method of principle component regression analysis in combination with step wise forward variable selection algorithm. It was observed that steric and hydrophobic descriptors positively contribute towards the inhibitory activity of the ligands. The developed model had a robust internal as well as external predictive power as indicated by the q(2) value of 0.8920 and predicted r(2) value of 0.8006 respectively. Hence, the generated model was used to screen a large set of naturally occurring chemical compounds and predict their biological activity to identify more potent natural compounds targeting mPTPB. The two top potential hits (with pIC50 value of 1.459 and 1.677 respectively) had a similar interaction pattern as that of the most potent compound (pIC50 = 1.42) of the congeneric series. CONCLUSION: The contour plot provided a better understanding of the relationship between structural features of substituted benzofuran salicylic acid derivatives and their activities which would facilitate design of novel mPTPB inhibitors. The QSAR modeling was used to obtain an equation, correlating the important steric and hydrophobic descriptors with the pIC50 value. Thus, we report two natural compounds of inhibitory nature active against mPTPB enzyme of Mycobacterium tuberculosis. These inhibitors have the potential to evolve as lead molecules in the development of drugs for the treatment of tuberculosis.

Identification and characterization of repurposed small molecule inhibitors of Mycobacterium tuberculosis caseinolytic protease B (ClpB) as anti-mycobacterials.

Mycobacterium tuberculosis (Mtb) caseinolytic protease B (ClpB) is a chaperone possessing a unique ability to resolubilize the aggregated proteins in vivo. ClpB has been shown to be important for the survival of Mtb within the host. Thus, it appears to be a promising target to develop new therapeutic molecules against tuberculosis. In this study, we have screened FDA approved compounds in silico to identify inhibitors against Mtb ClpB. In our screen, several compounds interacted with ClpB. The top four compounds, namely framycetin, gentamicin, ribostamycin and tobramycin showing the highest binding energy were selected for further investigation. MD simulations and tryptophan-based quenching of ClpB-drug complexes established that the selected inhibitors stably interacted with the target protein. The inhibitor and protein complexes were found to be stabilized by hydrogen bonding, and hydrophobic interactions. Although, the compounds did not affect the ATPase activity of ClpB significantly, the protein resolubilization activity of ClpB was remarkably reduced in their presence. All four compounds potently inhibited the growth of Mtb H37Ra. The antimycobacterial activity of the compounds appears to be due the inhibition of functional ClpB oligomer formation, in turn affecting its chaperonic activity.

Redesigning the kinetics of lysozyme amyloid aggregation by cephalosporin molecules.

In lysozyme amyloidosis, fibrillar aggregates of lysozyme are associated with severe renal, hepatic, and gastrointestinal manifestations, with no definite therapy. Current drugs are now being tested in amyloidosis clinical trials as aggregation inhibitors to mitigate disease progression. The tetracycline group among antimicrobials in use is in phase II of clinical trials, whereas some macrolides and cephalosporins have shown neuroprotection. In the present study, two cephalosporins, ceftazidime (CZD) and cefotaxime (CXM), and a glycopeptide, vancomycin (VNC), are evaluated for inhibition of amyloid aggregation of hen egg white lysozyme (HEWL) under two conditions (i) 4 M guanidine hydrochloride (GuHCl) at pH 6.5 and 37° C, (ii) At pH 1.5 and 65 °C. Fluorescence quench titration and molecular docking methods report that CZD, CXM, and VNC interact more strongly with the partially folded intermediates (PFI) in comparison to the protein's natural state (N). However, only CZD and CXM proficiently inhibit the aggregation. Transmission electron microscopy, tinctorial assessments, and aggregation kinetics all support oligomer-level inhibition. Transition structures in CZD-HEWL and CXM-HEWL aggregation are shown by circular dichroism (CD). On the other hand, kinetic variables and soluble fraction assays point to a localized association of monomers. Intrinsic fluorescence (IF),1-Anilino 8-naphthalene sulphonic acid, and CD demonstrate structural and conformational modifications redesigning the PFI. GuHCl-induced unfolding and differential scanning fluorimetry suggested that the PFI monomers bound to CZD and CXM exhibited partial stability. Our results present two mechanisms that function in both solution conditions, creating a novel avenue for the screening of putative inhibitors for drug repurposing. We extend our proposed mechanisms in the designing of physical inhibitors of amyloid aggregation considering shorter time frames and foolproof methods.Communicated by Ramaswamy H. Sarma.

Drug repurposing has overcome failures in drug discovery and has reduced the overall time and cost of drug discovery and development.We examined the effect of screened antibiotics, ceftazidime (CZD), cefotaxime (CXM), and vancomycin (VNC) on lysozyme aggregation under two solution conditions.These antibiotics inhibit/modulate the aggregation reactions by strongly interacting with aggregation-prone intermediate and modulation of conformation and stability.Our study puts forward with caution two cephalosporins for aggregation inhibition studies.

Computational exploration of the genomic assignments, molecular structure, and dynamics of the ccdABXn2 toxin-antitoxin homolog with its bacterial target, the DNA gyrase, in the entomopathogen Xenorhabdus nematophila.

Toxin-antitoxin (TA) modules, initially discovered on bacterial plasmids and subsequently identified within chromosomal contexts, hold a pivotal role in the realm of bacterial physiology. Among these, the pioneering TA system, ccd (Control of Cell Death), primarily localized on the F-plasmid, is known for its orchestration of plasmid replication with cellular division. Nonetheless, the precise functions of such systems within bacterial chromosomal settings remain a compelling subject that demands deeper investigation. To bridge this knowledge gap, our study focuses on exploring ccdABXn2, a chromosomally encoded TA module originating from the entomopathogenic bacterium Xenorhabdus nematophila. We meticulously delved into the system's genomic assignments, structural attributes, and functional interplay. Our findings uncovered intriguing patterns-CcdB toxin homologs exhibited higher conservation levels compared to their CcdA antitoxin counterparts. Moreover, we constructed secondary as well as tertiary models for both the CcdB toxin and CcdA antitoxin using threading techniques and subsequently validated their structural integrity. Our exploration extended to the identification of key interactions, including the peptide interaction with gyrase for the CcdB homolog and CcdB toxin interactions for the CcdA homolog, highlighting the intricate TA interaction network. Through docking and simulation analyses, we unequivocally demonstrated the inhibition of replication via binding the CcdB toxin to its target, DNA gyrase. These insights provide valuable knowledge about the metabolic and physiological roles of the chromosomally encoded ccdABXn2 TA module within the context of X. nematophila, significantly enhancing our comprehension of its functional significance within the intricate ecosystem of the bacterial host.Communicated by Ramaswamy H. Sarma.

Unravelling the potential of Triflusal as an anti-TB repurposed drug by targeting replication protein DciA.

The increasing prevalence of drug-resistant Tuberculosis (TB) is imposing extreme difficulties in controlling the TB infection rate globally, making treatment critically challenging. To combat the prevailing situation, it is crucial to explore new anti-TB drugs with a novel mechanism of action and high efficacy. The Mycobacterium tuberculosis (M.tb)DciA is an essential protein involved in bacterial replication and regulates its growth. DciA interacts with DNA and provides critical help in binding other replication machinery proteins to the DNA. Moreover, the lack of any structural homology of M.tb DciA with human proteins makes it an appropriate target for drug development. In this study, FDA-approved drugs were virtually screened against M.tb DciA to identify potential inhibitors. Four drugs namely Lanreotide, Risedronate, Triflusal, and Zoledronic acid showed higher molecular docking scores. Further, molecular dynamics simulations analysis of DciA-drugs complexes reported stable interaction, more compactness, and reduced atomic motion. The anti-TB activity of drugs was further evaluated under in vitro and ex vivo conditions where Triflusal was observed to have the best possible activity with the MIC of 25 µg/ml. Our findings present novel DciA inhibitors and anti-TB activity of Triflusal. Further investigations on the use of Triflusal may lead to the discovery of a new anti-TB drug.

Targeting of essential mycobacterial replication enzyme DnaG primase revealed Mitoxantrone and Vapreotide as novel mycobacterial growth inhibitors.

Tuberculosis (TB) is the second leading cause of mortality after COVID-19, with a global death toll of 1.6 million in 2021. The escalating situation of drug-resistant forms of TB has threatened the current TB management strategies. New therapeutics with novel mechanisms of action are urgently required to address the current global TB crisis. The essential mycobacterial primase DnaG with no structural homology to homo sapiens presents itself as a good candidate for drug targeting. In the present study, Mitoxantrone and Vapreotide, two FDA-approved drugs, were identified as potential anti-mycobacterial agents. Both Mitoxantrone and Vapreotide exhibit a strong Minimum Inhibitory Concentration (MIC) of ≤25µg/ml against both the virulent (M.tb-H37Rv) and avirulent (M.tb-H37Ra) strains of M.tb. Extending the validations further revealed the inhibitory potential drugs in ex vivo conditions. Leveraging the computational high-throughput multi-level docking procedures from the pool of ~2700 FDA-approved compounds, Mitoxantrone and Vapreotide were screened out as potential inhibitors of DnaG. Extensive 200 ns long all-atoms molecular dynamic simulation of DnaGDrugs complexes revealed that both drugs bind strongly and stabilize the DnaG during simulations. Reduced solvent exposure and confined motions of the active centre of DnaG upon complexation with drugs indicated that both drugs led to the closure of the active site of DnaG. From this study's findings, we propose Mitoxantrone and Vapreotide as potential anti-mycobacterial agents, with their novel mechanism of action against mycobacterial DnaG.

Mechanistic insights into mode of action of novel natural cathepsin L inhibitors.

BACKGROUND: Development of a cancerous cell takes place when it ceases to respond to growth-inhibiting signals and multiplies uncontrollably and can detach and move to other parts of the body; the process called as metastasis. A particular set of cysteine proteases are very active during cancer metastasis, Cathepsins being one of them. They are involved in tumor growth and malignancy and have also been reported to be overexpressed in tumor cell lines. In the present study, a combinatorial approach comprising three-dimensional quantitative structure-activity relationship (3D QSAR), ligand-based pharmacophore modelling and search followed by cathepsin L structure-based high throughput screening was carried out using an initial set of 28 congeneric thiosemicarbazone derivatives as cathepsin L inhibitors. A 3D QSAR was derived using the alignment of a common thiosemicarbazone substructure. Essential structural features responsible for biological activity were taken into account for development of a pharmacophore model based on 29 congeneric thiosemicarbazone derivatives. This model was used to carry out an exhaustive search on a large dataset of natural compounds. A further cathepsin L structure-based screen identified two top scoring compounds as potent anti-cancer leads. RESULTS: The generated 3D QSAR model showed statistically significant results with an r(2) value of 0.8267, cross-validated correlation coefficient q(2) of 0.7232, and a pred_r(2) (r(2) value for test set) of 0.7460. Apart from these, a high F test value of 30.2078 suggested low probability of the model's failure. The pharmacophoric hypothesis chosen for searching the natural compound libraries was identified as DDHRR, where two Ds denote 2 hydrogen donors, H represents a hydrophobic group and two Rs represent aromatic rings, all of which are essential for the biological activity. We report two potential drug leads ZINC08764437 (NFP) and ZINC03846634 (APQ) obtained after a combined approach of pharmacophore-based search and structure-based virtual screen. These two compounds displayed extra precision docking scores of -7.972908 and -7.575686 respectively suggesting considerable binding affinity for cathepsin L. High activity values of 5.72 and 5.75 predicted using the 3D QSAR model further substantiated the inhibitory potential of these identified leads. CONCLUSION: The present study attempts to correlate the structural features of thiosemicarbazone group with their biological activity by development of a robust 3D QSAR model. Being statistically valid, this model provides near accurate values of the activities predicted for the congeneric set on which it is based. These predicted activities are good for the test set compounds making it indeed a statistically sound 3D QSAR model. The identified pharmacophore model DDHRR.8 comprised of all the essential features required to interact with the catalytic triad of cathepsin L. A search for natural compounds based on this pharmacophore followed by docking studies further screened out two top scoring candidates: NFP and AFQ. The high binding affinity and presence of essential structural features in these two compounds make them ideal for consideration as natural anti-tumoral agents. Activity prediction using 3D QSAR model further validated their potential as worthy drug candidates against cathepsin L for treatment of cancer.

Resisting resistant Mycobacterium tuberculosis naturally: mechanistic insights into the inhibition of the parasite's sole signal peptidase Leader peptidase B.

Tuberculosis (TB) is the second highest cause of mortality after HIV/AIDS and is one of the leading public health problems worldwide. The growing resistance to anti-TB drugs and the recalcitrant nature of tenacious infections present arduous challenges for the treatment of TB. Thus, the need to develop therapeutics against novel drug targets to help overcome multi-drug resistant TB is inevitable. Leader peptidase B (LepB), the sole signal peptidase of Mycobacterium tuberculosis (MTb), is one such potential drug target. The present work aims at identifying potential inhibitors of LepB, so as to repress the formation of the functional proteins essential for the growth and pathogenesis of MTb. In this study, we screened a large dataset of natural compounds against LepB using a high throughput approach. The screening was directed toward a binding pocket consisting of residues, some of which are critical for the catalytic activity of the enzyme, while others are part of the conserved domains of the signal peptidases. We also carried out molecular dynamics simulations of the two top-scoring compounds in order to study their molecular interactions with the active site functional residues of LepB and also to assess their dynamic behavior. We report herein two prospective non-covalent type inhibitory drugs of natural origin which are active against tuberculosis. These lead molecules possess improved binding properties, have low toxicity and are specific against MTb.

Role of a substrate binding pocket in the amino terminal domain of Mycobacterium tuberculosis caseinolytic protease B (ClpB) in its function.

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis when infects the host encounters several stresses within the host, resulting in aggregation of its proteins. To resolve this problem Mtb uses chaperones to either repair the damage or degrade the aggregated proteins. Mtb caseinolytic protein B (ClpB) helps in the prevention of aggregation and also resolubilization of aggregated proteins in bacteria, which is important for the survival of Mtb in the host. To function optimally, ClpB associates with its co-partners DnaK, DnaJ, and GrpE. The role of N-terminal domain (NTD) of Mtb ClpB in its function is not well understood. In this context, we investigated the interaction of three substrate mimicking peptides with the NTD of Mtb ClpB in silico. A substrate binding pocket, within the NTD of ClpB comprising of residues L136, R137, E138, K142, R144, R148, V149, Y158, and Y162 forming an ɑ-helix was thus identified. The residues L136 and R137 of the ɑ-helix were found to be important for the interaction of DnaK to ClpB. Further, nine single alanine recombinant variants of the identified residues were generated. As compared to the wild-type Mtb ClpB all the Mtb ClpB variants generated in this study were found to have reduced ATPase and protein refolding activity indicating the importance of the substrate binding pocket in ClpB function. The study demonstrates that the NTD of Mtb ClpB is important for its substrate interaction activity, and the substrate binding pocket identified in this study plays a crucial role in this interaction.Communicated by Ramaswamy H. Sarma.

Potential Repurposed Drug Candidates for Tuberculosis Treatment: Progress and Update of Drugs Identified in Over a Decade.

The devastating impact of Tuberculosis (TB) has been a menace to mankind for decades. The World Health Organization (WHO) End TB Strategy aims to reduce TB mortality up to 95% and 90% of overall TB cases worldwide, by 2035. This incessant urge will be achieved with a breakthrough in either a new TB vaccine or novel drugs with higher efficacy. However, the development of novel drugs is a laborious process involving a timeline of almost 20-30 years with huge expenditure; on the other hand, repurposing previously approved drugs is a viable technique for overcoming current bottlenecks in the identification of new anti-TB agents. The present comprehensive review discusses the progress of almost all the repurposed drugs that have been identified to the present day (∼100) and are in the development or clinical testing phase against TB. We have also emphasized the efficacy of repurposed drugs in combination with already available frontline anti-TB medications along with the scope of future investigations. This study would provide the researchers a detailed overview of nearly all identified anti-TB repurposed drugs and may assist them in selecting the lead compounds for further in vivo/clinical research.