Dibyabhaba Pradhan

In silico identification of common putative drug targets in Leptospira interrogans.

Infectious diseases are the leading causes of death worldwide. Hence, there is a need to develop new antimicrobial agents. Traditional method of drug discovery is time consuming and yields a few drug targets with little intracellular information for guiding target selection. Thus, focus in drug development has been shifted to computational comparative genomics for identifying novel drug targets. Leptospirosis is a worldwide zoonosis of global concern caused by Leptospira interrogans. Availability of L. interrogans serovars and human genome sequences facilitated to search for novel drug targets using bioinformatics tools. The genome sequence of L. interrogans serovar Copenhageni has 5,124 genes while that of serovar Lai has 4,727 genes. Through subtractive genomic approach 218 genes in serovar Copenhageni and 158 genes in serovar Lai have been identified as putative drug targets. Comparative genomic approach had revealed that 88 drug targets were common to both the serovars. Pathway analysis using the Kyoto Encyclopaedia of Genes and Genomes revealed that 66 targets are enzymes and 22 are non-enzymes. Sixty two common drug targets were predicted to be localized in cytoplasm and 16 were surface proteins. The identified potential drug targets form a platform for further investigation in discovery of novel therapeutic compounds against Leptospira.

Para-(benzoyl)-phenylalanine as a potential inhibitor against LpxC of Leptospira spp.: homology modeling, docking, and molecular dynamics study

Leptospira interrogans, a Gram-negative bacterial pathogen is the main cause of human leptospirosis. Lipid A is a highly immunoreactive endotoxic center of lipopolysaccharide (LPS) that anchors LPS into the outer membrane of Leptospira. Discovery of compounds inhibiting lipid-A biosynthetic pathway would be promising for dissolving the structural integrity of membrane leading to cell lysis and death of Leptospira. LpxC, a unique enzyme of lipid-A biosynthetic pathway was identified as common drug target of Leptospira. Herein, homology modeling, docking, and molecular dynamics (MD) simulations were employed to discover potential inhibitors of LpxC. A reliable tertiary structure of LpxC in complex with inhibitor BB-78485 was constructed in Modeller 9v8. A data-set of BB-78485 structural analogs were docked with LpxC in Maestro v9.2 virtual screening workflow, which implements three stage Glide docking protocol. Twelve lead molecules with better XP Gscore compared to BB-78485 were proposed as potential inhibitors of LpxC. Para-(benzoyl)-phenylalanine – that showed lowest XP Gscore (−10.35 kcal/mol) – was predicted to have best binding affinity towards LpxC. MD simulations were performed for LpxC and para-(benzoyl)-phenylalanine docking complex in Desmond v3.0. Trajectory analysis showed the docking complex and inter-molecular interactions was stable throughout the entire production part of MD simulations. The results indicate para-(benzoyl)-phenylalanine as a potent drug molecule against leptospirosis. An animated Interactive 3D Complement (I3DC) is available in Proteopedia at http://proteopedia.org/w/Journal:JBSD:10

Virtual screening for potential inhibitors of homology modeled Leptospira interrogans MurD ligase

The life-threatening infections caused by Leptospira serovars remain a global challenge since long time. Prevention of infection by controlling environmental factors being difficult to practice in developing countries, there is a need for designing potent anti-leptospirosis drugs. ATP-dependent MurD involved in biosynthesis of peptidoglycan was identified as common drug target among pathogenic Leptospira serovars through subtractive genomic approach. Peptidoglycan biosynthesis pathway being unique to bacteria and absent in host represents promising target for antimicrobial drug discovery. Thus, MurD 3D models were generated using crystal structures of 1EEH and 2JFF as templates in Modeller9v7. Structural refinement and energy minimization of the model was carried out in Maestro 9.0 applying OPLS-AA 2001 force field and was evaluated through Procheck, ProSA, PROQ, and Profile 3D. The active site residues were confirmed from the models in complex with substrate and inhibitor. Four published MurD inhibitors (two phosphinics, one sulfonamide, and one benzene 1,3-dicarbixylic acid derivative) were queried against more than one million entries of Ligand.Info Meta-Database to generate in-house library of 1,496 MurD inhibitor analogs. Our approach of virtual screening of the best-ranked compounds with pharmacokinetics property prediction has provided 17 novel MurD inhibitors for developing anti-leptospirosis drug targeting peptidoglycan biosynthesis pathway.

Docking Studies towards Exploring Antiviral Compounds against Envelope Protein of Yellow Fever Virus

Yellow fever is among one of the most lethal viral diseases for which approved antiviral therapies were yet to be discovered. Herein, functional assignment of complete YFV proteome was done through support vector machine. Major envelope (E) protein that mediates entry of YFV into host cell was selected as a potent molecular target. Three dimensional structure of the molecular target was predicted using Modeller9v7. The model was optimized in Maestro9.0 applying OPLS AA force field and was evaluated using PROCHECK, ProSA, ProQ and Profile 3D. The BOG pocket residues Val48, Glu197, Thr200, Ile204, Thr265, Thr268 and Gly278 were located in YFV E protein using SiteMap2.3. More than one million compounds of Ligandinfo Meta database were explored using a computational virtual screening protocol targeting BOG pocket of the E protein. Finally, ten top ranked lead molecules with strong binding affinity to BOG pocket of YFV E protein were identified based on XP Gscore. Drug likeliness and comparative bioactivity analysis for these leads using QikProp3.2 had shown that these molecules would have the potential to act as better drug. Thus, the 10 lead molecules suggested in the present study would be of interest as promising starting point for designing antiviral compound against yellow fever.

Identification of Potential Leptospira Phosphoheptose Isomerase Inhibitors Through Virtual High-Throughput Screening

The life-threatening infections caused by Leptospira serovars demand the need for designing anti-leptospirosis drugs. The present study encompasses exploring inhibitors against phosphoheptose isomerase (GmhA) of Leptospira, which is vital for lipopolysaccharide (LPS) biosynthesis and is identified as a common drug target through the subtractive genomic approach. GmhA model was built in Modeller 9v7. Structural refinement and energy minimization of the predicted model was carried out using Maestro 9.0. The refined model reliability was assessed through Procheck, ProSA, ProQ and Profile 3D. The substrate-based virtual high-throughput screening (VHTS) in Ligand.Info Meta-Database tool generated an in-house library of 354 substrate structural analogs. Furthermore, structure-based VHTS from the in-house library with different conformations of each ligand provided 14 novel competitive inhibitors. The model together with insight gained from the VHTS would be a promising starting point for developing anti-leptospirosis competitive inhibitors targeting LPS biosynthesis pathway.

Computer aided subunit vaccine design against pathogenic Leptospira serovars

Epitopes of Leptospira inducing CD4+ T-cell responses by binding to human MHC molecules could critically contribute to the development of subunit vaccines for leptospirosis. Herein, we have identified unique vaccine peptides from outer membrane proteins (OMPs) common to four sequenced pathogenic Leptospira serovars through in silico reverse vaccinology technique. The OMPs were explored for probable antigens using jemboss and screened in ProPred subsequently to predict thirty HLA-DRB epitopes. The HLA-DRB epitopes were validated through published positive control (HA307-PKYVKQNTLKLAT-319), SYFPEITHI and immune epitope database (IEDB) to list twelve epitopes as putative subunit vaccine peptides from nine OMPs. Cation efflux system membrane protein (czcA) having four subunit vaccine peptides, was modeled in Modeller9v7 and evaluated through Procheck, ProSA and ProQ. The HLA-DRB alleles and czcA 3D interactions were studied using Hex 5.1. Further, the T-cell epitopes present in czcA were docked individually with HLA-DRB alleles. The docking result revealed that czcA and its epitopes were interacting well with HLA-DRB alleles, hence would certainly produce cell mediated immune response in host. Thus, czcA and its four subunit vaccine peptides would be ideal T-cell driven efficacious vaccine against leptospirosis.

In Silico Identification of Common Putative Drug Targets among the Pathogens of Bacterial Meningitis

Monitoring infectious emerging diseases, especially the central nervous system infections, has become one of the important priorities in health care system. Epidemiological, serological and bacteriological studies revealed that Streptococcus pneumonia, Neisseria meningitidis, Haemophilus influenzae type b and Staphylococcus aureus are common pathogens of bacterial meningitis. Therefore, identification of common drug targets in these pathogens would be crucial to overcome drug resistance to existing antibiotic therapy. In the present study, comparative proteome analysis, subtractive genomic approach and metabolic pathway analysis were implemented to propose common potential drug targets for pathogens of bacterial meningitis. Streptococcus pneumonia was selected as reference organism, and the common proteins of the pathogens were verified for essentiality in pathogen’s survival, using Database of Essential Genes (DEG). The 213 essential proteins identified were screened for human non-homology. Thirty seven unique essential proteins which are non-homologues to human were proposed as common potential drug targets for pathogens of bacterial meningitis. Pathway analysis revealed that 26 drug targets were enzymes, eight were non-enzymes, and three were conserved hypothetical proteins. Six enzymes were involved in pathways unique to the pathogens of bacterial meningitis. Furthermore, prediction of sub cellular localization and drug prioritization of 37 proteins affirmed that the drug targets would be useful in design and discovery of novel therapeutic compounds against bacterial meningitis.

Genome-based approaches to develop epitope-driven subunit vaccines against pathogens of infective endocarditis

Infective endocarditis (IE) has emerged as a public health problem due to changes in the etiologic spectrum and due to involvement of resistant bacterial strains with increased virulence. Developing potent vaccine is an important strategy to tackle IE. Complete genome sequences of eight selected pathogens of IE paved the way to design common T-cell driven subunit vaccines. Comparative genomics and subtractive genomic analysis were applied to identify adinosine tri phosphate (ATP)-binding cassette (ABC) transporter ATP-binding protein from Streptococcus mitis (reference organism) as common vaccine target. Reverse vaccinology technique was implemented using computational tools such as ProPred, SYFPEITHI, and Immune epitope database. Twenty-one T-cell epitopes were predicted from ABC transporter ATP-binding protein. Multiple sequence alignment of ABC transporter ATP-binding protein from eight selected IE pathogens was performed to identify six conserved T-cell epitopes. The six selected T-cell epitopes were further evaluated at structure level for HLA-DRB binding through homology modeling and molecular docking analysis using Maestro v9.2. The proposed six T-cell epitopes showed better binding affinity with the selected HLA-DRB alleles. Subsequently, the docking complexes of T-cell epitope and HLA-DRBs were ranked based on XP Gscore. The T-cell epitope (208-LNYITPDVV-216)–HLA-DRB1∗0101 (1T5 W) complex having the best XP Gscore (−13.25 kcal/mol) was assessed for conformational stability and interaction stability through molecular dynamic simulation for 10 ns using Desmond v3.2. The simulation results revealed that the HLA-DRB–epitope complex was stable throughout the simulation time. Thus, the epitope would be ideal candidate for T-cell driven subunit vaccine design against infective endocarditis.

Computational approaches to identify common subunit vaccine candidates against bacterial meningitis

Bacterial meningitis, an infection of the membranes (meninges) and cerebrospinal fluid (CSF) surrounding the brain and spinal cord, is a major cause of death and disability all over the world. From perinatal period to adult, four common organisms responsible for most of the bacterial meningitis are Streptococcus pneumonia, Neisseria meningitidis, Haemophilus influenza and Staphylococcus aureus. As the disease is caused by more organisms, currently available vaccines for bacterial meningitis are specific and restricted to some of the serogroups or serotypes of each bacterium. In an effort to design common vaccine against bacterial meningitis, proteomes of the four pathogens were compared to extract seven common surface exposed ABC transporter proteins. Pro-Pred server was used to investigate the seven surface exposed proteins for promiscuous T-cell epitopes prediction. Predicted 22 T-cell epitopes were validated through published positive control, SYFPEITHI and immune epitope database to reduce the epitope dataset into seven. T-cell epitope 162-FMILPIFNV-170 of spermidine/putrescine ABC transporter permease (potH) protein was conserved across the four selected pathogens of bacterial meningitis. Hence, structural analysis was extended for epitope 162-FMILPIFNV-170. Crystal structures of HLA-DRB alleles were retrieved and structure of potH was modeled using Prime v3.0 for structural analysis. Computational docking of HLA-DRB alleles and epitope 162-FMILPIFNV-170 of potH was performed using Glide v5.7. RMSD and RMSF of simulation studies were analyzed by Desmond v3.2. The docking and simulation results revealed that the HLA-DRB-epitope complex was stable with interaction repressive function of HLA. Thus, the epitope would be ideal candidate for T-cell driven subunit vaccine design against bacterial meningitis.

E-pharmacophore-based virtual screening to identify GSK-3β inhibitors.

Abstract Glycogen synthase kinase-3β (GSK-3β) is a serine/threonine kinase which has attracted significant attention during recent years in drug design studies. The deregulation of GSK-3β increased the loss of hippocampal neurons by triggering apoptosis-mediating production of neurofibrillary tangles and alleviates memory deficits in Alzheimer’s disease (AD). Given its role in the formation of neurofibrillary tangles leading to AD, it has been a major therapeutic target for intervention in AD, hence was targeted in the present study. Twenty crystal structures were refined to generate pharmacophore models based on energy involvement in binding co-crystal ligands. Four common e-pharmacophore models were optimized from the 20 pharmacophore models. Shape-based screening of four e-pharmacophore models against nine established small molecule databases using Phase v3.9 had resulted in 1800 compounds having similar pharmacophore features. Rigid receptor docking (RRD) was performed for 1800 compounds and 20 co-crystal ligands with GSK-3β to generate dock complexes. Interactions of the best scoring lead obtained through RRD were further studied with quantum polarized ligand docking (QPLD), induced fit docking (IFD) and molecular mechanics/generalized Born surface area. Comparing the obtained leads to 20 co-crystal ligands resulted in 18 leads among them, lead1 had the lowest docking score, lower binding free energy and better binding orientation toward GSK-3β. The 50 ns MD simulations run confirmed the stable nature of GSK-3β-lead1 docking complex. The results from RRD, QPLD, IFD and MD simulations confirmed that lead1 might be used as a potent antagonist for GSK-3β.