In silico trials to design potent inhibitors against matrilysin (MMP-7).

The study deals with structure-based rational drug design against the chief zinc-rely endopeptidase called matrilysin (MMP-7) that is involved in inflammatory and metastasis process of several carcinomas. Hyperactivated matrilysin of human was targeted, because of its hydrolytic actions on extracellular matrix (ECM) protein components constitutes fibrillar collagens, gelatins, fibronectins and it also activates zymogen forms of vital matrix metalloproteinases (gelatinase A-MMP-2 and B-MMP-9) responsible for ECM destruction in many cancers. In the present work, e-pharmacophores were generated for the respective five co-crystal structures of human matrilysin by mapping ligand's pharmacophoric features. During the lead-optimization campaign, the five e-pharmacophores-based shape screening against an in-house library of >21 million compounds created a dataset of 5000 structural analogs. The subsequent three different docking strategies, including rigid-receptor docking, quantum-polarized-ligand docking, induced-fit docking and free energy binding calculations resulted four leads as novel and potent MMP-7 binders. These four leads were observed with good pharmacological features and good receiver operating characteristics curve metrics (ROC: 0.93) in post-docking evaluations against five existing co-crystal inhibitors and 1000 decoy molecules with MMP-7. Moreover, stability and dynamics behavior of matrilysin-lead1 complex and matrilysin-cocrystal ligand (TQJ) complex were analyzed in natural physiological milieu of 1000 ns or 1 µs molecular dynamics simulations. Lead1-MMP-7 complex was found with an average Cα root-mean-square deviation (RMSD) of 2.35 Å, average ligand root-mean-square fluctuations (RMSF) of 0.66 Å and the strong metallic interactions with E220, a key residue for proteolytic action thereby hinders ECM proteolysis that in turn can halt metastatic cancerous condition.Communicated by Ramaswamy H. Sarma.

In silico exploration of lignin peroxidase for unraveling the degradation mechanism employing lignin model compounds.

Lignin peroxidase is a heme-containing biocatalyst, well-known for its diverse applications in the fields from environmental chemistry to biotechnology. LiP-mediated oxidative catalysis is H2O2-dependent, and can oxidize phenolic, and non-phenolic substrates by oxidative cleavage of the C-C and C-O bonds of lignin. In contrast to fungi-derived LiP, the binding affinity of bacterial-derived LiP to lignin at the molecular level is poorly known to date. Tremendous wet-lab studies have been unveiled that provide degradation and biotransformation information on kraft lignin, whilst studies on the completely transformed compounds and the degradation of each transformed compounds simultaneously during degradation are scarce. To gain an understanding of the degradation process using docking, and MDS based studies, we assessed the binding affinity of selected lignin model compounds with bacterial origin LiP and validated such docked complexes exploiting 30 ns molecular dynamics simulations. We selected and picked a total of 12 lignin model compounds for molecular modeling analysis, namely two chlorinated lignin model compounds (monomer) (2-chlorosyringaldehyde and 5-chlorovanillin), eight standard lignin model compounds (veratryl alcohol, syringyl alcohol, sinapyl alcohol, methyl hydroquinone, guaiacol, coniferyl alcohol, catechol, and 4-methoxy phenol), while, two 4-O-5, and ß-O-4 linkage-based multimeric model compounds (dimer: 2-methoxy-6-(2-methoxy-4-methylphenoxy)-4-methylphenol; trimer: syringyl ß-O-4 syringyl ß-O-4 sinapyl alcohol). Far more specific binding residues were observed from XP-Glide docking, as TYR, HIP (protonated histidine), PHE, VAL, ASP, THR, LYS and GLN. The binding affinity was confirmed by the Gibbs free energy or binding energy (ΔG) score; furthermore, it is found that the maximum binding energy seems to be observed for 4-methoxyphenol with a Glide score of -3.438 with Pi-Pi stacking and H-bond type bonding interactions, whilst the lowest XP Gscore as -8.136 with Pi-Pi stacking and H-bond (side chain) type bonding interactions were found for the trimer model compound. The docked complexes were further evaluated for deep rigorous structural and functional fluctuation analyses through high-performance molecular dynamics simulations-DESMOND, after a post simulation run of 30 ns. The RMSD trajectory analyses of the protein-ligands were found to be in the equilibrium state at the end of simulation run for multimeric lignin model compounds. In addition, ionic ligand-protein interaction occurs among chlorinated compounds, while hydrophobic and H-bond contacts have frequently been observed in all lignin-model compounds. The findings herein demonstrate that bacterial LiP can effectively catalyze multiple lignin model compounds, and it might further be used as an effective tool for sustainable mitigation of diverse environmental contaminants.

Design, synthesis, anti-tobacco mosaic viral and molecule docking simulations of urea/thiourea derivatives of 2-(piperazine-1-yl)-pyrimidine and 1-(4-Fluoro/4-Chloro phenyl)-piperazine and 1-(4-Chloro phenyl)-piperazine - A study.

The objectives of the present work are to design, syhthesize and introduce novel urea/thiourea derivatives of 2-(piperazine-1-yl)-pyrimidine and 1-(4-Fluoro/4-Chloro phenyl)-piperazine molecules as tobacco mosaic virus (TMV) inhibitors. A series of urea/thiourea derivatives containing pyrimidine and piperazine moieties were synthesized, characterized using Fourier-transform infrared (FTIR) mass spectra, nuclear magnetic resonance (NMR) spectroscopy, elemental analysis and evaluated their sustainability using biological experiments. The anti-viral bioassay of the title compounds showed an antiviral activity against TMV. The compounds synthesized, 9j, 6g and 3d, showed highly-potential curative, protective, and inhibitory activities against TMV at 500 mg/mL formulation. All these compounds were allowed to quantum-polarized-ligand (quantum mechanical and molecular mechanical (QM/MM)) docking experiments. The compounds 9j, 6g and 3d structurally exhibited identical higher affinity towards TMV-Helicase and TMV-Coat proteins. The docking interactions proposed had two stage inhibition of TMV virus by binding to coat protein and helicase for inhibition of RNA replication. The long-range molecular dynamics (150 ns) simulations has revealed more consistency by 9j, 6g and 3d. The present study outcomes good binding propensity for active-tunnel of TMV-Hel enzyme, by these thiourea, urea derivatives, 9j, 6g and 3d, to suggest that the designed and synthesized were ideal for proposing as selective novel inhibitors to target for TMV.

Synthesis, Molecular Docking Studies and Biological Evaluation of N-Acylarylhydrazones as Anti-Inflammatory Agents.

In the present work a series of N'-arylidene-2-(benzamido)-3-(naphthalen-2-yl)acrylohydrazides were synthesized by refluxing the intermediate 2-(benzamido)-3-(naphthalen-2-yl)acrylohydrazide with various substituted benzaldehyde in the presence of glacial acetic acid. The intermediate 2-(benzamido)-3-(naphthalen-2-yl)acrylohydrazide 2 was prepared by stirring 4-((naphthalen-2-yl)methylene)-2-phenyloxazol-5(4H)-one with hydrazine hydrate in the presence of absolute ethanol. The chemical structures of the compounds were established by IR, 1H NMR and mass spectral data. All the compounds were evaluated for anti-inflammatory (in vivo, in vitro) activity and performed docking against COX-2. The compounds 3a, 3c and 3o showed good inhibition of COX-2 in in vitro studies (0.75 µM, 0.5 µM and 0.7 µM as IC50, respectively). The compounds 3c, 3e and 3f were found to be more active than standard drug phenylbutazone at equidose. Molecular docking studies showed that compound 3 m exhibited good binding affinity against COX-2 with docking score 9.328 kcal/mol, when compared to the standard celecoxib.

An in silico approach towards identification of novel drug targets in pathogenic species of Leptospira.

Leptospirosis is one of the leading zoonotic infections worldwide. As with other infectious diseases, report of antimicrobial resistance to existing therapeutic arsenal poses challenges in the management of disease. Hence, identification of novel drug targets for the pathogen deems essential. Present study used combined approach of comparative and subtractive genomics to identify putative drug targets. Crucial genes of 16 pathogenic Leptospira strains were filtered and subjected to homology search via target identification tool "TiD". Thereafter, comparative analysis was performed for non-homologous, essential genes to accomplish the broad-spectrum drug target. Consequently, 37 essential genes were found to be conserved in at least 10 strains of Leptospira. Further, prioritization of resultant set of genes revealed 18 were hubs in protein-protein interaction network. Sixteen putative targets among the hub genes were conserved in all strains of Leptospira. Out of sixteen, fourteen were enzymes while 8 were novel and 4 were involved in virulence mechanism. In addition, genome scale metabolic network reconstruction and choke point analysis revealed cobA (porphyrin and chlorophyll metabolism) and thiL (thiamine metabolism) as chokepoints in their respective metabolic pathways. The proposed hub genes could act as putative broad-spectrum drug targets for Leptospira species, however, these putative targets should be validated to ensure them as real one prior to utilizing them for target based lead discovery.

In silico Prediction, Characterization, Molecular Docking, and Dynamic Studies on Fungal SDRs as Novel Targets for Searching Potential Fungicides Against Fusarium Wilt in Tomato.

Vascular wilt of tomato caused by Fusarium oxysporum f.sp. lycopersici (FOL) is one of the most devastating diseases, that delimits the tomato production worldwide. Fungal short-chain dehydrogenases/reductases (SDRs) are NADP(H) dependent oxidoreductases, having shared motifs and common functional mechanism, have been demonstrated as biochemical targets for commercial fungicides. The 1,3,6,8 tetra hydroxynaphthalene reductase (T4HNR) protein, a member of SDRs family, catalyzes the naphthol reduction reaction in fungal melanin biosynthesis. We retrieved an orthologous member of T4HNR, (complexed with NADP(H) and pyroquilon from Magnaporthe grisea) in the FOL (namely; FOXG_04696) based on homology search, percent identity and sequence similarity (93% query cover; 49% identity). The hypothetical protein FOXG_04696 (T4HNR like) had conserved T-G-X-X-X-G-X-G motif (cofactor binding site) at N-terminus, similar to M. grisea (1JA9) and Y-X-X-X-K motif, as a part of the active site, bearing homologies with two fungal keto reductases T4HNR (M. grisea) and 17-ß-hydroxysteroid dehydrogenase from Curvularia lunata (teleomorph: Cochliobolus lunatus PDB ID: 3IS3). The catalytic tetrad of T4HNR was replaced with ASN115, SER141, TYR154, and LYS158 in the FOXG_04696. The structural alignment and superposition of FOXG_04696 over the template proteins (3IS3 and 1JA9) revealed minimum RMSD deviations of the C alpha atomic coordinates, and therefore, had structural conservation. The best protein model (FOXG_04696) was docked with 37 fungicides, to evaluate their binding affinities. The Glide XP and YASARA docked complexes showed discrepancies in results, for scoring and ranking the binding affinities of fungicides. The docked complexes were further refined and rescored from their docked poses through 50 ns long MD simulations, and binding free energies (ΔGbind) calculations, using MM/GBSA analysis, revealed Oxathiapiprolin and Famoxadone as better fungicides among the selected one. However, Famoxadone had better interaction of the docked residues, with best protein ligand contacts, minimum RMSD (high accuracy of the docking pose) and RMSF (structural integrity and conformational flexibility of docking) at the specified docking site. The Famoxadone was found to be acceptable based on in silico toxicity and in vitro growth inhibition assessment. We conclude that the FOXG_04696, could be employed as a novel candidate protein, for structure-based design, and screening of target fungicides against the FOL pathogen.

An in silico study: Novel targets for potential drug and vaccine design against drug resistant H. pylori.

Gastric cancer risk and adverse ramifications by augmented multi-drug resistance (MDR) of Helicobacter pylori are alarming serious health concern. Combating through available drugs is a difficult task due to lack of appropriate common targets against genetically diverse strains. To improve efficacy, the effective targets should be identified and critically assessed. In the present study, we aim to predict the potential novel targets against H. pylori strains by employing computer aided approach. The genomic dataset of 53 H. pylori strains was comparatively processed and eventually predicted 826 'conserved gene products'. Further, we performed subtractive genomic approach in search of promising crucial targets through the combination of in silico analyses. Codon adaptation index (CAI) value calculation and literature surveys were also done in order to find highly expressed gene products with novelty. Consequently, four enzymes and three membrane proteins were prioritized as new therapeutic and vaccine targets respectively which found to have more interactors in network with high-confidence score, druggability, antigenicity and molecular weight <110 kDa. Therefore, our results underpin the importance of new targets may counteract with false-positive/negatives and facilitate appropriate potential targets for a new insight of reliable therapeutic development.

Inhibitor design against JNK1 through e-pharmacophore modeling docking and molecular dynamics simulations.

c-Jun-NH2 terminal kinases (JNKs) come under a class of serine/threonine protein kinases and are encoded by three genes, namely JNK1, JNK2 and JNK3. Human JNK1 is a cytosolic kinase belonging to mitogen-activated protein kinase (MAPK) family, which plays a major role in intracrinal signal transduction cascade mechanism. Overexpressed human JNK1, a key kinase interacts with other kinases involved in the etiology of many cancers, such as skin cancer, liver cancer, breast cancer, brain tumors, leukemia, multiple myeloma and lymphoma. Thus, to unveil a novel human JNK1 antagonist, receptor-based pharmacophore modeling was performed with the available eighteen cocrystal structures of JNK1 in the protein data bank. Eighteen e-pharmacophores were generated from the 18 cocrystal structures. Four common e-pharmacophores were developed from the 18 e-pharmacophores, which were used as three-dimensional (3D) query for shape-based similarity screening against more than one million small molecules to generate a JNK1 ligand library. Rigid receptor docking (RRD) performed using GLIDE v6.3 for the 1683 compounds from in-house library and 18 cocrystal ligands with human JNK1 from lower stringency to higher stringency revealed 17 leads. Further to derive the best leads, dock complexes obtained from RRD were studied further with quantum-polarized ligand docking (QPLD), induced fit docking (IFD) and molecular mechanics/generalized Born surface area (MM-GBSA). Four leads have showed lesser binding free energy and better binding affinity towards JNK1 compared to 18 cocrystal ligands. Additionally, JNK1-lead1 complex interaction stability was reasserted using 50 ns MD simulations run and also compared with the best resolute cocrystal structure using Desmond v3.8. Thus, the results obtained from RRD, QPLD, IFD and MD simulations indicated that lead1 might be used as a potent antagonist toward human JNK1 in cancer therapeutics.

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.

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.

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.

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.

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.

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.