Manne Munikumar

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

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.

197 Combination of e-pharmacophore modeling, multiple docking strategies and molecular dynamic simulations to discover of novel antagonists of BACE1

196 Antiinflamatory activity of phenolic compounds extracted from Uruguayan propolis and grape Elena Alvareda*, Pablo Miranda, Victoria Espinosa, Helena Pardo, Sara Aguilera and Margot Paulino Zunini Centro de Bioinformática Estructural, DETEMA – Facultad de Química, UdelaR, Montevideo, Uruguay; Facultad de Química, Regional Norte; Centro Nanomat, Polo Tecnológico de Pando – Facultad de Química, UdelaR; Escuela de Medicina, Facultad de Ciencias Médicas – Universidad de Santiago de Chile (USACH); Departamento de Física, Universidad Católica del Norte – Chile *Email: alvareda@fq.edu.uy, Phone: (598) 473-20412 int 105

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.

Docking and Molecular Dynamic Simulations of Legionella pneumophila MurB Reductase for Potential Inhibitor Design

Legionella pneumophila is the causative organism for Legionnaires’ disease, pneumonia and life-threatening prosthetic valve endocarditis. MurB reductase, one of the important enzymes for biosynthesis of peptidoglycan, a component of cell wall, was identified as common drug target against bacterial pathogens causing infective endocarditis including Legionella pneumophila . MurB reductase with FAD acts as a cofactor and catalyzes the NADPH-dependent reduction of UDP-N-acetylenolpyruvylglucosamine (UDP-GlcNAcEP) to UDP-N-acetylmuramic acid. In the present study, 360 structural analogs of FAD were docked to MurB reductase of Legionella pneumophila using sequential protocol of Glide v5.7 implemented in virtual screening workflow of Maestro v9.2. Among seven leads were obtained through docking analysis, only lead1 (XPGscore -13.27Kcal/mol) was observed to have better binding affinity towards MurB reductase as compared to cofactor FAD (XPGscore -13.25Kcal/mol). Molecular level interactions of the MurB reductase- lead1 docking complex showed good correlation with MurB reductase- FAD complex. Further, molecular dynamic simulations for MurB reductase - lead1 docking complex were performed using Desmond v3.0 to shed light on natural dynamic of the docking complex in solution on different timescales. Molecular dynamic simulations of MurB reductase - lead1 complex showed stable nature of the docking interactions.

Identification of Putative Drug Targets and Vaccine Candidates for Pathogens Causing Atherosclerosis

Atherosclerosis is a chronic inflammatory artery disease, responsible for both cardiovascular (heart) and cerebrovascular (brain) stroke with high morbidity and mortality worldwide. Infectious pathogens such as Chlamydophila pneumoniae, Porphyromonas gingivalis and Helicobacter pylori are shown to be associated with the disease in recent epidemiological studies. Therefore, identification of common drug targets and vaccine candidates against these three pathogens would be vital towards therapy and management of atherosclerosis. Chlamydophila pneumonia was selected as a reference organism due to its predominant role in atherosclerosis. Implementing comparative genomic approach, subtractive genomic approach, metabolic pathway analysis, non-homologous gut flora analysis and domain search analysis, 35 common putative drug targets were identified against pathogens of atherosclerosis. Subcellular localization studies were performed and identified UvrABC protein as vaccine candidate. Metabolic pathway analysis has showed that, out of 35 drug targets, 14 enzymes were participating in key pathways linked to pathogen’s survival, proliferation and pathogenesis without any alternative mechanism to synthesize the product. The gut microbiota analysis was performed to identify the drug targets which do not affect the microbiota in the humans. Domain search was performed for the identified 14 drug targets using Pfam and SMART databases and protein network analysis was carried out using STRING and Cytoscape v3.2.0. The drug targets and vaccine candidates proposed in the present study would serve as basis to design potent inhibitors and subunit vaccines through in silico approach for combating atherosclerosis caused by infectious pathogens.

177 T-cell vaccine design for Streptococcus pneumoniae: an in silico approach

Streptococcus pneumoniae (pneumococcus) remains an important cause of meningitis, bacteremia, acute otitis media, community acquired pneumonia associated with significant morbidity, and mortality world wide. Conjugated polysaccharide, glycoconjugated, and capsular polysaccharide based vaccines were existent for pneumococcal disease but are still specific and restricted to serotypes of S. pneumoniae. Proteome of eight serotypes of S. pneumoniae was retrieved and identified in common proteins (Munikumar et al., 2012). 18 membrane proteins were distinguished from 1657 common proteins of eight serotypes of S. pneumoniae. Implementing comparative genomic approach and subtractive genomic approach, three membrane proteins were predicted as essential for bacterial survival and non-homologous to human (Munikumar et al., 2012; Umamaheswari et al., 2011). ProPred server was used to propose four promiscuous T-cell epitopes from three membrane proteins and validated through published positive control, SYFPEITHI and immune epitope database (Munikumar et al., in press). The four epitopes docked into peptide binding region of predominant HLA-DRB alleles with good binding affinity in Maestro v9.2. The T-cell epitope 89-VVYLLPILI-97 and HLA-DRB5∗0101 docking complex was with best XPG score (−13.143 kcal/mol). Further, the stability of the complex was checked through molecular dynamics simulations in Desmond v3.3. The simulation results had revealed that the complex was stable throughout 5000 ps (Munikumar et al., in press). Thus, the epitope would be the ideal candidate for T-cell driven subunit vaccine design against selected serotypes of S. pneumoniae.

161 Discovery of potent KdsA inhibitors of Leptospira interrogans through homology modeling, docking, and molecular dynamics simulations

Leptospira interrogans is the foremost cause of human leptospirosis. Discovery of novel lead molecules for common drug targets of more than 250 Leptospira serovars is of significant research interest. Lipopolysaccharide (LPS) layer prevent entry of hydrophobic agents into the cell and protect structural integrity of the bacterium. KDO-8-phosphate synthase (KdsA) catalyzes the first step of KDO biosynthesis that leads to formation of inner core of LPS. KdsA was identified as a potential drug target against Leptospira interrogans through subtractive genomic approach, metabolic pathway analysis, and comparative analysis (Amineni et al., 2010). The present study rationalizes a systematic implementation of homology modeling, docking, and molecular dynamics simulations to discover potent KdsA inhibitors (Pradhan et al., 2013; Umamaheswari et al., 2010). A reliable tertiary structure of KdsA in complex with substrate PEP was constructed based on co-crystal structure of Aquifex aeolicus KdsA synthase with PEP using Modeller9v10. Geometry-based analog search for PEP was performed from LigandInfo database to generate an in house library of 352 ligands. The ligand data-set was docked into KdsA active site through three-stage docking technique (HTVS, SP, and XP) using Glidev5.7. Thirteen lead molecules were found to have better binding affinity compared to PEP (XP Gscore = −7.38 kcal/mol; Figure 1). The best lead molecule (KdsA- lead1 docking complex) showed XP Gscore of −10.26 kcal/mol and the binding interactions (Figure 2) were correlated favorably with PEP–KdsA interactions (Figure 1). Molecular dynamics simulations of KdsA– lead1 docking complex for 10 ns had revealed that the complex (Figure 3) remained stable in closer to physiological environmental condition. The predicted pharmacological properties of lead1 were well within the range of a drug molecule with good ADME profile, hence, would be intriguing towards development of potent inhibitor molecule against KdsA of Leptospira.

176 Structure-based virtual screening towards identification of potential FabH inhibitors

Infective endocarditis (IE) is a serious form of microbial infection of the endocardial surface, lining of the heart chambers and heart valves with a high mortality rate. Through comparative genomics, subtractive genomics, and metabolic pathway analysis, 18 common drug targets were identified (Priyadarshini et al., 2013). In the present study, β-Ketoacyl-acyl carrier protein synthase III (FabH), a common protein among eight selected pathogens of IE, was selected for the study. FabH catalyzes the initiation of fatty acid elongation by condensing malonyl-ACP with acetyl-CoA. FabH is an essential enzyme for bacterial viability, because of its pivotal roles in both initiation and regulation of the fatty acid biosynthesis. Experimentally determined tertiary structure of FabH of Streptococcus mitis (reference organism) was not reported yet. Therefore, molecular modeling of FabH in complex with 2-({[4-bromo-3-(diethylsulfamoyl) phenyl] carbonyl} amino) benzoic acid (B82) was constructed using Modeller9v10 (Figure 1). An in-house library consisting of 23969 structural analogs from 60 available FabH inhibitors was compiled from Ligand.Info database. Structure-based virtual screening was performed through three-stage docking technique (HTVS, SP, and XP) using Glide v5.7 led to identification of seven lead molecules with better binding affinity compared to published inhibitor (XP Gscore −8.268 kcal/mol). Lead1 showed the lowest XP Gscore of −9.953 kcal/mol with strong binding interactions with FabH. Molecular dynamic (MD) simulations (Priyadarshini et al., 2011) for FabH–lead1 docking complex were performed using Desmond v3.0 for 10 ns. It revealed that the complex (Figure 1) remained structurally and energetically stable in all 2084 trajectories. The docking interactions were also reproduced during MD simulations. Therefore, lead1 would be a potent inhibitor of FabH and ideal for designing drug for IE.