Vani Priyadarshini

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

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.

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.

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.

181 Discovery of potential inhibitors of BMX non-receptor tyrosine kinase through e-pharmacophore based virtual screening.

Cellular functioning depends on proper coordination between proteins, and much of this communication is mediated by so-called peptide-protein interactions in which a short linear motif is bound by a corresponding peptide-binding domain. These interactions provide major challenges both to experiment as well as modeling due to their often weak, transient character, but our ability to study them is critical for improved understanding, and precise modulation, of cellular regulation. A major focus of our research lies in the development and application of protocols for the accurate modeling of peptide-protein interactions. Rosetta FlexPepDock takes as input a receptor structure and an approximate starting structure of the peptide, and refines this structure to near-native resolution using a Monte-Carlo sampling approach coupled with minimization that starts with an attraction–dominated energy function and gradually increases repulsion to generate well-packed, clash-free models (Raveh et al., 2010, 2011; London et al., 2011a). These models can then be used to rank different peptide sequences for their ability to bind to a given receptor (London et al., 2011b). In my talk I will describe recent new developments and applications of peptide-protein modeling, including initial and advanced steps towards the full ab initio modeling of peptide-protein interactions in which no prior information about the peptide-binding site is available. Most exciting, for peptides with characterized binding motifs, we show that a motif-based search for fragments in solved structures and their subsequent docking allows us to identify an acceptable model of interaction, which can then be further refined using e.g. FlexPepDock. We anticipate that this novel approach and implementation will significantly extend the number of peptide-mediated interactions that can be accurately modeled, and thus characterized and manipulated.

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.

Para-(benzoyl)-phenylalanine as a potential inhibitor against leptospirosis

Leptospirosis is a zoonotic disease of global concern caused by Leptospira interrogans. Subtractive genomic approach, metabolic pathway analysis and multi strain genome comparisons of Leptospira interrogans serovars had proposed 88 common drug targets from 5,124 genes of serovar Copenhageni and 4,727 genes of serovar Lai. Three potential drug targets (lpxC, lpxD and lpxB) were identified from Lipid A biosynthesis process of lipopolysaccharide (LPS) biosynthesis pathway. Lipid A is one of the three components of LPS that contains multiple hydrophobic fatty acid chains which anchor the LPS into the bacterial membrane. Designing inhibitory drug molecules targeting Lipid A biosynthesis would dissolve the structural integrity of membrane structure leading to cell lysis and death of Leptospira. LpxC being the first enzyme among the three drug targets of Lipid A biosynthesis pathway; blocking the enzyme with suitable inhibitor would stop synthesizing substrates for lpxD and lpxB. Also, there is no alternative mechanism in Leptospira to replace the catalytic activity rendered by lpxC; hence, the drug target was selected herein for rational drug design. The lpxC tertiary structure was modeled incorporating inhibitor BB-78485 using Modeller9v8. The lpxC 3D structure reliability was assessed through various model validation techniques. Ligand based virtual screening was performed from one million entries of ligand.Info metadatabase. The leads were ranked using computational docking technique of Glidev5.5. Twelve leads with better binding affinity than BB-78485 (XPGscore -7.98 Kcal/mol) were proposed as potential inhibitors of lpxC. Para-(benzoyl)-phenylalanine, the best ranked inhibitor (XPGscore -10.34Kcal/mol), would be intriguing for rational drug design against leptospirosis.