Identification of Potent Leads for Human cAMP Dependent Protein Kinase Catalytic Subunit Alpha: A Strategic Application of Virtual Screening for Cancer Therapeutics

The advancement in therapeutic applications focused on specific macromolecular compounds of deregulated cell signaling pathways bestowed novel approach to design the ligands as drug molecules against several life threatening diseases such as Cancer. In humans, protein kinase A is one of the important kinases those were involved in cell signaling mechanism. cAMP, G-proteins and ATP molecules were required for activation of protein kinase A (PKA), upon activation, PKA catalytic subunits (PRKACA,PRKACB and PRKACG) undergoes many cellular functions like cell proliferations, cell cycle regulation, and survival of cells through acting on many substrates. Overexpression of extracellular cAMP dependent protein kinase A catalytic subunits (PRKACA) causes severe tumorgenesis in different organs (prostate gland, breast, lungs and pancreas) leading to cancer. High throughput virtual screening was implemented herein to identify the potent leads for human PRKACA that stimulates chronic form of cancers. In silico functional and phylogenetic analysis of PRKACA protein provided enough evidences towards its cancer stimulating nature. The human PRKACA crystal structure in complex with inhibitor ‘796’ (PDB ID: 2GU8) was optimized in Maestro v9.0 and the amino acid residues constituting inhibitor interaction site were determined. Fifteen published inhibitors were selected including HA1077, Flavopiridol, Roscovitine, MLN-518, PP2 and Gleevec which were already in clinical trials for high throughput screening at Ligand.Info database. An in house library of 5388 compounds was designing from the above screening procedure were prepared in LigPrep for molecular docking with human PRKACA. Maestro Glide docking from lesser to higher stringency towards minor steric classes were applied subsequently to the prepared ligand dataset against a grid around centroid of the identified inhibitor interaction site of human PRKACA and 21 lead molecules with good docking scores were obtained. Lead ‘1’ (Leptosidin) with relatively least docking score (-11.02 Kcal/mol) compared to other 20 lead molecules and 15 published inhibitors delineates it as potentially the best competitive inhibitor among all. The promising inhibitory activity of Leptosidin is further supported from analysis of binding orientations of human PRKACA- Leptosidin complex deciphering the Lead 1 blocks the active site residues Thr51, Glu121, Val123, Glu127 and Thr183 by forming hydrogen bond. Thus, Leptosidin could be futuristic perspective chemical compound to design drug molecule against human PRKACA in numerous cancers, however, further in vitro and in vivo studies were required to verify the computational strategic prediction of PKA holoenzyme against cancer therapeutics

Computer aided drug design studies to explore novel antagonist of human myotrophin

Human myotrophin is the smallest ankyrin repeat protein implicated as a factor to induce cardiac hypertrophy. Activation of myotrophin was observed during acute myocardial infarction (MI). In acute coronary syndrome (ACS) patients, myotrophin acts as a self-governing predictor of major adverse cardiac events (MACE). Therefore, human myotrophin serves as an effective drug target for discovery of new potential drugs. Recent human myotropin inhibitors have poor pharmalogical properties leading to intolerable side effects. Hence, ligand based virtual screening protocol of CADD method was persuaded in the present study to propose new class potential myotrophin inhibitors. Docking was done by using Schrödinger software suite 2010 (maestro v9.1), docked complexes were validated and enumerated to find out the best lead, top twenty docked complexes were selected, analyzed through LIGPLOT for their binding orientations. Finally ten top ranked leads were reported based on the XPGscore, better binding affinity and good pharmacological properties compared to existing inhibitors. Lead ‘1’ (Mitoxantrone) showed lowest XPGscore (-8.4k cal/mol) and good van der Waal interaction, hydrophobic interactions with the residues Lys-24, Glu-26, Tyr-21, Arg-30, Cys-2, Asp-3, Lys-4, Phe-6, Glu-5, Ala-9, Glu-70 and Gly-140 responsible for the preference of inhibition. Three hydrogen bonds were observed with myotrophin- lead1 docking complex with residues Asp-3, Cys-2 and Gly-5. Thus, lead1 would be the preferred compound to proceed with in vitro and in vivo verification. Our results illustrate a well-designed virtual screening campaign successfully identifying novel lead compounds as potential entry points for the development of drugs for cardiovascular disease treatment

Prediction of novel inhibitors for human RNase1 involved in cardiovascular disease through in silico screening

Human pancreatic ribonuclease (RNase1) is a small digestive and pyramidine specific enzyme secreted by the pancreas. RNase1 contributes in the regulation of extracellular RNA by hydrolyzing RNA phosphodiester bonds. High levels of RNase1 in cardiovascular disease patients project the enzyme as an attractive drug target. The known RNase1 inhibitors, citric acid and U1S were searched for structural analogs from Ligand.info database to compile 783 ligands. The ligands' 3D structures and their tautomeric states were generated using LigPrep. The 3424 prepared conformations were subjected to QikProp analysis and filtered based on Lipinski rule of five and zero reactive functional group. The 3376 conformations with good ADME (absorption, desorption, metabolism, excretion) profile were passed through multistage docking in virtual screening workflow of Schrodinger software 2011. Seventy five ligands with good binding affinity towards RNase1 were ranked based on XPGscore, through Glide extra precision (XP) docking. Twenty three ligands with better XPGscore compared to published inhibitors (citric acid and U1S) were proposed as potential RNase1 inhibitors. Analysis of docking complexes, their binding orientations, XPGscores and through stringent correlation with published data lead ‘1’ that showed least XPGscore (-12.284 Kcal/mol) was proposed as the best molecule to consider for rational drug designing for treatment of cardiovascular disease

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

<div><p>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 <i>Streptococcus mitis</i> (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.</p></div

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

<div><p><i>Leptospira interrogans</i>, 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 <i>Leptospira</i>. 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 <i>Leptospira</i>. LpxC, a unique enzyme of lipid-A biosynthetic pathway was identified as common drug target of <i>Leptospira</i>. 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.</p><p>An animated Interactive 3D Complement (I3DC) is available in Proteopedia at <a href="http://proteopedia.org/w/Journal:JBSD:10" target="_blank">http://proteopedia.org/w/Journal:JBSD:10</a></p></div