Kanipakam Hema

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

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.

E-Pharmacophore Model Assisted Discovery of Novel Antagonists ofnNOS

The nitric oxide (NO) synthesized by neuronal nitric oxide synthase (nNOS) acts as a neurotransmitter and plays a crucial role in a series of neurobiological functions. In diseased condition, activated nNOS induces nitrosylation as well as phosphorylation of tau protein and glycogen synthase kinase 3 beta (GSK-3β) respectively. Hyper phosphorylation of tau accelerates tau oligomerization resulting in formation of neurofibrillary tangles (NFT), ensuring the neuronal cell death in hippocampus region; a hallmark of Alzheimer’s disease (AD). Thus, designing inhibitor towards nNOS may reduce the neuronal loss caused by nNOS. Hence nNOS has been one of the revitalizing targets for AD. In the present work, one energetically optimized structure-based pharmacophore (e-pharmacophore) was generated using nNOS co-crystal structure (4D1N) to map important pharmacophoric features of nNOS. Shape based similarity screening performed using e-pharmacophore against in-house library of more than one million compounds resulted 2701 library of compounds. Rigid receptor docking (RRD) was applied and followed by molecular mechanics and generalized Born and surface area (MM-GBSA) calculation which results 22 nNOS ligands. To define the leads, dock complexes were subjected to quantum-polarized ligand docking (QPLD) followed by free energy calculations revealed 3 leads. On comparison with 1 existing inhibitor,it concealed three best leads with lower binding energy and better binding affinity. The best lead was subjected to induced fit docking (IFD) with MM-GBSA calculation and further molecular dynamics (MD) simulations for 50 ns in solvated model system. Potential energy, root mean square deviation (RMSD) and root mean square fluctuations (RMSF) results disclosed constancy of lead 1 interactions throughout 50 ns MD simulations run. Thus proposed three leads are having favorable absorption distribution metabolism excretion toxicity (ADME/T) properties and provide a scaffold for designing nNOS antagonists.

E-Pharmacophore Based Virtual Screening to Identify Agonist for PKA-Cñ

Owing to PKA-Cα unique functions in regulating tau splicing alternatively in neurons results in aggregation of tau which contributes to neurofibrillary tangles and taupathies generation a hallmark of Alzheimer’s disease (AD). PKACα also inhibits GSK3β thus it has been a therapeutic target for AD intervention. In this study, e-pharmacophore and multiple docking strategies were followed to propose a novel PKA-Cα agonists. Nine e-pharmacophores were developed from nine co-crystal structures such that all the critical pharmacophoric features involved in their bioactivity of PKA-Cα were effectively mapped. Rigid receptor docking (RRD) was performed with the library of PKA-Cα activators having 3512 shape screened compounds towards PKA-Cα. To derive the best leads, dock complexes were further subjected to QPLD, IFD and MM-GBSA calculations. PKA-Cα-lead1 dock complex was subjected to 50 ns MD simulations run. Comparative analysis between obtained 25 leads and 9 co-crystal ligands revealed three the best leads. Among the three, lead1 has the least docking score with lowest binding free energy with better binding orientation towards PKA-Cα. The constancy of PKA-Cα-lead1 interactions was revealed by 50 ns MD simulations run. Thus ADME predictions and results from RRD, QPLD, IFD and MD simulations affirmed that the proposed three leads might be used as a potent agonists for PKA-Cα.

Identification of Effectual Inhibitors against Human Insulin like Growth Factor Binding Protein-2.

Human Insulin-like Growth Factor Binding Protein-2 (IGFBP 2) is reported to be a modulator of the action of Insulin-like Growth Factors (IGFs), over expression of IGFBP 2 has been reported in cancers. Hence with an aim to design an inhibitor for selected drug target high-throughput virtual screening was implemented. The tertiary structure was retrieved from the protein databank. A 2D similarity search was performed using Ligand. Info for known inhibitor to acquire 778 structural analogs. The 3D structural conversion and multiple confirmations were generated using LigPrep. The docking and scoring calculations were performed using Glide v5.7. Five leads having better docking score compared to heparin were selected as potential IGFBP 2 inhibitors. Among them lead 1 with the highest docking score of -6.009 kcal/mol was proposed as a promising antagonist for IGFBP 2. Molecular dynamics simulations were performed using Desmond v3.6 to check the stability of docking complex.

202 Subunit vaccine design against pathogens causing atherosclerosis

docking (HTVS, SP and XP) with the 4QTA in Glide v6.5. The best docked ten leads were further applied for QPLD, IFD and MM-GBSA analysis (Du et al., 2011). Lead 1 and 2 (Figure 2) exhibited better XPGscore (−9.59 k.cal/mol; −9.06 k.cal/mol) and binding interactions than the 20 crystal ligands. The best two leads were proposed and applied to the molecular dynamics simulations. Docking, molecular dynamics simulations and ADME property predictions showed higher potency of the leads which would be exciting towards the development of potent inhibitor towards the ERK.

201 Structure guided novel lead molecules against ERK proteins: application of multiple docking and molecular dynamics studies.

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