Research Seminar by Sagar Bhayye | Shiv Nadar University
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Research Seminar by Sagar Bhayye

Research Seminar by Mr. Sagar Bhayye, Centre for Informatics.

Seminar Title: Design and Optimization of Some Protein Modulators as Anti-Parkinson’s Agents using Advanced Cheminformatics Techniques.

Event Date: 
Monday, June 24, 2019 -

Design and Optimization of Some Protein Modulators as Anti-Parkinson’s Agents using Advanced Cheminformatics Techniques
Sagar S. Bhayyea, Kunal Royb & Achintya Sahaa
aDepartment of Chemical Technology, University of Calcutta, Kolkata, West Bengal – 700 009
bDepartment of Pharmaceutical Technology, Jadavpur University, Kolkata, West Bengal – 700 032
Abstract -
Parkinson’s disease is an age-related multi-factorial neurodegenerative disorder, described by protein aggregation, oxidative stress, genetic and mitochondrial abnormalities, and neuro-inflammatory processes. The root cause of PD is still unclear, while various theories, such as, α–synuclein deposition, depletion of dopamine producing neurons, overexpression of MAO-B, environmental condition, missense mutations in enzymes, oxidative stress etc. have been proposed. A variety of chemometrics methods have evolved in CADD that have two major application areas, i.e., ligand-based drug design (LBDD) and structured-based drug design (SBDD). Thus, in this work, both LBDD and SBDD techniques utilized. Several chemometric techniques, such as QSAR, pharmacophore modeling, molecular docking and dynamics, virtual screening etc. have been employed for the purpose. Extensive molecular dynamics simulation has been performed on in-house developed homology model of LRRK2-kinase domain to study the effect of pathogenic mutations on dynamic behavior of active conformation (DYG-In) in presence and absence of ATP at the active site. Study explained that mutated residues in activation loop start interacting with nearby residues through H-bonding due to polar side chain which replaces hydrophobic/aliphatic side chain containing original residues. Ligand-based pharmacophore model has been developed with a set of heterocyclic derivatives of LRRK2-kinase inhibitor and appropriately validated. The model explored the essential structural requirements of LRRK2-kinase inhibitors for activity and designed novel inhibitors through de novo design. Binding affinity of the designed molecules is predicted through pharmacophore model, and docking study has shown good binding affinity. Structure-based pharmacophore models have been developed and validated with decoy set, and explored different chemical databases to identify potential inhibitors. Molecular dynamics and MM-GBSA have ascertained the novel hits. A series of dual AA2A antagonist and MAO-B inhibitor have been utilized in different chemometric techniques to understand the structural features required for essential binding affinity against AA2A as well as inhibition of MAO-B affinity. Virtual screening has been performed on chemical databases for identifying dual inhibitors, and molecular docking analysis provided the insight of binding site of AA2A and MAO-B. A set of indolinone-diene derivatives, having binding affinity against α-synuclein, β-amyloid and tau protein, has been used to build QSAR and QAAR models, and appropriately validated. The QSAR model explores structural requirements for improving binding affinity of biomarkers, while QAAR model facilitates better understanding of features required for selectivity of α-synuclein biomarkers over β-amyloid and tau.

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Monday 24, Jun 2019
02:30 PM - 03:30 PM