Raghuvir Ramakant Pissurlenkar

Goa College of Pharmacy, Panaji Goa INDIA

Title: Comprehensive computational study in the identification of Novel potential cholesterol lowering agents targeting Proprotein Convertase Subtilisin/Kexin Type 9

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Biography

Raghuvir Pissurlenkar is a Professor at Goa College of Pharmacy, Goa, India. He has a

rich experience of teaching and research in Organic and Medicinal Chemistry. Dr.

Pissurlenkar has his expertise in molecular modeling for drug design using structurebased

and ligand-based methods along with molecular simulations of natural and

synthetic polymers for the estimation of free reneges for binding and solvation. Dr.

Pissurlenkar has graduate from Goa College of Pharmacy under Goa University

affiliation where he has joined as an Associate Professor. He has his Masters and PhD

from Bombay College of Pharmacy, affiliated to the Mumbai University. Dr. Pissurlenkar

has published his research work extensively in peer-reviewed journals with high impact

factor. He’s looking for collaborations for drug design research where he can share his

expertise.

Abstract

The enzymatic target proprotein convertase subtilisin/kexin type 9 (PCSK9) is critically involved in

the regulation of the lipoprotein metabolism leading to the degradation of low-density lipoprotein

receptors (LDLRs) upon binding. Drugs that lower LDL cholesterol (LDL-C) through the inhibition

of PCSK9 are useful in the management of hypercholesterolemia which greatly reduces the associated

risk of atherosclerotic cardiovascular disease (CVD). In 2015, anti-PCSK9 monoclonal antibodies

(mAbs), alirocumab and evolocumab were approved but owing to their high costs their prior

authorization practices were impeded, reducing their long-term adherence. This has drawn

considerable attention for the development of small-molecule PCSK9 inhibitors. In this research

work, novel and diverse molecules with affinity towards PCSK9 thereby having ability to lower

cholesterol. A hierarchical multistep docking was implemented to identify small molecules from

chemical libraries with a score cutoff ?8.00 kcal/mol, thereby weeding all the non-potential

molecules. A set of seven representative molecules have been identified from a comprehensive

computational study which included assessment of pharmacokinetics and toxicity profiles and binding

interactions along with in-depth analysis of structural dynamics and integrity using prolong molecular

dynamics (MD) simulation (in-duplicate). Furthermore the binding affinity of these PCSK9 inhibitory

candidates molecules was ascertained over 1000 trajectory frames using MM-GBSA calculations. The

molecules reported herein are propitious candidates for further development through necessary

experimental considerations