Speaker Biography

Gera Narendra

Molecular Modeling Lab, Department of Pharmaceutical Sciences and Drug Research, Punjabi University,Punjab, India

Title: Molecular Docking, Dynamics, and WaterSwap Analysis to Identify Anti aggregating Agents of Insulin and IFN β

Gera Narendra
Biography:

Gera Narendra completed his M. S. (Pharm.) degree in Pharmacoinformatics from the National Institute of Pharmaceutical Sciences and Drug Research (NIPER), Mohali, Punjab, India. He is currently pursuing a Ph.D. in Medicinal Chemistry from the Department of Pharmaceutical Sciences and Drug Research, Punjabi University, Patiala, Punjab, India, under the supervision of Dr. Om Silakari. He is a senior research fellow in the ICMR fellowship project and works, by using in silico techniques, on designing heterocycles for addressing the problem of Drug metabolizing enzymes medicated Anticancer drug resistance.

 

Abstract:

There are several challenges in the development, and formulation of biologics, particularly concerning their physical stabilities. The self-assembly of peptides like human insulin and interferon beta (IFN-β) has potential to form aggregates in pharmaceutical formulation. Therefore, it is a significant problem in the manufacturing, storage, and delivery of insulin and IFN-β formulations. Amino acids as aggregation suppressing additives have been used to stabilize proteins during manufacturing and storage. Several changes to the B chain’s C-terminus have been proposed in an attempt to improve insulin formulation. The core segments of the A and B chains (SLYQLENY and LVEALYLV) have recently been identified as sheet-forming areas, and their microcrystalline structures have been exploited to construct a high-resolution insulin amyloid fibril model. Here, we have chosen twenty-one amino acids to develop as additives in rendering the insulin and IFN-β aggregations. Thereafter, integrated molecular docking studies of single layer monomers of full-length insulin and IFN-β have been performed to identify structural elements (amino acids) that can act as disaggregating agents. The stability of the best-docked amino acid complexes was judged using molecular dynamics studies. Finally, phenylalanine was identified as a disaggregation agent for insulin, and lysine, tyrosine, phenylalanine, and tryptophan were identified as disaggregation agents for IFN-β from the molecular dynamics study. These findings may open a novel proposal to explore further in vitro studies to increase the stability of the insulin and IFN-β formulation.