Title

Virtual screening of human pancreatic lipase inhibitors using an integrated transfer learning and molecular dynamics simulation

Authors

C. Tamilselvan & B. S. Lakshmi*

Affiliation

Department of Biotechnology, Anna University, Guindy, Chennai, 600025, Tamilnadu, India; *Corresponding author

Email

C. Tamilselvan - E-mail: tamilselvanchandran003@gmail.com
B. S. Lakshmi - E-mail: lakshmibs@annauniv.edu

Article Type

Research Article

Date

Received June 1, 2026; Revised June 30, 2026; Accepted June 30, 2026, Published June 30, 2026

Abstract

Human pancreatic lipase (hPL), a major enzyme involved in dietary lipid digestion is a crucial therapeutic target for the management of obesity. Therefore, it is of interest to identify hPL inhibitors using an integrated transfer learning and molecular dynamics simulation. Transfer learning predicted 17,309 active candidates based on the pIC₅₀, from which prenylated flavanonol was identified as the top-ranked compound with a binding affinity of 9.85 kcal/mol in comparison to reference inhibitor orlistat using Glide XP docking. Moreover, 200ns molecular dynamics simulations confirmed the stability of the protein-ligand complex through sustained interactions with key catalytic residues, including Ser152 and Asp79. Thus, data shows that prenylated flavanonol as a promising natural inhibitor of hPL.

Keywords

Human pancreatic lipase (hPL), Transfer learning, Virtual screening, Prenylated flavanonol, Molecular dynamics simulation, Anti-obesity drug discovery.

Citation

Tamilselvan & Lakshmi, Bioinformation 22(6): 3002-3009 (2026)

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.