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ORIGINAL RESEARCH article

Front. Bioinform.

Sec. Protein Bioinformatics

Volume 5 - 2025 | doi: 10.3389/fbinf.2025.1674791

This article is part of the Research TopicBioinformatics tools and approaches for prediction and assessment of protein allergenicity and toxicity potentialView all articles

Unravelling the Molecular Basis for snake venom NGF - human TrkA recognition through Molecular Dynamics Simulation and comparison with Human NGF

Provisionally accepted
  • School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India

The final, formatted version of the article will be published soon.

Neurodegenerative diseases pose a significant challenge due to the limited effective therapies. Nerve Growth Factor (NGF) plays a crucial role in neuronal survival and differentiation through the TrkAAlthough snake venom NGF (sNGF) have been studied for their ability to activate the TrkA, their binding modes and associated dynamics still remain unclear when compared to hNGF. This study explores the possibilities of NGF from Daboia russelii and Naja naja as potential therapeutic alternatives to hNGF by comparing their structural similarities and conserved binding residues. Active sites were identified using literature review, Molecular docking was performed using HADDOCK, followed by Molecular Dynamics Simulation (MDS) to analyse the stability of the complexes. PRODIGY and mmPBSA was used for binding affinity. sNGFs exhibited stronger binding affinity and stability when compared to hNGF, while PCA and FEL indicated constrained conformational flexibility suggestive of an adaptive mechanism involved in sNGF for effective receptor engagement. Network coevolutionary analysis shows the pattern in which the amino acids are co-evolved and are conserved throughout the simulation. These findings indicate that drNGF and nnNGF are promising therapeutic candidates for neurodegenerative disorders and warrant further in vivo validation.

Keywords: Snake venom, Nerve Growth Factor, TrkA, neurodegenerative disease, simulation

Received: 28 Jul 2025; Accepted: 22 Sep 2025.

Copyright: © 2025 Devi and Gurunathan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Jayaraman Gurunathan, gjayaraman@vit.ac.in

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