ArticleFrontiers in bioinformatics2025
Unraveling the molecular basis of snake venom nerve growth factor: human TrkA recognition through molecular dynamics simulation and comparison with human nerve growth factor.
Article in Frontiers in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- A comparison of honeybee and scorpion venoms as anticancer agents against three different cancer cell lines: lung, colon, and breast cancer.Frontiers in toxicology · 2026Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Neurodegenerative diseases pose significant challenges owing to the limited number of effective therapies. Nerve growth factor (NGF) plays a crucial role in neuronal survival and differentiation through tropomyosin receptor kinase A (TrkA). Although snake venom NGF (sNGF) has been studied for its ability to activate TrkA, the binding modes and associated dynamics remain unclear compared to those of human NGF (hNGF). Herein, we explored the possibilities of NGFs from Methods: The active sites were identified through a literature review, molecular docking was performed using HADDOCK, and molecular dynamics simulation was performed to analyse the stabilities of the complexes; then, PRODIGY and molecular mechanics Poisson-Boltzmann surface area were used to determine the binding affinities. Results: The different sNGFs exhibited stronger binding affinities and stabilities than hNGF, while principal component analysis and the free energy landscape indicated constrained conformational flexibilities suggestive of an adaptive mechanism in sNGF for effective receptor engagement. A network coevolutionary analysis was performed, which showed the pattern in which the amino acids were coevolved and conserved throughout the simulations. Discussion: These findings indicate that NGFs from
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