Preprint Communication Version 1 Preserved in Portico This version is not peer-reviewed

Computational Insights into Polydatin: Unraveling Therapeutic Opportunities through Interactions with Rab Proteins

Version 1 : Received: 5 December 2023 / Approved: 6 December 2023 / Online: 6 December 2023 (10:32:50 CET)

How to cite: FERRARI, I.V.; Ravagnan, G. Computational Insights into Polydatin: Unraveling Therapeutic Opportunities through Interactions with Rab Proteins. Preprints 2023, 2023120367. https://doi.org/10.20944/preprints202312.0367.v1 FERRARI, I.V.; Ravagnan, G. Computational Insights into Polydatin: Unraveling Therapeutic Opportunities through Interactions with Rab Proteins. Preprints 2023, 2023120367. https://doi.org/10.20944/preprints202312.0367.v1

Abstract

Molecular docking, a computational method predicting how molecules bind to target proteins, is employed in this study to explore Polydatin's interactions with Ras-related protein Rab (Rab) proteins using the Mcule Database. This database validates the docking results and offers insights into the pharmacological properties of Polydatin. Notably, specific Rab proteins like Rab-5A, HRas, and Rab-18 exhibit robust interactions with Polydatin, indicated by favorable binding energies.These findings illuminate the potential roles of Polydatin in therapeutic and biological contexts, emphasizing its interaction with Rab proteins. The Mcule Database enhances the credibility of the study, providing additional perspectives on Polydatin's applications. The observed interactions, particularly with key proteins like HRas, present a promising avenue for modulating cellular signaling pathways. This modulation holds therapeutic potential, potentially addressing conditions associated with pathway overactivity, including specific cancer types.

Keywords

Rab proteins; Polydatin; Docking analysis; Autodock Vina

Subject

Biology and Life Sciences, Life Sciences

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