In silico evaluation of phytoconstituents from Bertholletia excelsa against inflammatory, oxidative stress, and androgen-dependent molecular targets via molecular docking
Year: 2025
Type: article
Abstract: Bertholletia excelsa (Brazil nut) is a nutritionally and ethnomedicinally valued Amazonian plant, traditionally used for its anti-inflammatory, antioxidant, and androgen-modulating properties. Despite known phytoconstituents with diverse bioactivities, molecular-level insights into their interaction with therapeutic targets remain limited.nThis study aimed to investigate the molecular interactions of selected phytoconstituents from Bertholletia excelsa against key inflammatory, oxidative stress, and androgen-related protein targets using in silico docking and ADME profiling. Ten major phytoconstituents were selected based on literature and screened against Human Androgen Receptor (1E3G), COX-2 (5F19), and IL-1? (4DEP) using Glide docking in Schrödinger Suite. Drug-likeness and ADME properties were predicted via SwissADME. Docking scores, interaction profiles, and pharmacokinetic properties were analyzed. Quercetin, Kaempferol, and Catechin showed the most favorable binding affinities (up to -9.5 kcal/mol) through hydrogen bonding and ?-? stacking interactions with key active site residues in all three targets. These flavonoids fully complied with Lipinski’s rule of five and demonstrated high gastrointestinal absorption. In contrast, sterols and fatty acids exhibited moderate to weak interactions and lower oral bioavailability predictions. The findings highlight Quercetin, Kaempferol, and Catechin as promising natural leads with dual anti-inflammatory and androgen-modulating potential. These in silico results warrant further in vitro and in vivo validation to substantiate their therapeutic applications.
Source: The Pharma Innovation
Authors: Aditya ., Anju Yadav, Sagar ., Uday ., Jitender ., Aniket Hooda, Mohammad Sameer
Institution: Baba Mastnath University
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4412545954
