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High-Throughput Molecular Modeling and Evaluation of the Anti-Inflammatory Potential of Açaí Constituents against NLRP3 Inflammasome. | LitMetric

AI Article Synopsis

  • The study investigates the anti-inflammatory effects of açaí compounds on the NLRP3 inflammasome using advanced molecular modeling techniques.
  • Findings show that açaí constituents demonstrate significant interactions with the NLRP3 protein and have favorable binding energies, although slightly lower than known inhibitors.
  • In silico toxicology results indicate that açaí compounds are less toxic than synthetic inhibitors, suggesting their potential as safer options for new anti-inflammatory therapies.

Article Abstract

The search for bioactive compounds in natural products holds promise for discovering new pharmacologically active molecules. This study explores the anti-inflammatory potential of açaí ( Mart.) constituents against the NLRP3 inflammasome using high-throughput molecular modeling techniques. Utilizing methods such as molecular docking, molecular dynamics simulation, binding free energy calculations (MM/GBSA), and in silico toxicology, we compared açaí compounds with known NLRP3 inhibitors, MCC950 and NP3-146 (RM5). The docking studies revealed significant interactions between açaí constituents and the NLRP3 protein, while molecular dynamics simulations indicated structural stabilization. MM/GBSA calculations demonstrated favorable binding energies for catechin, apigenin, and epicatechin, although slightly lower than those of MCC950 and RM5. Importantly, in silico toxicology predicted lower toxicity for açaí compounds compared to synthetic inhibitors. These findings suggest that açaí-derived compounds are promising candidates for developing new anti-inflammatory therapies targeting the NLRP3 inflammasome, combining efficacy with a superior safety profile. Future research should include in vitro and in vivo validation to confirm the therapeutic potential and safety of these natural products. This study underscores the value of computational approaches in accelerating natural product-based drug discovery and highlights the pharmacological promise of Amazonian biodiversity.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11311378PMC
http://dx.doi.org/10.3390/ijms25158112DOI Listing

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