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

Author:

Rocha Elaine Cristina Medeiros da123,Rocha João Augusto Pereira da1234ORCID,da Costa Renato Araújo25ORCID,Costa Andreia do Socorro Silva da25,Barbosa Edielson dos Santos2,Josino Luiz Patrick Cordeiro4,Brasil Luciane do Socorro Nunes dos Santos2,Vendrame Laura Fernanda Osmari6,Machado Alencar Kolinski6,Fagan Solange Binotto6ORCID,Brasil Davi do Socorro Barros2ORCID

Affiliation:

1. Laboratory of Modeling and Computational Chemistry, Federal Institute of Education, Science and Technology of Pará (IFPA) Campus Bragança, Bragança 68600-000, PA, Brazil

2. Laboratory of Biosolutions and Bioplastics of the Amazon, Graduate Program in Science and Environment, Institute of Exact and Natural Sciences, Federal University of Pará (UFPA), Belém 66075-110, PA, Brazil

3. Graduate Program in Chemistry, Federal University of Pará (UFPA), Belém 66075-110, PA, Brazil

4. Laboratório de Planejamento e Desenvolvimento de Fármacos, Instituto de Ciências Exatas e Naturais, Universidade Federal do Pará, Belém 66075-110, PA, Brazil

5. Laboratory of Molecular Biology, Evolution and Microbiology, Federal Institute of Education, Science and Technology of Pará (IFPA) Campus Abaetetuba, Abaetetuba 68440-000, PA, Brazil

6. Graduate Program in Nanosciences, Franciscana University, Santa Maria 97010-032, RS, Brazil

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 (Euterpe oleracea 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.

Funder

Fundação Amazônia de Amparo a Estudos

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

MDPI AG

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