Flavonoids are known to showcase anti-inflammatory abilities. Hence, it is not a wild guess that they might inhibit NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) inflammasome signaling, implying these chemicals could inspire new drug candidates for this specific pathway. As such, this work aims to identify flavonoids as potential NLRP3 inhibitors, virtually screening 100 known compounds through molecular docking, with subsequent Molecular Dynamics (MD) and MM/PBSA analysis of the two best performing ligands. It was found that Dorsmanin C (DC) and Poinsettifolin A (PA) performed best out of all compounds screened, both satisfying screening criteria determined in docking method validation and predictably binding to key residue Arg578, essential for activity. In MD simulations, PA was observed to be bound steadier to NLRP3 than DC and NP3-146, a known inhibitor, as demonstrated by RMSD, RMSF, Rg and SASA values, although underperforming in H-bonds and ligand stability when compared to NP3-146. MM/PBSA calculations describe lower binding energy for NP3-146 when compared to PA and DC, yet PA still proves superior to DC in terms of target affinity. Therefore, Poinsettifollin A presents as the most promising candidate, highlighting it as a potential lead for development of novel anti-inflammatory drugs.
We have a question for you, you can read and answer bellow.
Question for Authors:
What role could play Machine Learning methods on this area?
REVIEWWWERS'23 participation:
We also invite you to participate in the REVIEWWWERS Workshop, which is now open, by making questions to other authors.
The steps are very easy. instructions: Step(1), Register/Login here [Register/Login] to Sciforum platform. Step(2), Go to presetations list [MOL2NET'23 Papers List], Step(3), Scroll down papers list and click on one title. Step(4), Scroll down and click on Commenting button, post your comment, and click submit. Step(5), Repeat review process for other papers. Step(6), Request certificate. See details [Reviewers Workshop] or contact us at Email: mol2net.chair@gmail.com.