Computational screening of coumarin derivatives as inhibitors of the NACHT domain of NLRP3 inflammasome for the treatment of Alzheimer’s disease

Abstract

The nucleotide-binding oligomerization domain (NOD)-like receptor (NLR), leucine-rich-repeat (LRR), and pyrin domain containing 3 (NLRP3) is one of the key players in neuroinflammation, which is a major pathological hallmark of Alzheimer’s Disease (AD). Activated NLRP3 causes release of pro-inflammatory molecules that aggravate neurodegeneration. Thus, pharmacologically inhibiting the NLRP3 inflammasome has the potential to alleviate the inflammatory injury to the neurons. Coumarin is a multifunctional nucleus with potent anti-inflammatory properties and can be utilized to develop novel drugs for the treatment and management of AD. In the present study, we have explored the NLRP3-inhibitory activities of a library of coumarin derivatives through a computational drug discovery approach. Drug-like, PAINS free, and potentially BBB permeable compounds were screened out and subjected to molecular docking and in silico ADMET studies, resulting in three virtual hits, i.e. MolPort-050-872-358, MolPort-050-884-068, and MolPort-051-135-630. The hits exhibited better NLRP3-binding affinity than MCC950, a selective inhibitor of NLRP3. Further, molecular dynamics (MD) simulations, post-MD simulation analyses, and binding free energy calculations of the hits established their potential as promising virtual leads with a common coumarin scaffold for the inhibition of NLRP3 inflammasome.

Communicated by Ramaswamy H. Sarma

Keywords:

• NLRP3
• inflammasome
• coumarin
• Alzheimer’s disease
• neuroinflammation
• molecular docking
• molecular dynamics simulation
• MCC950
• drug discovery

Acknowledgement

The authors would like to express their gratitude toward Professor David A. Case of the Department of Chemistry & Chemical Biology at Rutgers University, New Jersey, USA, for his generous support in granting a license for Amber 20.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are openly available in figshare at https://doi.org/10.6084/m9.figshare.24486052.v1.

Additional information

Funding

Powsali Ghosh, Ravi Singh, and Chayanika Chatterjee would like to acknowledge the financial support from the Ministry of Education (MoE), New Delhi, India in the form of teaching assistantships.