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Letters in Drug Design & Discovery


ISSN (Print): 1570-1808
ISSN (Online): 1875-628X

Research Article

Computational Study Reveals PARP1 and P2Y1 Receptors as Prospective Targets of Withaferin-A for Cardiovascular Diseases

Author(s): Rekha Ravindran, Praveen Kumar Posa Krishnamoorthy*, Sriram Kumar, Sujata Roy, Sakthi Abirami Gowthaman and Johanna Rajkumar

Volume 19, Issue 4, 2022

Published on: 21 January, 2022

Page: [323 - 336] Pages: 14

DOI: 10.2174/1570180819666211228103102

Price: $65


Background: Cardiovascular Diseases (CVDs) remain the leading cause of death worldwide, which urges for effective strategies of prevention and treatment. Withaferin-A (WFA), the key metabolite identified in Withania somnifera, has been known for its cardioprotective properties. Although it has been traditionally employed to treat cardiovascular ailments for several decades, its exact mechanism of action still remains unexplained.

Objective: The current study modeled and scored the interactions of WFA with nine prospective protein targets associated with cardiovascular diseases through molecular docking and DSX-scoring.

Methods: Molecular docking was carried out using Autodock and DSX scoring was carried out using DSX standalone software. WFA was observed to favorably interact with six targets before DSX-based rescoring, but only with Poly (ADP-Ribose) Polymerase-1 and P2Y Purinoceptor-1 after DSX-based rescoring. The spatial orientation, physicochemical properties and structural features of Withaferin-A were compared with that of the approved drugs by pharmacophore modeling and hierarchical clustering.

Results: The results of molecular docking, DSX-based rescoring and complete pharmacophore modeling together revealed that PARP1 and P2Y1 receptors could be prospective targets of WFA for the treatment of CVD.

Conclusion: Simulation using GROMACS has revealed that WFA forms a more stable complex with PARP1 and will be useful in developing broad-spectrum drugs against cardiovascular diseases. Further computational studies through machine learning and network pharmacology methods can be carried out to improve the Withaferin-A compound features by incorporating additional functional groups necessary for molecular recognition of the target genes in the network responsible for cardiovascular diseases.

Keywords: Cardiovascular diseases, Withania somnifera, Withaferin-A, molecular docking, DSX scoring, PARP1.

Graphical Abstract
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