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Large-scale computational screening of Indian medicinal plants reveals Cassia angustifolia to be a potentially anti-diabetic.
Devaraji, Vinod; Sivaraman, Jayanthi; Prabhu, S.
Affiliation
  • Devaraji V; Computational Drug Design Lab, Department of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
  • Sivaraman J; Computational Drug Design Lab, Department of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
  • Prabhu S; Department of Botany, Annai Vailankanni Arts and Science College, Thanjavur, India.
J Biomol Struct Dyn ; 42(1): 194-210, 2024.
Article in En | MEDLINE | ID: mdl-36961200
ABSTRACT
Researchers are investigating the medicinal properties of herbal plants throughout the world, which often leads to the discovery of novel plants and their chemicals for prophylactic needs of humans. Natural phytochemicals continue to be sought as alternative treatments for various diseases because of their non-toxic and therapeutic properties. In recent years, computational phytochemistry has enabled large-scale screening of phytochemicals, enabling researchers to pursue a wide range of therapeutic research alternatives to traditional ethnopharmacology. We propose to identify an anti-diabetic plant by computational screening on Indian herbal plants in conjunction with experimental characterization and biological validation. The methodology involves the creation of an in-house Indian herbal plant database. Molecular docking is used to screen against alpha amylase for anti-diabetic prophylaxis. Cassia angustifolia was chosen because its phytochemicals are able to bind to alpha amylase. Plants were experimentally extracted, botanically studied and their biological activity was evaluated. Further, the use of molecular dynamics was then applied to pinpoint the phytochemicals responsible for the affinity of alpha amylase. Results in the phytochemical analysis of the extracts revealed strong presence of alkaloids, flavonoids and cardiac glycosides. Moreover, alpha amylase biological activity with C. angustifolia extracts of chloroform, hexane and ethyl acetate demonstrated activity of 3.26, 8.01 and 30.33 µg/ml validating computational predictions. In conclusion, this study developed, validated computational predictions of identifying potential anti-diabetic plants 'Cassia angustifolia' from house herbal databases. Hope this study shall inspire explore plant therapeutic repurposing using computational methods of drug discovery.Communicated by Ramaswamy H. Sarma.
In-house database phytochemicals preparation using Indian medicinal plants for repurposing plant therapeutics screening.Virtual screening of in-house database against alpha amylase for anti-diabetic therapeutics.The highest affinity plants Cassia angustifolia were identified, collected, processed four solvent extracts, along with qualitative and quantitative estimations.All plant extracts are subjected to botanical and biological experimental perspective.Advanced molecular dynamics simulations are used to understand the non-bonding interactions of phytochemicals with alpha amylase.
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Full text: 1 Database: MEDLINE Therapeutic Methods and Therapies TCIM: Terapias_biologicas Main subject: Plants, Medicinal / Senna Plant Type of study: Diagnostic_studies / Prognostic_studies / Qualitative_research / Screening_studies Language: En Journal: J Biomol Struct Dyn Year: 2024 Type: Article Affiliation country: India

Full text: 1 Database: MEDLINE Therapeutic Methods and Therapies TCIM: Terapias_biologicas Main subject: Plants, Medicinal / Senna Plant Type of study: Diagnostic_studies / Prognostic_studies / Qualitative_research / Screening_studies Language: En Journal: J Biomol Struct Dyn Year: 2024 Type: Article Affiliation country: India