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Year : 2021, Volume : 14, Issue : 1
First page : ( 146) Last page : ( 152)
Print ISSN : 0974-3618. Online ISSN : 0974-360X.
Article DOI : 10.5958/0974-360X.2021.00026.3

ADME and Inhibitory target molecules predicition of Cyamopsis tetragonoloba

Peter Jerine S, Panchal Nagesh Kishan, Nair Aishwaria V, Joshi Kshitija, Sosa Andrews Shobhy, Sabina Evan Prince*

Department of Biomedical Sciences, School of Bio Science and Technology, VIT, Vellore, Tamil Nadu, 632014

*Corresponding Author E-mail eps674@gmail.com

Online published on 22 April, 2021.


Cyamopsis tetragonoloba is also known as a cluster bean which is an annual legume typically grown in the summer season. Asian and South East Asian countries dominate in the cultivation of this plant and is used as a food source wherein both the seeds as well as the seedpods are consumed. It is also used as feed for cattle and fish. While the immature pods contain a high level of hyaluronic acid, trace amounts of it are seen in the mature pods. It is also the source of the Guar Gum which is made from dried and crushed seeds and chemically, is a neutral polysaccharide containing mannose and galactose units. This is primarily used as a thickening agent and also is known to have certain laxative properties. Previous literature has also suggested its usage in the management of diabetes. The aim of our research is to evaluate the ADME properties and its potential inhibitory target molecule prediction of Cyamopsis tetragonoloba through in-silico analysis. ADME is Absorption, Distribution, Metabolism and Excretion properties that is essential for drug designing. The active compounds of the plant were obtained from literature survey. The canonical SMILES of the compound were retrieved from PubChem database which is submitted to Swiss ADME to obtain its properties. The inhibitory target molecule was obtained from Swiss target prediction online software. The compound were studied to understand its role in molecular pathway which helps in drug designing.



ADME, Cyamopsis tetragonoloba, Inhibitory target molecule prediction, In-silico.


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