Author(s):
Jerine Peter S, Nagesh Kishan Panchal, Aishwaria V Nair, Kshitija Joshi, Shobhy Sosa Andrews, Evan Prince Sabina
Email(s):
eps674@gmail.com
DOI:
10.5958/0974-360X.2021.00026.3 
Address:
Jerine Peter S, Nagesh Kishan Panchal, Aishwaria V Nair, Kshitija Joshi, Shobhy Sosa Andrews, Evan Prince Sabina*
Department of Biomedical Sciences, School of Bio Science and Technology, VIT, Vellore, Tamil Nadu, 632014.
*Corresponding Author
Published In:
Volume - 14,
Issue - 1,
Year - 2021
ABSTRACT:
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.
Cite this article:
Jerine Peter S, Nagesh Kishan Panchal, Aishwaria V Nair, Kshitija Joshi, Shobhy Sosa Andrews, Evan Prince Sabina. ADME and Inhibitory Target Molecules Predicition of Cyamopsis tetragonoloba. Research J. Pharm. and Tech. 2021; 14(1):146-152. doi: 10.5958/0974-360X.2021.00026.3
Cite(Electronic):
Jerine Peter S, Nagesh Kishan Panchal, Aishwaria V Nair, Kshitija Joshi, Shobhy Sosa Andrews, Evan Prince Sabina. ADME and Inhibitory Target Molecules Predicition of Cyamopsis tetragonoloba. Research J. Pharm. and Tech. 2021; 14(1):146-152. doi: 10.5958/0974-360X.2021.00026.3 Available on: https://www.rjptonline.org/AbstractView.aspx?PID=2021-14-1-26
REFERENCES:
1. Dhugga KS, Barreiro R, Whitten B, et al. Guar seed beta-mannan synthase is a member of the cellulose synthase super gene family. Science (New York, N.Y.). 2004; 303(5656):363-366.
2. Nishimura H, Nose M, Hiai H, Minato N, Honjo T. Development of lupus-like autoimmune diseases by disruption of the PD-1 gene encoding an ITIM motif-carrying immunoreceptor. Immunity. 1999; 11(2):141-151.
3. Naoumkina M, Torres-Jerez I, Allen S, et al. Analysis of cDNA libraries from developing seeds of guar (Cyamopsis tetragonoloba (L.) Taub). BMC plant biology. 2007; 7:62.
4. Vrbanac J, Slauter R. Chapter 2 - ADME in Drug Discovery. In: Faqi AS, ed. A Comprehensive Guide to Toxicology in Preclinical Drug Development. Academic Press; 2013:3-30.
5. Abdelwahab NS, Hassan HM, Magd AMA. Rapid microwave-assisted hydrolytic degradation of colchicine: In silico ADME/Tox profile, molecular docking, and development of innovative RP-Chromatographic methods. Microchemical Journal. November 2019:104419.
6. Vukic VR, Loncar DM, Vukic DV, et al. In vitro antitumor activity, ADME-Tox and 3D-QSAR of synthesized and selected natural styryl lactones. Computational Biology and Chemistry. 2019; 83:107112.
7. Duchowicz PR, Talevi A, Bellera C, Bruno-Blanch LE, Castro EA. Application of descriptors based on Lipinski’s rules in the QSPR study of aqueous solubilities. Bioorganic & Medicinal Chemistry. 2007; 15(11):3711-3719.
8. Wang D. Current Research Method in Transporter Study. Advances in Experimental Medicine and Biology. 2019; 1141:203-240.
9. Pogaku V, Gangarapu K, Basavoju S, Tatapudi KK, Katragadda SB. Design, synthesis, molecular modelling, ADME prediction and anti-hyperglycemic evaluation of new pyrazole-triazolopyrimidine hybrids as potent α-glucosidase inhibitors. Bioorganic Chemistry. 2019; 93:103307.
10. Prieto-Martínez FD, López-López E, Eurídice Juárez-Mercado K, Medina-Franco JL. Chapter 2 - Computational Drug Design Methods—Current and Future Perspectives. In: Roy K, ed. In Silico Drug Design. Academic Press; 2019:19-44.
11. Daina A, Michielin O, Zoete V. iLOGP: A Simple, Robust, and Efficient Description of n-Octanol/Water Partition Coefficient for Drug Design Using the GB/SA Approach. Journal of Chemical Information and Modeling. 2014; 54(12):3284-3301.
12. Ertl P, Rohde B, Selzer P. Fast calculation of molecular polar surface area as a sum of fragment-based contributions and its application to the prediction of drug transport properties. Journal of Medicinal Chemistry. 2000; 43(20):3714-3717.
13. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews. 2001; 46(1-3):3-26.
14. Egan WJ, Merz KM, Baldwin JJ. Prediction of drug absorption using multivariate statistics. Journal of Medicinal Chemistry. 2000; 43(21):3867-3877.
15. Wu B, Song H-P, Zhou X, et al. Screening of minor bioactive compounds from herbal medicines by in silico docking and the trace peak exposure methods. Journal of Chromatography. A. 2016; 1436:91-99.
16. Ekins S, Mestres J, Testa B. In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling. British Journal of Pharmacology. 2007; 152(1):9-20.