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Design of novel JAK3 Inhibitors towards Rheumatoid Arthritis using molecular docking analysis



Divya Jain1,3, Trishang Udhwani1, Shreshtha Sharma1, Aishwarya Gandhe1, Palugulla Bhaskar Reddy3, Anuraj Nayarisseri*,1,2,4, Sanjeev Kumar Singh*,4



1In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore 452010, Madhya Pradesh, India; 2Bioinformatics Research Laboratory, LeGene Biosciences Pvt Ltd., Mahalakshmi Nagar, Indore - 452010, Madhya Pradesh, India; 3Department of Biotechnology and Microbiology, Government PG Arts and Science College, Ratlam - 457001, Madhya Pradesh, India; 4Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu, India.


Dr. Sanjeev Kumar Singh Email: skysanjeev@gmail.com; Dr. Anuraj Nayarisseri - anuraj@eminentbio.com *Corresponding authors


Article Type

Research Article



Received January 27, 2019; Revised February 10, 2019; Accepted February 19, 2019; Published February 28, 2019



Multiple cytokines play a pivotal role in the pathogenesis of Rheumatoid Arthritis by inducing intracellular signaling and it is known that the members of the Janus kinase (JAK) family are essential for such signal transduction. Janus kinase 3 is a tyrosine kinase that belongs to the Janus family of kinases. Drugs targeting JAK 3 is known as an effective treatment of Rheumatoid arthritis. Therefore, it of interest to design suitable inhibitors against the JAK3 dimeric structure using the molecular docking tool Molegro Virtual Docker. The compound possessing the highest affinity score is subjected to virtual screening to retrieve inhibitors. The compound SCHEMBL19100243 (PubChem CID- 76749591) displays a high affinity with the target protein. The affinity scores of this compound are more than known drugs. ADMET analysis and BOILED Egg plot provide insights into this compound as a potent inhibitor of JAK3.



Rheumatoid Arthritis, JAK 3 inhibitor, Molecular docking, Virtual screening, BOILED-Egg plot, ADMET



Jain et al. Bioinformation 15(2): 68-78 (2019)


Edited by

P Kangueane






Biomedical Informatics



This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.