Molecular modeling-driven approach for identification of Janus kinase 1 inhibitors through 3D-QSAR, docking and molecular dynamics simulations

Abstract

Janus kinase 1 (JAK 1) belongs to the JAK family of intracellular nonreceptor tyrosine kinase. JAK-signal transducer and activator of transcription (JAK-STAT) pathway mediate signaling by cytokines, which control survival, proliferation and differentiation of a variety of cells. Three-dimensional quantitative structure activity relationship (3 D-QSAR), molecular docking and molecular dynamics (MD) methods was carried out on a dataset of Janus kinase 1(JAK 1) inhibitors. Ligands were constructed and docked into the active site of protein using GLIDE 5.6. Best docked poses were selected after analysis for further 3 D-QSAR analysis using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methodology. Employing 60 molecules in the training set, 3 D-QSAR models were generate that showed good statistical reliability, which is clearly observed in terms of r²_ncv and q²_loo values. The predictive ability of these models was determined using a test set of 25 molecules that gave acceptable predictive correlation (r²_Pred) values. The key amino acid residues were identified by means of molecular docking, and the stability and rationality of the derived molecular conformations were also validated by MD simulation. The good consonance between the docking results and CoMFA/CoMSIA contour maps provides helpful clues about the reasonable modification of molecules in order to design more efficient JAK 1 inhibitors. The developed models are expected to provide some directives for further synthesis of highly effective JAK 1 inhibitors.

Keywords:

• Comparative molecular field analysis
• comparative molecular similarity indices analysis
• partial least squares analysis
• Janus kinase
• extra precision
• molecular dynamics

Acknowledgements

We gratefully acknowledge Tripos Inc and Schrödinger LLC, New York, for providing us the software. The authors RI and SB would like to acknowledge financial support from UGC for research fellowships. We wish to express our gratitude to Department of Chemistry, Osmania University for providing facilities to carry out the research work.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was made possible through grants from Science and Engineering Research Board [SB/EMEQ-004/2013], Council for Scientific and Industrial Research, [01/(2436)/10/EMR-II], University Grants Commission [42?233/2013(SR), and UGC/UPE/FAR/OU/2017] New Delhi, India.