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Field-based 3D-QSAR for tyrosine protein kinase JAK-2 inhibitors. | LitMetric

Field-based 3D-QSAR for tyrosine protein kinase JAK-2 inhibitors.

J Biomol Struct Dyn

School of Pharamcy, Anurag University, Venkatapur, Ghatkesar, Medchal-Malkajgiri district, Hyderabad, Telangana, India.

Published: July 2024

The present work aimed to develop a Field-based 3D-QSAR model with existing JAK-2 inhibitors. The JAK-STAT pathway is known to play a role in the development of autoimmune diseases, including rheumatoid arthritis, ulcerative colitis, and Crohn's disease. Dysregulation of JAK-STAT is also linked to the development of myelofibrosis and other myeloproliferative diseases. JAK antagonists can be used in many areas of medicine. There are many compounds that already show inhibition of Jak-2. We have developed a Field-based 3D QSAR model which showed good correlation values ( 0.884 and 0.67) with an external test set regression pred_ 0.562. Various properties, such as electronegativity, electro positivity, hydrophobicity, and shape features, were studied under the activity atlas to determine the inhibitory potential of ligands. These were also identified as important structural features responsible for biological activity. We performed virtual screening based on the pharmacophore features of the co-crystal ligand (PDB ID: 3KRR) and a dataset of NPS was selected with a RMSD value less than 0.8. The developed 3D QSAR model was used to screen ligands and calculate the predicted JAK-2 inhibition activity (pKi). The results of the virtual screening were validated using molecular docking and molecular dynamics simulations. SNP1 (SN00154718) and SNP2 (SN00213825) showed binding affinity of -11.16 and -11.08 kcal/mol, respectively, which were very close to the crystal ligand of 3KRR, -11.67 kcal/mol. The RMSD plot of the protein-ligand complex of SNP1 and 3KRR showed stable interactions with an average RMSD of 2.89 Å. Thus, a statistically robust 3D QSAR model could reveal more inhibitors and aid in the design of novel JAK-2 inhibitors.

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Source
http://dx.doi.org/10.1080/07391102.2023.2226723DOI Listing

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