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

References

• Appell, M., Compton, D. L., & Evans, K. O. (2020). Predictive quantitative structure-activity relationship modeling of the antifungal and antibiotic properties of triazolothiadiazine compounds. Methods and Protocols, 4(1), 2. https://doi.org/10.3390/mps4010002
   PubMedGoogle Scholar
• Babu, S., Nagarajan, S. K., & Madhavan, T. (2019). Understanding the structural features of JAK2 inhibitors: A combined 3D-QSAR, DFT and molecular dynamics study. Molecular Diversity, 23(4), 845–874. https://doi.org/10.1007/s11030-018-09913-4
   PubMed Web of Science ®Google Scholar
• Baffert, F., Régnier, C. H., De Pover, A., Pissot-Soldermann, C., Tavares, G. A., Blasco, F., Brueggen, J., Chène, P., Drueckes, P., Erdmann, D., Furet, P., Gerspacher, M., Lang, M., Ledieu, D., Nolan, L., Ruetz, S., Trappe, J., Vangrevelinghe, E., Wartmann, M., … Radimerski, T. (2010). Potent and selective inhibition of polycythemia by the quinoxaline JAK2 inhibitor NVP-BSK805NVP-BSK805, a potent and selective JAK2 inhibitor. Molecular Cancer Therapeutics, 9(7), 1945–1955. https://doi.org/10.1158/1535-7163.MCT-10-0053
   PubMed Web of Science ®Google Scholar
• Boström, J. (2001). Reproducing the conformations of protein-bound ligands: A critical evaluation of several popular conformational searching tools. Journal of Computer-Aided Molecular Design, 15(12), 1137–1152. https://doi.org/10.1023/A:1015930826903
   PubMed Web of Science ®Google Scholar
• Bowers, K. J., Chow, E., Xu, H., Dror, R. O., Eastwood, M. P., Gregersen, B. A., Klepeis, J. L., Kolossvary, I., Moraes, M. A., & Sacerdoti, F. D. (2006). Scalable algorithms for molecular dynamics simulations on commodity clusters. Proceedings of the 2006 ACM/IEEE Conference on Supercomputing. IEEE.
   Google Scholar
• Cheeseright, T., Mackey, M., Rose, S., & Vinter, A. (2006). Molecular field extrema as descriptors of biological activity: Definition and validation. Journal of Chemical Information and Modeling, 46(2), 665–676. https://doi.org/10.1021/ci050357s
   PubMed Web of Science ®Google Scholar
• Dhanachandra Singh, K., Karthikeyan, M., Kirubakaran, P., & Nagamani, S. (2011). Pharmacophore filtering and 3D-QSAR in the discovery of new JAK2 inhibitors. Journal of Molecular Graphics and Modelling, 30, 186–197. https://doi.org/10.1016/j.jmgm.2011.07.004
   PubMed Web of Science ®Google Scholar
• Ekins, S., Madrid, P. B., Sarker, M., Li, S. G., Mittal, N., Kumar, P., Wang, X., Stratton, T. P., Zimmerman, M., Talcott, C., Bourbon, P., Travers, M., Yadav, M., & Freundlich, J. S. (2015). Combining metabolite-based pharmacophores with Bayesian machine learning models for Mycobacterium tuberculosis drug discovery. PLOS One, 10(10), e0141076. https://doi.org/10.1371/journal.pone.0141076
   PubMed Web of Science ®Google Scholar
• Floresta, G., & Abbate, V. (2021). Machine learning vs. field 3D-QSAR models for serotonin 2A receptor psychoactive substances identification. RSC Advances, 11(24), 14587–14595. https://doi.org/10.1039/D1RA01335A
   PubMed Web of Science ®Google Scholar
• Georas, S. N., Donohue, P., Connolly, M., & Wechsler, M. E. (2021). JAK inhibitors for asthma. Journal of Allergy and Clinical Immunology, 148(4), 953–963. https://doi.org/10.1016/j.jaci.2021.08.013
   PubMed Web of Science ®Google Scholar
• Gertrudes, J. C., Maltarollo, V. G., Silva, R. A., Oliveira, P. R., Honório, K. M., & da Silva, A. B. (2012). Machine learning techniques and drug design. Current Medicinal Chemistry, 19(25), 4289–4297. https://doi.org/10.2174/092986712802884259
   PubMed Web of Science ®Google Scholar
• Ghoreschi, K., Laurence, A., & O'Shea, J. J. (2009). Janus kinases in immune cell signalling. Immunological Reviews, 228(1), 273–287. https://doi.org/10.1111/j.1600-065X.2008.00754.x
   PubMed Web of Science ®Google Scholar
• Gilson, M. K., Liu, T., Baitaluk, M., Nicola, G., Hwang, L., & Chong, J. (2016). BindingDB in 2015: A public database for medicinal chemistry, computational chemistry and systems pharmacology. Nucleic Acids Research, 44(D1), D1045–D1053. https://doi.org/10.1093/nar/gkv1072
   PubMed Web of Science ®Google Scholar
• Griesshammer, M., Gisslinger, H., & Mesa, R. (2015). Current and future treatment options for polycythemia vera. Annals of Hematology, 94(6), 901–910. https://doi.org/10.1007/s00277-015-2357-4
   PubMed Web of Science ®Google Scholar
• Hua, Y., Wang, W., Zheng, X., Yang, L., Wu, H., Hu, Z., Li, Y., Yue, J., Jiang, Z., Zhang, X., Hou, Q., & Wu, S. (2020). NVP-BSK805, an inhibitor of JAK2 kinase, significantly enhances the radiosensitivity of esophageal squamous cell carcinoma in vitro and in vivo. Drug Design, Development and Therapy 14, 745–755. https://doi.org/10.2147/DDDT.S203048
   PubMed Web of Science ®Google Scholar
• Hubbard, S. R. (2018). Mechanistic insights into regulation of JAK2 tyrosine kinase. Frontiers in Endocrinology, 8, 361. https://doi.org/10.3389/fendo.2017.00361
   PubMed Web of Science ®Google Scholar
• Ihle, J. N., Witthuhn, B. A., Quelle, F. W., Yamamoto, K., Thierfelder, W. E., Kreider, B., & Silvennoinen, O. (1994). Signaling by the cytokine receptor superfamily: JAKs and STATs. Trends in Biochemical Sciences, 19(5), 222–227. https://doi.org/10.1016/0968-0004(94)90026-4 8048164
   PubMed Web of Science ®Google Scholar
• Ihle, J. N., & Kerr, I. M. (1995). Jaks and Stats in signaling by the cytokine receptor superfamily. Trends in Genetics, 11(2), 69–74. PMID: 7716810. https://doi.org/10.1016/s0168-9525(00)89000-9
   PubMed Web of Science ®Google Scholar
• Irwin, J. J., Tang, K. G., Young, J., Dandarchuluun, C., Wong, B. R., Khurelbaatar, M., Moroz, Y. S., Mayfield, J., & Sayle, R. A. (2020). ZINC20—a free ultralarge-scale chemical database for ligand discovery. Journal of Chemical Information and Modeling, 60(12), 6065–6073. https://doi.org/10.1021/acs.jcim.0c00675
   PubMed Web of Science ®Google Scholar
• Keretsu, S., S. P., Bhujbal, & S. J., Cho. (2021). Molecular modeling studies of pyrrolo[2,3-d]pyrimidin-4-amine derivatives as JAK1 inhibitors based on 3D-QSAR, molecular docking, molecular dynamics (MD) and MM-PBSA calculations. Journal of Biomolecular Structure and Dynamics, 39(3), 753–765. https://doi.org/10.1080/07391102.2020.1714483
   PubMed Web of Science ®Google Scholar
• McLornan, D. P., Pope, J. E., Gotlib, J., & Harrison, C. N. (2021). Current and future status of JAK inhibitors. The Lancet, 398(10302), 803–816. PMID: 34454676 https://doi.org/10.1016/S0140-6736(21)00438-4
   PubMed Web of Science ®Google Scholar
• Nogueira, M., Puig, L., & Torres, T. (2020). JAK Inhibitors for Treatment of Psoriasis: Focus on Selective TYK2 Inhibitors. Drugs, 80(4), 341–352. https://doi.org/10.1007/s40265-020-01261-8
   PubMed Web of Science ®Google Scholar
• Rane, S. G., & Reddy, E. P. (2002). JAKs, STATs and SRC kinases in hematopoiesis. Oncogene, 21(21), 3334–3358. https://doi.org/10.1038/sj.onc.1205398
   PubMed Web of Science ®Google Scholar
• Rogler, G. (2020). Efficacy of JAK inhibitors in Crohn’s disease. Journal of Crohn’s & Colitis, 14(Supplement_2), S746–s754. https://doi.org/10.1093/ecco-jcc/jjz186
   PubMedGoogle Scholar
• Romero, F. A., Zak, M., Zhao, G., Gibbons, P., Li, W., Cheng, Y.-X., Yuen, P.-W., & Cheng, L. (2021). Pyrazolopyrimidine compounds and methods of use thereof, United States Patents. Patent No: US 11,155,557 B2, Date of Patent Oct 26, 2021. Applicant: Genentech Inc., San Francisco, CA(US).
   Google Scholar
• Sahoo, S., Adhikari, C., Kuanar, M., & Mishra, B. K. (2016). A short review of the generation of molecular descriptors and their applications in quantitative structure property/activity relationships. Current Computer Aided-Drug Design, 12(3), 181–205. https://doi.org/10.2174/1573409912666160525112114
   PubMed Web of Science ®Google Scholar
• Scott, D. W., & Miller, W. H. (2011). Chapter 8 – skin immune system and allergic skin diseases. In D. W. Scott & W. H. Miller (Eds.), Equine dermatology (second edition, pp. 263–313). W. B. Saunders.
   Google Scholar
• Semerano, L., Decker, P., Clavel, G., & Boissier, M. C. (2016). Developments with investigational Janus kinase inhibitors for rheumatoid arthritis. Expert Opinion on Investigational Drugs, 25(12), 1355–1359. https://doi.org/10.1080/13543784.2016.1249565
   PubMed Web of Science ®Google Scholar
• Sorokina, M., Merseburger, P., Rajan, K., Yirik, M. A., & Steinbeck, C. (2021). Coconut online: Collection of open natural products database. Journal of Cheminformatics, 13(1), 2. https://doi.org/10.1186/s13321-020-00478-9
   PubMed Web of Science ®Google Scholar
• Villarino, A. V., Kanno, Y., & O'Shea, J. J. (2017). Mechanisms and consequences of Jak-STAT signaling in the immune system. Nature Immunology, 18(4), 374–384. https://doi.org/10.1038/ni.3691
   PubMed Web of Science ®Google Scholar
• Wang, L., Ding, J., Pan, L., Cao, D., Jiang, H., & Ding, X. (2019). Artificial intelligence facilitates drug design in the big data era. Chemometrics and Intelligent Laboratory systems, 194(August), 103850. https://doi.org/10.1016/j.chemolab.2019.103850
   Google Scholar
• Wang, X., Lupardus, P., Laporte, S. L., & Garcia, K. C. (2009). Structural biology of shared cytokine receptors. Annual Review of Immunology, 27(1), 29–60. https://doi.org/10.1146/annurev.immunol.24.021605.090616
   PubMedGoogle Scholar
• Wang, E. H. C., Sallee, B. N., Tejeda, C. I., & Christiano, A. M. (2018). JAK inhibitors for treatment of alopecia areata. The Journal of Investigative Dermatology, 138(9), 1911–1916. https://doi.org/10.1016/j.jid.2018.05.027
   PubMed Web of Science ®Google Scholar
• Wei, J. J., Kallenbach, L. R., Kreider, M., Leung, T. H., & Rosenbach, M. (2019). Resolution of cutaneous sarcoidosis after Janus kinase inhibitor therapy for concomitant polycythemia vera. JAAD Case Reports, 5(4), 360–361. https://doi.org/10.1016/j.jdcr.2019.02.006
   PubMedGoogle Scholar
• Wold, S., Sjöström, M., & Eriksson, L. (2001). PLS-regression: A basic tool of chemometrics. Chemometrics and Intelligent Laboratory Systems, 58(2), 109–130. https://doi.org/10.1016/S0169-7439(01)00155-1
   Web of Science ®Google Scholar
• Wrobleski, S. T., Moslin, R., Lin, S., Zhang, Y., Spergel, S., Kempson, J., Tokarski, J. S., Strnad, J., Zupa-Fernandez, A., Cheng, L., Shuster, D., Gillooly, K., Yang, X., Heimrich, E., McIntyre, K. W., Chaudhry, C., Khan, J., Ruzanov, M., Tredup, J., … Weinstein, D. S. (2019). Highly selective inhibition of tyrosine kinase 2 (TYK2) for the treatment of autoimmune diseases: Discovery of the allosteric inhibitor BMS-986165. Journal of Medicinal Chemistry, 62(20), 8973–8995. https://doi.org/10.1021/acs.jmedchem.9b00444
   PubMed Web of Science ®Google Scholar
• You, H., Xu, D., Zhao, J., Li, J., Wang, Q., Tian, X., Li, M., & Zeng, X. (2020). JAK inhibitors: Prospects in connective tissue diseases. Clinical Reviews in Allergy & Immunology, 59(3), 334–351. https://doi.org/10.1007/s12016-020-08786-6
   PubMed Web of Science ®Google Scholar