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Research Article

Molecular docking-based classification and systematic QSAR analysis of indoles as Pim kinase inhibitors

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Pages 399-419 | Received 12 Feb 2020, Accepted 31 Mar 2020, Published online: 22 Apr 2020

References

  • V. Asati, D.K. Mahapatra, and S.K. Bharti, PIM kinase inhibitors: Structural and pharmacological perspectives, Eur. J. Med. Chem. 172 (2019), pp. 95–108. doi:10.1016/j.ejmech.2019.03.050.
  • N.A. Keane, M. Reidy, A. Natoni, M.S. Raab, and M. O’dwyer, Targeting the Pim kinases in multiple myeloma, Blood. Cancer J. 5 (2015), pp. 325–334. doi:10.1038/bcj.2015.46.
  • N.M. Santio and P.J. Koskinen, PIM kinases: From survival factors to regulators of cell motility, Int. J. Biochem. Cell. Biol. 93 (2017), pp. 74–85. doi:10.1016/j.biocel.2017.10.016.
  • M. Narlik‐Grassow, C. Blanco‐Aparicio, and A. Carnero, The PIM family of serine/threonine kinases in cancer, Med. Res. Rev. 34 (2014), pp. 136–159. doi:10.1002/med.21284.
  • N.A. Warfel and A.S. Kraft, PIM kinase (and Akt) biology and signaling in tumors, Pharmacol. Therapeut. 151 (2015), pp. 41–49. doi:10.1016/j.pharmthera.2015.03.001.
  • A. Bora, S. Avram, I. Ciucanu, M. Raica, and S. Avram, Predictive models for fast and effective profiling of kinase inhibitors, J. Chem. Inf. Model. 56 (2016), pp. 895–905. doi:10.1021/acs.jcim.5b00646.
  • P.M. Fischer, Approved and experimental small‐molecule oncology kinase inhibitor drugs: A mid‐2016 overview, Med. Res. Rev. 37 (2017), pp. 314–367. doi:10.1002/med.21409.
  • M. Rask-Andersen, J. Zhang, D. Fabbro, and H.B. Schiöth, Advances in kinase targeting: Current clinical use and clinical trials, Trends Pharmacol. Sci. 35 (2014), pp. 604–620. doi:10.1016/j.tips.2014.09.007.
  • K.N. More, V.S. Hong, A. Lee, J. Park, S. Kim, and J. Lee, Discovery and evaluation of 3, 5-disubstituted indole derivatives as Pim kinase inhibitors, Bioorg. Med. Chem. Lett. 28 (2018), pp. 2513–2517. doi:10.1016/j.bmcl.2018.05.054.
  • J. Lee, K.N. More, S.A. Yang, and V.S. Hong, 3, 5-Bis (aminopyrimidinyl) indole derivatives: Synthesis and evaluation of pim kinase inhibitory activities, B. Korean Chem. Soc. 35 (2014), pp. 2123–2129. doi:10.5012/bkcs.2014.35.7.2123.
  • K.N. More, H.W. Jang, V.S. Hong, and J. Lee, Pim kinase inhibitory and antiproliferative activity of a novel series of meridianin C derivatives, Bioorg. Med. Chem. Lett. 24 (2014), pp. 2424–2428. doi:10.1016/j.bmcl.2014.04.035.
  • G. Liu, Y. Wan, W. Wang, S. Fang, S. Gu, and X. Ju, Docking-based 3D-QSAR and pharmacophore studies on diarylpyrimidines as non-nucleoside inhibitors of HIV-1 reverse transcriptase, Mol. Div. 23 (2019), pp. 107–121. doi:10.1007/s11030-018-9860-1.
  • M. Asadollahi-Baboli and S. Dehnavi, Docking and QSAR analysis of tetracyclic oxindole derivatives as α-glucosidase inhibitors, Comput. Biol. Chem. 76 (2018), pp. 283–292. doi:10.1016/j.compbiolchem.2018.07.019.
  • S. Simeon, R. Möller, D. Almgren, H. Li, C. Phanus-umporn, V. Prachayasittikul, and L. Bülow, Unraveling the origin of splice switching activity of hemoglobin β-globin gene modulators via QSAR modeling, Chemom. Intell. Lab. Syst. 151 (2016), pp. 51–60. doi:10.1016/j.chemolab.2015.12.002.
  • K. Seraj and M. Asadollahi-Baboli, In silico evaluation of 5-hydroxypyrazoles as LSD1 inhibitors based on molecular docking derived descriptors, J. Mol. Struct. 1179 (2019), pp. 514–524. doi:10.1016/j.molstruc.2018.11.019.
  • HyperChem(TM) Professional 8.0. Available at www.hyper.com.
  • Molecular Operating Environment, MOE2014.09, Chemical Computing Group. Available at www.chemcomp.com.
  • E-Dragon software. Available at www.vcclab.org/lab/edragon.
  • A. Mauri, V. Consonni, and R. Todeschini, Molecular Descriptors. Handbook of Computational Chemistry, John Wiley & Sons, Weinheim, Germany, 2017.
  • A.M. Al-Fakih, Z.Y. Algamal, M.H. Lee, M. Aziz, and H.T.M. Ali, QSAR classification model for diverse series of antifungal agents based on improved binary differential search algorithm, SAR. QSAR. Environ. Res. 30 (2019), pp. 131–143. doi:10.1080/1062936X.2019.1568298.
  • P. Shahbazikhah, M. Asadollahi-Baboli, R. Khaksar, R.F. Alamdari, and V. Zare-Shahabadi, Predicting partition coefficients of migrants in food simulant/polymer systems using adaptive neuro-fuzzy inference system, J. Braz. Chem. Soc. 22 (2011), pp. 1446–1451. doi:10.1590/S0103-50532011000800007.
  • M. Asadollahi-Baboli, Quantitative structure–activity relationship analysis of human neutrophil elastase inhibitors using shuffling classification and regression trees and adaptive neuro-fuzzy inference systems, SAR. QSAR. Environ. Res. 23 (2012), pp. 505–520. doi:10.1080/1062936X.2012.665811.
  • MATLAB Version 11.1. Available at www.mathworks.com.
  • R. Shahin, L. Swellmeen, O. Shaheen, N. Aboalhaija, and M. Habash, Identification of novel inhibitors for Pim-1 kinase using pharmacophore modeling based on a novel method for selecting pharmacophore generation subsets, J. Comput. Aid. Mol. Des. 30 (2016), pp. 39–68. doi:10.1007/s10822-015-9887-7.
  • M. Hemmer, Expert Systems, in Handbook of Chemoinformatics, Wiley-VCH Verlag, Weinheim, Germany, 2003.
  • M.P. González, C. Terán, M. Teijeira, and A.M. Helguera, Radial distribution function descriptors: An alternative for predicting A2 adenosine receptors agonists, Eur. J. Med. Chem. 41 (2006), pp. 56–62. doi:10.1016/j.ejmech.2005.08.004.
  • J.C. Dearden, The use of topological indices in QSAR and QSPR modeling, in Advances in QSAR Modeling, K. Roy (ed.), Springer, Cham, Switzerland, 2017.
  • A.U. Khan, Descriptors and their selection methods in QSAR analysis: Paradigm for drug design, Drug. Discov. Today 21 (2016), pp. 1291–1302. doi:10.1016/j.drudis.2016.06.013.
  • M. Asadollahi-Baboli and A. Mani-Varnosfaderani, Shuffling multivariate adaptive regression splines as a predictive method for modeling of novel pyridylmethylthio derivatives as VEGFR2 inhibitors, Med. Chem. Res. 22 (2013), pp. 2645–2653. doi:10.1007/s00044-012-0266-9.
  • K. Roy, P. Ambure, and R.B. Aher, How important is to detect systematic error in predictions and understand statistical applicability domain of QSAR models? Chemom. Intell. Lab. Syst. 162 (2017), pp. 44–54. doi:10.1016/j.chemolab.2017.01.010.
  • M. Asadollahi-Baboli and A. Mani-Varnosfaderani, Therapeutic index modeling and predictive QSAR of novel thiazolidin-4-one analogs against Toxoplasma gondii, Eur. J. Pharm. Sci. 70 (2017), pp. 117–124. doi:10.1016/j.ejps.2015.01.014.
  • C. Rücker, G. Rücker, and M. Meringer, Y-Randomization and its variants in QSPR/QSAR, J. Chem. Inf. Model. 47 (2007), pp. 2345–2357. doi:10.1021/ci700157b.
  • M. Asadollahi-Baboli, In silico evaluation, molecular docking and QSAR analysis of quinazoline-based EGFR-T790M inhibitors, Mol. Div. 20 (2016), pp. 729–739. doi:10.1007/s11030-016-9672-0.
  • A. Valadkhani, M. Asadollahi-Baboli, and A. Mani-Varnosfaderani, QSAR study of the inhibitors of the acetyl-CoA carboxylase 1 and 2 using bayesian regularized genetic neural networks: A comparative study, J. Braz. Chem. Soc. 26 (2015), pp. 619–631. doi:10.5935/0103-5053.20150017.
  • S. Weaver and M.P. Gleeson, The importance of the domain of applicability in QSAR modeling, J. Mol. Graph. Model. 26 (2008), pp. 1315–1326. doi:10.1016/j.jmgm.2008.01.002.
  • K. Roy, S. Kar, and P. Ambure, On a simple approach for determining applicability domain of QSAR models, Chemom. Intell. Lab. Syst. 145 (2015), pp. 22–29. doi:10.1016/j.chemolab.2015.04.013.
  • S.R. Peddi, S.R. Peddi, S. Sivan, R. Veerati, and V. Manga, Integrated molecular docking, 3D QSAR and molecular dynamics simulation studies on indole derivatives for designing new Pim-1 inhibitors, J. Recept. Sig. Transd. 1 (2020), pp. 1–4. doi:10.1080/10799893.2020.1713809.
  • H. Razmazma, A. Ebrahimi, and M. Hashemi, Structural insights for rational design of new PIM-1 kinase inhibitors based on 3,5-disubstituted indole derivatives: An integrative computational approach, Comput. Biol. Med. 118 (2020), pp. 103641. doi:10.1016/j.compbiomed.2020.103641.

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