Generic placeholder image

Letters in Drug Design & Discovery

Editor-in-Chief

ISSN (Print): 1570-1808
ISSN (Online): 1875-628X

Research Article

QSAR Model Study of 2,3,4,5-tetrahydro-1H-pyrido[4,3-b]indole of Cystic- brosis-transmembrane Conductance-regulator Gene Potentiators

Author(s): Yaru Si, Kang Ma, Yingfeng Hu, Hongzong Si* and Honglin Zhai

Volume 19, Issue 4, 2022

Published on: 22 October, 2021

Page: [269 - 278] Pages: 10

DOI: 10.2174/1570180818666211022142920

Price: $65

conference banner
Abstract

Background: Cystic Fibrosis (CF) is a genetic disease, which has no effective treatment.

Objective: The aim of our research is to predict the EC50 value of 2,3,4,5-tetrahydro-1H-pyrido[4,3- b]indole core as a novel chemotype of potentiators to establish a highly predicting quantitative structureactivity relationship model.

Methods: 41 products were optimized, and a linear model was built by a heuristic method in CODESSA program. In this study, 3 descriptors were selected and utilized to build a nonlinear model in gene expression programming.

Results: The square of the correlation coefficient of the heuristic method is 0.57, and the s2 is 0.30. In gene expression programming, the square of correlation coefficient and the mean square error for the training set are 0.74 and 0.13, respectively. The square of correlation coefficient and the mean square error for the test set are 0.70 and 0.27, respectively.

Conclusion: The GEP model has stronger predictive ability to help develop the novel structure of 2,3,4,5- tetrahydro-1H-pyrido[4,3-b]indole of cystic-brosis-transmembrane conductance-regulator gene potentiators.

Keywords: Cystic fibrosis, quantitative structure-activity relationship, gene expression programming, heuristic method, cysticbrosis- transmembrane conductance-regulator gene, EC50.

Graphical Abstract

[1]
Stoltz, D.A.; Meyerholz, D.K.; Welsh, M.J. Origins of cystic fibrosis lung disease. N. Engl. J. Med., 2015, 372(4), 351-362.
[http://dx.doi.org/10.1056/NEJMra1300109] [PMID: 25607428]
[2]
Aleksandrov, A.A.; Aleksandrov, L.A.; Riordan, J.R. CFTR (ABCC7) is a hydrolyzable-ligand-gated channel. Pflugers Arch., 2007, 453(5), 693-702.
[http://dx.doi.org/10.1007/s00424-006-0140-z] [PMID: 17021796]
[3]
Shapiro, M.E.; Corcoran, T.E.; Bertrand, C.A. Physiologically-based model of fluid absorption and mucociliary clearance in cystic fibrosis. IFAC, 2018, 51(19), 102-103.
[http://dx.doi.org/10.1016/j.ifacol.2018.09.023]
[4]
Colledge, W.H.; Evans, M.J. Cystic fibrosis gene therapy. Curr. Opin. Genet. Dev., 1994, 4(3), 466-471.
[http://dx.doi.org/10.1016/0959-437X(94)90037-X] [PMID: 7522673]
[5]
Castellani, C.; Assael, B.M. Cystic fibrosis: A clinical view. Cell. Mol. Life Sci., 2017, 74(1), 129-140.
[http://dx.doi.org/10.1007/s00018-016-2393-9] [PMID: 27709245]
[6]
Peters, D.H.; Sorkin, E.M. Meyler’s Side Effects of Drugs, 16th ed; Zonisamide - ScienceDirect, 2016.
[7]
Fuchs, H.J.; Borowitz, D.S.; Christiansen, D.H.; Morris, E.M.; Nash, M.L.; Ramsey, B.W.; Rosenstein, B.J.; Smith, A.L.; Wohl, M.E. Effect of aerosolized recombinant human DNase on exacerbations of respiratory symptoms and on pulmonary function in patients with cystic fibrosis. N. Engl. J. Med., 1994, 331(10), 637-642.
[http://dx.doi.org/10.1056/NEJM199409083311003] [PMID: 7503821]
[8]
DiMasi, J.A.; Grabowski, H.G.; Hansen, R.W. Innovation in the pharmaceutical industry: New estimates of R&D costs. J. Health Econ., 2016, 47(5), 20-33.
[http://dx.doi.org/10.1016/j.jhealeco.2016.01.012] [PMID: 26928437]
[9]
Neely, W.B.; Branson, D.R.; Blau, G.E. Partition coefficient to measure bioconcentration potential of organic chemicals in fish. Environ. Sci. Technol., 1974, 8(13), 1113-1115.
[http://dx.doi.org/10.1021/es60098a008]
[10]
Roy, K.; Sanyal, I.; Roy, P.P. QSPR of the bioconcentration factors of non-ionic organic compounds in fish using extended topochemical atom (ETA) indices. SAR QSAR Environ. Res., 2006, 17(6), 563-582.
[http://dx.doi.org/10.1080/10629360601033499] [PMID: 17162387]
[11]
Ruah, S.H. Pyridyl derivatives as CFTR modulators. U.S. Patent 8,227,615, 2012.
[12]
Wang, S.M.; Wu, Y.; Wang, W. Application of ixazomib monotherapy and combination therapy in patients with multiple myeloma. Cancer Cell Research, 2020, 7(27), 744-748.
[13]
Ferreira, C. Genetic representation and genetic neutrality in gene expression programming. Adv. Complex Syst., 2002, 5(04), 389-408.
[http://dx.doi.org/10.1142/S0219525902000626]
[14]
Froimowitz, M. HyperChem: A software package for computational chemistry and molecular modeling. Biotechniques, 1993, 14(6), 1010-1013.
[PMID: 8333944]
[15]
Yang, B.; Si, H.; Zhai, H. QSAR studies on the IC50 of a class of thiazolidinone/thiazolide based hybrids as antitrypanosomal agents. Lett. Drug Des. Discov., 2021, 18(4)
[16]
Csonka, G.I. Analysis of the core-repulsion functions used in AM1 and PM3 semiempirical calculations: Conformational analysis of ring systems. J. Comput. Chem., 1993, 14(8), 895-898.
[http://dx.doi.org/10.1002/jcc.540140803]
[17]
Katritzky, A.R.; Perumal, S.; Petrukhin, R.; Kleinpeter, E. Codessa-based theoretical QSPR model for hydantoin HPLC-RT lipophilicities. J. Chem. Inf. Comput. Sci., 2001, 41(3), 569-574.
[http://dx.doi.org/10.1021/ci000099t] [PMID: 11410031]
[18]
Boyd, D.B. Quantum chemistry program exchange. J. Mol. Graph. Model., 1999, 17(1), 62-63.
[PMID: 10660912]
[19]
Mancuso, J.; McEachern, R.J. Applications of the PM3 semi-empirical method to the study of triethylenediamine. J. Mol. Graph. Model., 1997, 15(2), 82-90, 101.
[http://dx.doi.org/10.1016/S1093-3263(97)00025-9] [PMID: 9385556]
[20]
Katritzky, A.R.; Petrukhin, R.; Jain, R.; Karelson, M. QSPR analysis of flash points. J. Chem. Inf. Comput. Sci., 2001, 41(6), 1521-1530.
[http://dx.doi.org/10.1021/ci010043e] [PMID: 11749578]
[21]
Si, H.; Zhao, J.; Cui, L.; Lian, N.; Feng, H.; Duan, Y.B.; Hu, Z. Study of human dopamine sulfotransferases based on gene expression programming. Chem. Biol. Drug Des., 2011, 78(3), 370-377.
[http://dx.doi.org/10.1111/j.1747-0285.2011.01155.x] [PMID: 21668651]
[22]
Si, Y.; Xu, X.; Hu, Y.; Si, H.; Zhai, H. Novel qsar model to predict activity of natural products against covid-19. Chem. Biol. Drug Des., 2021, 97(4), 978-983.
[23]
Liao, S.L.; Song, J.; Wang, Z.D.; Chen, J.Z.; Chen, S.Y. Quantitative calculation of the influence of the molecular association between terpenoid repellents and CO2 on their repellency against mosquitoes. Acta Entomol. Sinica, 2012, 55(9), 1054-1061.
[24]
Liu, C.; Shao, Y.J.; Deng, F.L.; Yuan, F.; Chen, Y.C.; Wen, S.Y.; Zhang, J.Y.; Zhao, W.; He, Z.K.; Yan, J.Y.; Cui, X.Y.; Sun, X.Y.; Yue, C.W.; Lv, Y.H. Advances in anticancer activity of natural products from fungi. Cancer Cell Research, 2020, 7(27), 736-743.
[25]
Mulliken, R.S. Electronic structures of molecules xi. Electroaffinity, Molecular Orbitals and Dipole Moments. J. Chem. Phys., 1935, 3(9), 573-585.
[http://dx.doi.org/10.1063/1.1749731]
[26]
Liao, S.L.; Song, J.; Wang, Z.D.; Chen, J.Z.; Chen, S.C.; Fan, G.R.; Jiang, Z.K.; Han, Z.J. Quantitative calculation of the effect of terpenoids association with carbon dioxide on their mosquito repellent activity. Acta Entomol. Sinica., 2012, 9, 58-65.
[27]
Latscha, H.P.; Kazmaier, U.; Klein, H.A. Die nucleophile Substitution (SN) am gesättigten C-Atom. Org. Chem., 2002, 127-136.

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy