QSAR Studies of amino-pyrimidine derivatives as Mycobacterium tuberculosis Protein Kinase B inhibitors

Year 2018, Volume: 2 Issue: 2, 16 - 27, 15.12.2018

Saida Khamoulı Salah Belaıdı , Houmam Belaıdı Lotfi Belkhırı

https://doi.org/10.33435/tcandtc.397449

Cited By: 2

Abstract

Quantitative structure activity relationship (QSAR)
analysis was applied to a series of amino-pyrimidine derivatives as PknB
inhibitors using a combination of various physicochemical and quantum
descriptors. A multiple linear regression (MLR) procedure was used to model the
relationships between molecular descriptors and the chemotherapeutic activity
of the amino-pyrimidine derivatives. Good agreement between experimental and
predicted activity values, obtained in the validation procedure, indicated the
good quality of the derived QSAR model. The statistically
significant best QSAR model has a cross validated correlation coefficient R²_CV=
0.973 and external predictive ability of prediction R² = 0.778 was
developed by MLR. The proposed model has good robustness and
predictability when verified by internal and external validation.

Keywords

QSAR, amino-pyrimidine, PknB, MLR

References

• [1] K. McDonough, Y. Kress, B. R. Bloom, Pathogenesis of tuberculosis: interaction of Mycobacterium tuberculosis with macrophages, Infection and Immunity 61 (1993) 2763-2773.
• [2] K. Rohini , P. S. Srikumar, Insights from the docking and molecular dynamics simulation of the Phosphopantetheinyl transferase (PpTt) structural model from Mycobacterium tuberculosis, Bioinformation 9 (2013) 685–689.
• [3] K. E. Lougheed, S. A. Osborne, B. Saxty, D. Whalley , T. Chapman, N. Bouloc , et al, Effective inhibitors of the essential kinase PknB and their potential as anti-mycobacterial agents, Tuberculosis (Edinburgh, Scotland) 91 (2011) 277-286.
• [4] S. Lapenna, A. Giordano, Cell cycle kinases as therapeutic targets for cancer, Nature Reviews. Drug Discovery 8 (2009) 547-566.
• [5] V. U. Ahmad, A. Khan, U. F. arooq, F. Kousar, S.S. Khan, S. A. Nawaz, M. A. Abbasi , M. I. Choudhary, Three new cholinesterase-inhibiting cis-clerodanediterpenoids from Otostegialimbata , Chemical & Pharmaceutical Bulletin 53 (2005) 378-381.
• [6] Z. N. Siddiqui , F. Farooq, Heterocyclic Silica supported sodium hydrogen sulfate (NaHSO4–SiO2): A novel, green catalyst for synthesis of pyrazole and pyranyl pyridine derivatives under solvent-free condition via heterocyclic β-enaminones, Journal of Molecular Catalysis A: Chemical 363 (2012) 451-459.
• [7] Y. Lim, H.W. Xu, W.Fan, Q. Ye, X. Wang, B. Jiang, S. L. Wan, S. J. Tu ,New formal (3+3) cycloaddition of enaminones for forming tetracyclic indolo[2,3-b]quinolines under microwave irradiation ,Tetrahedron 70 (2014)1004-1010.
• [8] S. N. Bukhari, S. G. Franzblau, I. Jantan , M. Jasamai, Current prospects of synthetic curcumin analogs and chalcone derivatives against mycobacterium tuberculosis, Medicinal Chemistry 9(2013)897-903.
• [9] J. B. Nachega, R. E .Chaisson ,Tuberculosis drug resistance: a global threat, Clinical Infectious Diseases 36 (2003) 24-30.
• [10] M. Raviglione, I. Smith, XDR tuberculosis-implications for global public health, New England Journal Of Medicine 356 (200) 656–659.
• [11] S. Belaidi, T. Salah, N. Melkemi, L. Sinha, O. Prasad , Structure Activity Relationship and Quantitative Structure-Activity Relationships Modeling of Antitrypanosomal Activities of AlkyldiamineCryptolepine Derivatives, Journal of Computational and Theoretical Nanoscience 12 (2015)1–7.
• [12] K. Dermeche, N. Tchouar, S. Belaidi, T. Salah ,Qualitative Structure-Activity Relationships and 2D-QSAR Modeling of TNF- Inhibition by Thalidomide Derivatives, Journal of Bionanoscience 9 (2015) 395–400.
• [13] S. Belaidi, Z. Almi, D. Bouzidi , Electronic Structure and Physical-Chemistry Properties Relationship for Phenothiazine Derivatives by Quantum Chemical Calculations, Journal of Computational and Theoretical Nanoscience 11 (2014) 2481-2488.
• [14] S. Khamouli, S. Belaidi, Z. Almi, S. Medjahed, H. Belaidi, Property/Activity Relationships and Drug Likeness for Pyrimidine Derivatives as Serine/Threonine Protein Kinase B Inhibitors, Journal of Bionanoscience 11 (2017) 1–9.
• [15] D. M. Hawkins The Problem of Overfitting. Journal of chemical information and computer sciences 44 (2004)1-12.
• [16] L. Eriksson, J. Jaworska, A. P. Worth, M. T. D. Cronin, M. c. Dowel, P. Gramatica , Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs, Environmental Health Perspectives 111 (2003)1361–1375.
• [17] T. M. Chapman, N. Bouloc, R. S. Buxton, J. Chugh, K. E. Lougheed, S. A. Osborne, et al, Substituted aminopyrimidine protein kinase B (PknB) inhibitors show activity against Mycobacterium tuberculosis, Bioorganic & Medicinal Chemistry Letters 22 (2012) 3349-3353 .
• [18] M. V. Damre, R. P. Gangwal, G. V. Dhoke, M. Lalit, D.Sharma, K. Khandelwal, A. T. Sangamwar, 3D-QSAR and molecular docking studies of amino-pyrimidine derivatives as PknB inhibitors, Journal of the Taiwan Institute of Chemical Engineers 45 (2014) 354-364.
• [19] HyperChem (Molecular Modeling System) Hypercube (2008) Inc., 1115 NW, 4th Street, Gainesville, FL 32601, USA.
• [20] M. J. Frisch, G. W. Trucks, H. B. Schlegel, G. E. Scuseria, M. A. Robb, J. R. Cheeseman, G. Scalmani, V. Barone, B. Mennucci, G. A. Petersson, H. Nakatsuji, M. Caricato, X. Li, H. P. Hratchian, A. F. Izmaylov, J. Bloino, G. Zheng, J. L. Sonnenberg, M. Hada, M. Ehara, K. Toyota, R. Fukuda, J. Hasegawa, M. Ishida, T. Nakajima, Y. Honda, O. Kitao, H. Nakai, T. Vreven, J. A. Montgomery Jr., J. E. Peralta, F. Ogliaro, M. Bearpark, J. J. Heyd, E. Brothers, K. N. Kudin, V. N. Staroverov, R. Kobayashi, J. Normand, K. Raghavachari, A. Rendell, J. C. Burant, S. S. Iyengar, J. Tomasi, M. Cossi, N. Rega, J. M. Millam, M. Klene, J. E. Knox, J. B. Cross, V. Bakken, C. Adamo, J. Jaramillo, R. Gomperts, R. E. Stratmann, O. Yazyev, A. J. Austin, R. Cammi, C. Pomelli, J. W. Ochterski, R. L. Martin, K. Morokuma, V. G. Zakrzewski, G. A. Voth, P. Salvador, J. J. Dannenberg, S. Dapprich, A. D. Daniels, Ö. Farkas, J. B. Foresman, J. V. Ortiz, J. Cioslowski, D. J. Fox, Gaussian 09, Revision A.02, Gaussian, Inc., Wallingford CT (2009).
• [21] SPSS software packages, SPSS Inc., 444 North Michigan Avenue, Suite 3000, Chicago, Illinoi, 60611, USA.
• [22] A. Golbraikh, A. Tropsha, Beware of q2, Journal of Molecular Graphics and Modelling 20 (2002) 269–276.
• [23] A. Tropsha, P. Gramatica, V. K. Gombar,The importance of being earnest: validation is the absolute essential for successful application and interpretation of QSPR models, QSAR & Combinatorial Science 22 (2003) 69–77.
• [24] K. J. Sanmati, J. Rahul, S. Lokesh, K. Y. Arvind , QSAR Analysis on 3,5-disubstituted-4,5-dihydropyrazole-1-carbothioamides as epidermal growth factor receptor (EGFR) kinase inhibitors, Journal of Chemical and Pharmaceutical Research 4(2012) 3215-3223.
• [25] S. O. Podunavac-Kuzmanovic, D. D. Cvetkovic, D. J. Barna, QSAR Analysis of 2-Amino or 2-Methyl-1-Substituted Benzimidazoles Against Pseudomonas aeruginosa, International Journal of Molecular Sciences 10 (2009) 1670-1682.
• [26] M. Jalali-Heravi , A. Kyani , Use of computer-assisted methods for the modeling of the retention time of a variety of volatile organic compounds: a PCA-MLR-ANN approach, Journal of chemical information and computer sciences 44 ( 2004) 1328-1335.