New method for predict biological activity of kinases inhibitors

Volume 2, Issue 2, April 2017     |     PP. 90-104      |     PDF (605 K)    |     Pub. Date: June 19, 2017
DOI:    296 Downloads     7035 Views  

Author(s)

Gabriela Souza Fernandes, Department of Medicine, Federal University of Juiz de Fora, Governador Valadares, Brazil
Michelle Bueno de Moura Pereira, Department of Life Basic Sciencies , Federal University of Juiz de Fora, Governador Valadares, Brazil
Guilherme Rodrigo Reis Monteiro dos Santos, Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School; Laboratory for Translational Research, Hematology, Brigham and Women's Hospital, Harvard Medical School
João Eustáquio Antunes, Department of Pharmacy, Federal University of Juiz de Fora, Governador Valadares, Brazil

Abstract
Computational studies have been applied in order to discover and develop new drugs with the advancer of experimental time reduction. On this way, a group of quinazolines, hypotetical inhibitors of epidermal grow factor (EGFR), has been in one computational models elaborated to do correlation between experimental values of biological activity and the ability of this quinazolines to inhibit the kinase activity. By conversion of biological activity (IC50) in pIC50 we obtained the first group of data for the linear correlation model. The second group of data are computational results obtained. These data were obtained using the computational plataform Molinspitation. Using this approach gave a correlation coefficient R2. This correlation was used for test of new molecules. The capacity of kinase inhibition for each quinazoline was computationally calculated to obtain an estimate pIC50. Three new molecules 1, 2 e 3 has been tested. For molecule 1 the estimate pIC50 was 6.61, what is considerate a strong inhibitor. In the other way the molecule 3 had a low pIC50 (3.56) and was considerate a weak inhibitor. New methodology like that one present in this work could be used for discovery and screening new molecules for synthesis without the needs of expense biological test.

Keywords
Kinase Inhibitors, Quinazoline, Drug Discovery, EGFR

Cite this paper
Gabriela Souza Fernandes, Michelle Bueno de Moura Pereira, Guilherme Rodrigo Reis Monteiro dos Santos, João Eustáquio Antunes, New method for predict biological activity of kinases inhibitors , SCIREA Journal of Chemistry. Volume 2, Issue 2, April 2017 | PP. 90-104.

References

[ 1 ] Silva BV, Horta BAC, Alencastro RB and Pinto AC. (2009). Proteínas quinases: características estruturais e inibidores químicos. Quim. Nova. 32, 453-462.
[ 2 ] Avila CM and Romeiro NC. (2010). Proteínas Tirosinas Quinases: Desafios do Desenvolvimento de Fármacos para a Terapia do Câncer. Rev. Virt. Quim. 2, 59-82.
[ 3 ] Amalie FR, Skovgaard T, Knapp S, Jensen LJ and Berthelsen JA. (2014). Comparison of Protein Kinases Inhibitor Screening Methods Using Both Enzymatic Activity and Binding Affinity Determination. Plos One. 9, 1-5.
[ 4 ] Shepherd FA, Pereira Jr, Ciuleanu T, et al. (2005). Erlotinib in previously treated non-small-cell lung cancer. The New Engl. Jour. Med. 353, 123-132.
[ 5 ] Antunes JE. (2009) Modelagem MIA-QSAR das atividades biológicas de inibidores da fosfodiasterase tipo-5. [Dissertação de Mestrado] - Universidade Federal de Lavras.
[ 6 ] Freitas MP, Brown SD and Martins JA. (2005). MIA-QSAR: a simple 2D image-based approach for quantitative structure–activity relationship analysis. Jour. Mol. Struct. 738, 149-154.
[ 7 ] Bridges AJ, Zhou H, Cody DR, Rewcastle GW, Mcmichael A, Showalter HDH, Fry DW, Kraker AJ and Denny WA. (1996). Tyrosine Kinase Inhibitors. An Unusually Steep Structure−Activity Relationship for Analogues of 4-(3-Bromoanilino)-6,7-dimethoxyquinazoline (PD 153035), a Potent Inhibitor of the Epidermal Growth Factor Receptor. Jour. Med. Chem. 39, 267-276.
[ 8 ] Antunes JE, Freitas MP and Rittner R. (2008a). Bioactivities of a series of phosphodiesterase type 5 (PDE-5) inhibitors as modelled by MIA-QSAR. Eur. Jour. Med. Chem. 43, 1632-1638.
[ 9 ] Fernandes GS, Antunes JE, Pereira MBM, Marinho ACB, Machado B, Moreira ACS, Freitas MP and Lang K. (2015). In silico Pharmacokinetics Studies for Quinazolines Proposed as EGFR Inhibitors. Open Jour. Med. Chem. 5, 106-115.
[ 10 ] Antunes JE, Freitas MP, Da Cunha EFF, Ramalho TC and Rittner R. (2008b) In silico prediction of novel phosphodiesterase type-5 inhibitors derived from Sildenafil, Vardenafil and Tadalafil. Bioorg. Med. Chem. 16, 7599-7606.
[ 11 ] Dancey C and Reidy J. (2006). Estatística Sem Matemática para Psicologia: Usando SPSS para Windows. 5. ed. Porto Alegre, Artmed.
[ 12 ] Jacob C. (1988). Statistical power analysis for the behavioral sciences. 2.ed. Hillsdale, NJ: Erlbaum.
[ 13 ] Duarte MH, Barige SJ and Freitas MP. (2015). Exploring MIA-QSAR's for antimalarial quinolon-4(1H)-imines. Comb. Chem. & High Throughput Screening. 18, 208-215.
[ 14 ] Lioret GR, Cunha NA, Rittner R, Bittencourt M, Freitas MP and Aquino AS. (2009). Synthesis and Rational Design of Anti-Inflammatory Compounds: N-Phenyl-Cyclohexenylsulfonamide Derivatives. Jour. Phys. Org. Chem. 22, 1188-1192.