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.

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