Análise energética in silico da interação do ER? com estrogênios relacionados a neoplasma mamária: estradiol e dietilestilbestrol

Abstract

Breast cancer is a hormone-dependent disease, which has several different subtypes, patterns of gene expression and distinct manifestations (CHENG et al., 2002). According to the National Cancer Institute (INCA), in women, it has the highest incidence and mortality in both developing and developed countries. The majority of breast neoplasms are ER + (estrogen receptor positive), ie, 17β-estradiol dependent and the number of ERα (estrogen receptor alpha subtype), is higher than the number of ERβ (estrogen receptor subtype beta), evidencing the importance of the alpha subtype in this disease. This work measured the individual binding energies of the residues composing ERα with 17β-estradiol and Diethylstilbestrol, using computational simulation. For that, the Functional Density Theory (DFT) and the Molecular Fractionation Method with Conjugated Caps (MFCC) were used. The results obtained showed the residues with the most significant energy values are: GLU353, LEU391, MET343, LEU346, MET388, ARG394, PHE404, HIS524, ASP411, LEU525, ARG352 and ARG548. The results obtained showed that the residues with the most significant energy values are: GLU353, LEU391, MET343, LEU346, MET388, ARG394, PHE404, HIS524, ASP411, LEU525, ARG352 and ARG548. These results help to characterize the interaction between 17βestradiol and Diethylstilbestrol with ERα and, in turn, can be used as a basis for studies, structural drug design, modulation of existing drugs, such as for the design of new drugs.