Binding mode of conformations and structure-based pharmacophore development for farnesyltransferase inhibitors

Farnesyltransferase (FTase) is one of the prenyltransferase family enzymes that catalyse the transfer of 15-membered isoprenoid (farnesyl) moiety to the cysteine of CAAX motif-containing proteins including Rho and Ras family of G proteins. Inhibitors of FTase act as drugs for cancer, malaria, progeria and other diseases. In the present investigation, we have developed two structure-based pharmacophore models from protein–ligand complex (3E33 and 3E37) obtained from the protein data bank. Molecular dynamics (MD) simulations were performed on the complexes, and different conformers of the same complex were generated. These conformers were undergone protein–ligand interaction fingerprint (PLIF) analysis, and the fingerprint bits have been used for structure-based pharmacophore model development. The PLIF results showed that Lys164, Tyr166, TrpB106 and TyrB361 are the major interacting residues in both the complexes. The RMSD and RMSF analyses on the MD-simulated systems showed that the absence of FPP in the complex 3E37 has significant effect in the conformational changes of the ligands. During this conformational change, some interactions between the protein and the ligands are lost, but regained after some simulations (after 2 ns). The structure-based pharmacophore models showed that the hydrophobic and acceptor contours are predominantly present in the models. The pharmacophore models were validated using reference compounds, which significantly identified as HITs with smaller RMSD values. The developed structure-based pharmacophore models are significant, and the methodology used in this study is novel from the existing methods (the original X-ray crystallographic coordination of the ligands is used for the model building). In our study, along with the original coordination of the ligand, different conformers of the same complex (protein–ligand) are used. It concluded that the developed methodology is significant for the virtual screening of novel molecules on different targets.     

Gender,race and socioeconomic influence on diagnosis and treatment of thyroid disorders in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

Thyroid diseases are common, and use of levothyroxine is increasing worldwide. We investigated the influence of gender, race and socioeconomic status on the diagnosis and treatment of thyroid disorders using data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), a multicenter cohort study of civil servants (35-74 years of age) from six Brazilian cities. Diagnosis of thyroid dysfunction was by thyrotropin (TSH), and free thyroxine (FT4) if TSH was altered, and the use of specific medications. Multivariate logistic regression models were constructed using overt hyperthyroidism/hypothyroidism and levothyroxine use as dependent variables and sociodemographic characteristics as independent variables. The frequencies of overt hyper- and hypothyroidism were 0.7 and 7.4%, respectively. Using whites as the reference ethnicity, brown, and black race were protective for overt hypothyroidism (OR=0.76, 95%CI=0.64-0.89, and OR=0.53, 95%CI=0.43-0.67, respectively, and black race was associated with overt hyperthyroidism (OR=1.82, 95%CI=1.06-3.11). Frequency of hypothyroidism treatment was higher in women, browns, highly educated participants and those with high net family incomes. After multivariate adjustment, levothyroxine use was associated with female gender (OR=6.06, 95%CI=3.19-11.49) and high net family income (OR=3.23, 95%CI=1.02-10.23). Frequency of hyperthyroidism treatment was higher in older than in younger individuals. Sociodemographic factors strongly influenced the diagnosis and treatment of thyroid disorders, including the use of levothyroxine.