The (5Z)-5-Pentacosenoic and 5-Pentacosynoic Acids Inhibit the HIV-1 Reverse Transcriptase

Lipids - The natural fatty acids (5Z)-5-pentacosenoic and (9Z)-9-pentacosenoic acids were synthesized for the first time in eight steps starting from either 4-bromo-1-butanol or 8-bromo-1-butanol...     

Hierarchical Clustering and Target-Independent QSAR for Antileishmanial Oxazole and Oxadiazole Derivatives

Leishmaniasis is a neglected tropical disease that kills more than 20,000 people each year. The chemotherapy available for the treatment of the disease is limited, and novel approaches to discover novel drugs are urgently needed. Herein, 2D- and 4D-quantitative structure–activity relationship (QSAR) models were developed for a series of oxazole and oxadiazole derivatives that are active against Leishmania infantum, the causative agent of visceral leishmaniasis. A clustering strategy based on structural similarity was applied with molecular fingerprints to divide the complete set of compounds into two groups. Hierarchical clustering was followed by the development of 2D- (R² = 0.90, R²pred = 0.82) and 4D-QSAR models (R² = 0.80, R²pred = 0.64), which showed improved statistical robustness and predictive ability.     

Structural and chemical basis for enhanced affinity and potency for a large series of estrogen receptor ligands: 2D and 3D QSAR studies

The estrogen receptor (ER) is an important drug target for the development of novel therapeutic agents for the treatment of breast cancer. Progress towards the design of more potent and selective ER modulators requires the optimization of multiple ligand-receptor interactions. Comparative molecular field analyses (CoMFA) and hologram quantitative structure-activity relationships (HQSAR) were conducted on a large set of ERalpha modulators. Two training sets containing either 127 or 69 compounds were used to generate QSAR models for in vitro binding affinity and potency, respectively. Significant correlation coefficients (affinity models, CoMFA, r(2)=0.93 and q(2)=0.79; HQSAR, r(2)=0.92 and q(2)=0.71; potency models, CoMFA, r(2)=0.94 and q(2)=0.72; HQSAR, r(2)=0.92 and q(2)=0.74) were obtained, indicating the potential of the models for untested compounds. The generated models were validated using external test sets, and the predicted values were in good agreement with the experimental results. The final QSAR models as well as the information gathered from 3D contour maps should be useful for the design of novel ERalpha modulators having improved affinity and potency.     

3D QSAR comparative molecular field analysis on nonsteroidal farnesoid X receptor activators

Three-dimensional quantitative structure–activity relationships (3D QSAR) were performed for a series of farsenoid X receptor activators using comparative molecular field analysis (CoMFA). A training set containing 77 compounds served to establish the models. The best statistical results among all models were obtained with region focusing weighted by a S.D. × coefficient values of 0.8 and a grid spacing of 1.0 (r² = 0.963, SEE = 0.097; q² = 0.742, SEP = 0.255). The model was used to predict the potency of 20 test set compounds that were not included in the training set, and the predicted values were in good agreement with the experimental results. The final CoMFA model along with the information obtained from 3D contour maps should be useful for the design of novel FXR ligands having improved potency.