Worldwide, tuberculosis (TB) is the leading cause of death among curable infectious diseases. Multidrug-resistant Mycobacterium tuberculosis is an emerging problem of great importance to public health, and there is an urgent need for new anti-TB drugs. In the present work, classical 2D quantitative structure-activity relationships (QSAR) and hologram QSAR (HQSAR) studies were performed on a training set of 91 isoniazid derivatives. Significant statistical models (classical QSAR, q (2) = 0.68 and r (2) = 0.72; HQSAR, q (2) = 0.63 and r (2) = 0.86) were obtained, indicating their consistency for untested compounds. The models were then used to evaluate an external test set containing 24 compounds which were not included in the training set, and the predicted values were in good agreement with the experimental results (HQSAR, r(2)(pred) = 0.87; classical QSAR, r(2)(pred) = 0.75).
Estrogens exert important physiological effects through two human estrogen receptor subtypes (hERs), alpha (hERα) and beta (hERβ). While hERα is a macromolecular target of great importance for breast cancer therapy, hERβ is an attractive drug target for the development of novel therapeutic agents for hormone replacement therapy. Progress towards the design of modulators having improved potency, affinity and selectivity requires the optimization of multiple ligand-receptor interactions. The strong multidisciplinary character of modern Medicinal Chemistry supplies a rich arsenal of useful rational strategies for the design of new drug candidates. Molecular modeling tools and quantitative structure-activity relationships (QSAR) are integrated into the drug design process in the search of bioactive molecules having optimized properties. In this study, standard data sets were organized for different chemical classes of ER modulators, integrating the qualified information about chemical structure associated to the corresponding pharmacological property. The data sets established the scientific basis for the development of models employing the hologram QSAR, CoMFA and GRID/PCA methods. The final HQSAR and CoMFA models possess high internal and external consistency, with good correlative and predictive power. The generated QSAR and GRID/PCA models as well as the information gathered from the 3D contour maps provide useful guidelines for the design of new selective ER modulators having improved affinity and potency.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.