Fragment-based and classical quantitative structure-activity relationships for a series of hydrazides as antituberculosis agents

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(pred)(2) = 0.87; classical QSAR, r(pred)(2) = 0.75).

Classical and fragment-based hologram structure-activity relationships for a series of analgesic cyclic imides

Cyclic imides have been widely employed in drug design research due to their multiple pharmacological and biological properties. In the present study, two-dimensional quantitative structure-activity relationship (2D QSAR) studies were conducted on a series of potent analgesic cyclic imides using both classical and hologram QSAR (HQSAR) methods, yielding significant statistical models (classical QSAR, q(2) = 0.80; HQSAR, q(2) = 0.84). The models were then used to evaluate an external data test, and the predicted values were in good agreement with the experimental results, indicating their consistency for untested compounds.

Structure-activity relationships for a class of selective inhibitors of the major cysteine protease from Trypanosoma cruzi

Chagas` disease is a parasitic infection widely distributed throughout Latin America, with devastating consequences in terms of human morbidity and mortality. Cruzain, the major cysteine protease from Trypanosoma cruzi, is an attractive target for antitrypanosomal chemotherapy. In the present work, classical two-dimensional quantitative structure-activity relationships (2D QSAR) and hologram QSAR (HQSAR) studies were performed on a training set of 45 thiosemicarbazone and semicarbazone derivatives as inhibitors of T. cruzi cruzain. Significant statistical models (HQSAR, q2=0.75 and r2=0.96; classical QSAR, q2=0.72 and r2=0.83) were obtained, indicating their consistency for untested compounds. The models were then used to evaluate an external test set containing 10 compounds which were not included in the training set, and the predicted values were in good agreement with the experimental results (HQSAR, [image omitted]=0.95; classical QSAR, [image omitted]=0.91), indicating the existence of complementary between the two ligand-based drug design techniques.

Comparative molecular field analysis of a series of inhibitors of HIV-1 protease

Several protease inhibitors have reached the world market in the last fifteen years, dramatically improving the quality of life and life expectancy of millions of HIV-infected patients. In spite of the tremendous research efforts in this area, resistant HIV-1 variants are constantly decreasing the ability of the drugs to efficiently inhibit the enzyme. As a consequence, inhibitors with novel frameworks are necessary to circumvent resistance to chemotherapy. In the present work, we have created 3D QSAR models for a series of 82 HIV-1 protease inhibitors employing the comparative molecular field analysis (CoMFA) method. Significant correlation coefficients were obtained (q(2) = 0.82 and r(2) = 0.97), indicating the internal consistency of the best model, which was then used to evaluate an external test set containing 17 compounds. The predicted values were in good agreement with the experimental results, showing the robustness of the model and its substantial predictive power for untested compounds. The final QSAR model and the information gathered from the CoMFA contour maps should be useful for the design of novel anti-HIV agents with improved potency.

Discovery of New Inhibitors of Schistosoma mansoni PNP by Pharmacophore-Based Virtual Screening

Schistosomiasis is considered the second most important tropical parasitic disease, with severe socioeconomic consequences for millions of people worldwide. Schistosoma monsoni, one of the causative agents of human schistosomiasis, is unable to synthesize purine nucleotides de novo, which makes the enzymes of the purine salvage pathway important targets for antischistosomal drug development. In the present work, we describe the development of a pharmacophore model for ligands of S. mansoni purine nucleoside phosphorylase (SmPNP) as well as a pharmacophore-based virtual screening approach, which resulted in the identification of three thioxothiazolidinones (1-3) with substantial in vitro inhibitory activity against SmPNP. Synthesis, biochemical evaluation, and structure activity relationship investigations led to the successful development of a small set of thioxothiazolidinone derivatives harboring a novel chemical scaffold as new competitive inhibitors of SmPNP at the low-micromolar range. Seven compounds were identified with IC(50) values below 100 mu M. The most potent inhibitors 7, 10, and 17 with 1050 of 2, 18, and 38 mu M, respectively, could represent new potential lead compounds for further development of the therapy of schistosomiasis.