Anticancer activity of the new [Ru(eta(5)-C5H5)(PPh3)(Me(2)bpy)][CF3SO3] (Me(2)bpy = 4,4'-dimethyl-2,2'-bipyridine) complex was evaluated in vitro against several human cancer cell lines, namely A2780, A2780CisR, HT29, MCF7, MDAMB231 and PC3. Remarkably, the IC50 values, placed in the nanomolar and sub-micromolar range, largely exceeded the activity of cisplatin. Binding to human serum albumin, either HSA (human serum albumin) or HSA(faf) (fatty acid-free human serum albumin) does not affect the complex activity. Fluorescence studies revealed that the present ruthenium complex strongly quench the intrinsic fluorescence of albumin. Cell death by the [Ru(eta(5)-C5H5)(PPh3)(Me(2)bpy)][CF3SO3] complex was reduced in the presence of endocytosis modulators and at low temperature, suggesting an energy-dependent mechanism consistent with endocytosis. On the whole, the biological activity evaluated herein suggests that the complex could be a promising anticancer agent. (C) 2013 Elsevier Inc. All rights reserved.

Tuberculosis (TB) is a worldwide infectious disease that has shown over time extremely high mortality levels. The urgent need to develop new antitubercular drugs is due to the increasing rate of appearance of multi-drug resistant strains to the commonly used drugs, and the longer durations of therapy and recovery, particularly in immuno-compromised patients. The major goal of the present study is the exploration of data from different families of compounds through the use of a variety of machine learning techniques so that robust QSAR-based models can be developed to further guide in the quest for new potent anti-TB compounds. Eight QSAR models were built using various types of descriptors (from ADRIANA.Code and Dragon software) with two publicly available structurally diverse data sets, including recent data deposited in PubChem. QSAR methodologies used Random Forests and Associative Neural Networks. Predictions for the external evaluation sets obtained accuracies in the range of 0.76-0.88 (for active/inactive classifications) and Q(2)=0.66-0.89 for regressions. Models developed in this study can be used to estimate the anti-TB activity of drug candidates at early stages of drug development (C) 2011 Elsevier B.V. All rights reserved.