Enhancing drug discovery through in silico screening: strategies to increase true positives retrieval rates.

Computational chemistry software for lead discovery has become well established in pharmaceutical industry and has found its way to the desktop computers of medicinal chemists for different purposes, providing insight on the mode of action and binding properties, and creating new ideas for lead structure refinement. In this review we investigate the performance and reliability of recent state-of-the-art data modeling techniques, as well as ligand-based and structure-based modeling approaches for 3D virtual screening. We discuss and summarize recently published success stories and lately developed techniques. Parallel screening is one of these emerging approaches allowing for efficient activity in silico profiling of several compounds against different targets or anti-targets simultaneously. This is of special interest to medicinal chemists, as the approach allows revealing unknown binding modes ('target-fishing') as well as integrated ADME profiling or--more generally--the prediction of off-target effects.

Synthesis and anti-microbial activity evaluation of some new 1-benzoyl-isothiosemicarbazides.

The synthesis of some aroylisothiosemicarbazides was accomplished and their biological activity against bacteria, fungi, and mycobacteria was investigated. Different synthetic pathways were followed according to the kind of substituents that were introduced on both the aroyl ring and the sulfur atom. Anti-bacterial activity was measured against Staphylococcus aureus, S. epidermidis, Streptococcus agalactiae and S. faecalis, Escherichia coli, and Salmonella typhi, while antifungal activity was evaluated against C. albicans. Two species, Mycobacterium tuberculosis H37RV and Mycobacterium avium ATCC19421, were employed to evaluate antimycobacterial activity.