Using whole-cell phenotypic assays, the GlaxoSmithKline high-throughput screening (HTS) diversity set of 1.8 million compounds was screened against the three kinetoplastids most relevant to human disease, i.e. Leishmania donovani, Trypanosoma cruzi and Trypanosoma brucei. Secondary confirmatory and orthogonal intracellular anti-parasiticidal assays were conducted, and the potential for non-specific cytotoxicity determined. Hit compounds were chemically clustered and triaged for desirable physicochemical properties. The hypothetical biological target space covered by these diversity sets was investigated through bioinformatics methodologies. Consequently, three anti-kinetoplastid chemical boxes of ~200 compounds each were assembled. Functional analyses of these compounds suggest a wide array of potential modes of action against kinetoplastid kinases, proteases and cytochromes as well as potential host–pathogen targets. This is the first published parallel high throughput screening of a pharma compound collection against kinetoplastids. The compound sets are provided as an open resource for future lead discovery programs, and to address important research questions.

Drug binding to Human Serum Albumin (HSA) is an area of intense research. The pharmacokinetics and pharmacodynamics of drugs are strongly affected by their binding to this protein. In this article, the field is reviewed, as well as our models to predict drug-binding affinities to HSA from drug structure. The physiological role of HSA is described, as well as its influence in drug action. The crystal structures of this protein are discussed, emphasizing the two drug-binding sites and the fatty acids binding sites observed therein. The advantages of using high-performance affinity chromatography to rapidly screen drugs for HSA binding are explained. The different QSAR models for HSA binding of restricted families of drugs (both from other groups and our group) are enumerated. Finally, a detailed description of our general models to predict drug-binding strengths to HSA from structure is given. It is expected for these models to be useful in drug design and pharmaceutical research.

Models to predict binding affinities to human serum albumin (HSA) should be very useful in the pharmaceutical industry to speed up the design of new compounds, especially as far as pharmacokinetics is concerned. We have experimentally determined through high-performance affinity chromatography the binding affinities to HSA of 95 diverse drugs and druglike compounds. These data have allowed us the derivation of quantitative structure-activity relationship models to predict binding affinities to HSA of new compounds on the basis of their structure. Simple linear, one-variable models have been derived for specific families of compounds (r(2) > or = 0.80; q(2) > or = 0.62): beta-adrenergic antagonists, steroids, COX inhibitors, and tricyclic antidepressants. Also, global models have been derived to be applicable to the whole medicinal chemical space by using the full database of HSA binding constants described above. For this aim, a genetic algorithm has been used to exhaustively search and select for multivariate and nonlinear equations, starting from a large pool of molecular descriptors. The resulting models display good fits to the experimental data (r(2) > or = 0.78; LOF< or = 0.12). In addition, both internal (cross validation and randomization) and external validation tests have demonstrated that these models have good predictive power (q(2) > or = 0.73; PRESS/SSY < or = 0.23; r(2) > or = 0.82 for the external set). Statistical analysis of the equation populations indicates that hydrophobicity (as measured by the ClogP) is the most important variable determining the binding extent to HSA. In addition, structural factors (especially the topological (6)chi(ring) index and some Jurs descriptors) also frequently appear as descriptors in the best equations. Therefore, binding to HSA turns out to be determined by a combination of hydrophobic forces together with some modulating shape factors. This agrees with X-ray structures of HSA alone or bound to ligands, where the binding pockets of both sites I and II are composed mainly of hydrophobic residues.

The stringent response enables Mycobacterium tuberculosis (Mtb) to shut down its replication and metabolism under various stresses. Here we show that Mtb lacking the stringent response enzyme RelMtb was unable to slow its replication rate during nutrient starvation. Metabolomics analysis revealed that the nutrient-starved relMtb-deficient strain had increased metabolism similar to that of exponentially growing wild-type bacteria in nutrient-rich broth, consistent with an inability to enter quiescence. Deficiency of relMtb increased the susceptibility of mutant bacteria to killing by isoniazid during nutrient starvation and in the lungs of chronically infected mice. We screened a pharmaceutical library of over 2 million compounds for inhibitors of RelMtb and showed that the lead compound X9 was able to directly kill nutrient-starved M. tuberculosis and enhanced the killing activity of isoniazid. Inhibition of RelMtb is a promising approach to target M. tuberculosis persisters, with the potential to shorten the duration of TB treatment.