Folate analogue inhibitors of Leishmania major pteridine reductase (PTR1) are potential antiparasitic drug candidates for combined therapy with dihydrofolate reductase (DHFR) inhibitors. To identify new molecules with specificity for PTR1, we carried out a virtual screening of the Available Chemicals Directory (ACD) database to select compounds that could interact with L. major PTR1 but not with human DHFR. Through two rounds of drug discovery, we successfully identified eighteen drug-like molecules with low micromolar affinities and high in vitro specificity profiles. Their efficacy against Leishmania species was studied in cultured cells of the promastigote stage, using the compounds both alone and in combination with 1 (pyrimethamine; 5-(4-chlorophenyl)-6-ethylpyrimidine-2,4-diamine). Six compounds showed efficacy only in combination. In toxicity tests against human fibroblasts, several compounds showed low toxicity. One compound, 5c (riluzole; 6-(trifluoromethoxy)-1,3-benzothiazol-2-ylamine), a known drug approved for CNS pathologies, was active in combination and is suitable for early preclinical evaluation of its potential for label extension as a PTR1 inhibitor and antiparasitic drug candidate.

Enterobacteria have developed numerous constitutive and inducible strategies to sense and adapt to an external acidity. These molecular responses require dozens of specific acid shock proteins (ASPs), as shown by genomic and proteomic analysis. Most of the ASPs remain poorly characterized, and their role in the acid response and survival is unknown. We recently identified an Escherichia coli gene, asr (acid shock RNA), encoding a protein of unknown function, which is strongly induced by high environmental acidity (pH < 5.0). We show here that Asr is required for growth at moderate acidity (pH 4.5) as well as for the induction of acid tolerance at moderate acidity, as shown by its ability to survive subsequent transfer to extreme acidity (pH 2.0). Sodium dodecyl sulfate-polyacrylamide gel electrophoresis and Western analysis of acid-shocked E. coli cells harboring a plasmid-borne asr gene demonstrated that the Asr protein is synthesized as a precursor with an apparent molecular mass of 18 kDa. Mutational studies of the asr gene also demonstrated the Asr preprotein contains 102 amino acids. This protein is subjected to an N-terminal cleavage of the signal peptide and a second processing event, yielding 15-and 8-kDa products, respectively. Only the 8-kDa polypeptide was detected in acid-shocked cells containing only the chromosomal copy of the asr gene. N-terminal sequencing and site-directed mutagenesis revealed the two processing sites in the Asr protein precursor. Deletion of amino acids encompassing the processing site required for release of the 8-kDa protein resulted in an acid-sensitive phenotype similar to that observed for the asr null mutant, suggesting that the 8-kDa product plays an important role in the adaptation to acid shock. Analysis of Asr:PhoA fusions demonstrated a periplasmic location for the Asr protein after removal of the signal peptide. Homologues of the asr gene from other Enterobacteriaceae were cloned and shown to be induced in E. coli under acid shock conditions.

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We present a computational procedure for modeling protein-protein association and predicting the structures of protein-protein complexes. The initial sampling stage is based on an efficient Brownian dynamics algorithm that mimics the physical process of diffusional association. Relevant biochemical data can be directly incorporated as distance constraints at this stage. The docked configurations are then grouped with a hierarchical clustering algorithm into ensembles that represent potential protein-protein encounter complexes. Flexible refinement of selected representative structures is done by molecular dynamics simulation. The protein-protein docking procedure was thoroughly tested on 10 structurally and functionally diverse protein-protein complexes. Starting from X-ray crystal structures of the unbound proteins, in 9 out of 10 cases it yields structures of protein-protein complexes close to those determined experimentally with the percentage of correct contacts >30% and interface backbone RMSD <4 A. Detailed examination of all the docking cases gives insights into important determinants of the performance of the computational approach in modeling protein-protein association and predicting of protein-protein complex structures.

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