A proteome reference map of Neisseria gonorrhoeae was successfully established using twodimensional gel electrophoresis in conjunction with matrix-assisted laser desorption ionizationtime of flight mass spectrometry. This map was further applied to compare protein expression profiles of high-level spectinomycin-resistant (clinical isolate) and -susceptible (reference strain) N. gonorrhoeae following treatment with subminimal inhibitory concentrations (subMICs) of spectinomycin. Approximately 200 protein spots were visualized by Coomassie brilliant blue G-250 staining and 66 spots representing 58 unique proteins were subsequently identified. Most of the identified proteins were analysed as cytoplasmic proteins and belonged to the class of energy metabolism. Comparative proteomic analysis of whole protein expression of susceptible and resistant gonococci showed up to 96 % similarity while eight proteins were found to be differentially expressed in the resistant strain. In the presence of subMICs of spectinomycin, it was found that 50S ribosomal protein L7/L12, an essential component for ribosomal translocation, was upregulated in both strains, ranging from 1.5-to 3.5-fold, suggesting compensatory mechanisms of N. gonorrhoeae in response to antibiotic that inhibits protein synthesis. Moreover, the differential expression of proteins involved in energy metabolism, amino acid biosynthesis, and the cell envelope was noticeably detected, indicating significant cellular responses and adaptation against antibiotic stress. Such knowledge provides valuable data, not only fundamental proteomic data, but also knowledge of the mode of action of antibiotic and secondary target proteins implicated in adaptation and compensatory mechanisms.

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Aromatase, the rate-limiting enzyme that catalyzes the conversion of androgen to estrogen, plays an essential role in the development of estrogen-dependent breast cancer. Side effects due to aromatase inhibitors (AIs) necessitate the pursuit of novel inhibitor candidates with high selectivity, lower toxicity and increased potency. Designing a novel therapeutic agent against aromatase could be achieved computationally by means of ligand-based and structure-based methods. For over a decade, we have utilized both approaches to design potential AIs for which quantitative structure–activity relationships and molecular docking were used to explore inhibitory mechanisms of AIs towards aromatase. However, such approaches do not consider the effects that aromatase variants have on different AIs. In this study, proteochemometrics modeling was applied to analyze the interaction space between AIs and aromatase variants as a function of their substructural and amino acid features. Good predictive performance was achieved, as rigorously verified by 10-fold cross-validation, external validation, leave-one-compound-out cross-validation, leave-one-protein-out cross-validation and Y-scrambling tests. The investigations presented herein provide important insights into the mechanisms of aromatase inhibitory activity that could aid in the design of novel potent AIs as breast cancer therapeutic agents.

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