A mass accuracy sensitive probability based scoring algorithm for database searching of tandem mass spectrometry data

<p>Abstract</p> <p>Background</p> <p>Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has become one of the most used tools in mass spectrometry based proteomics. Various algorithms have since been developed to automate the process for modern high-throughput LC-MS/MS experiments.</p> <p>Results</p> <p>A probability based statistical scoring model for assessing peptide and protein matches in tandem MS database search was derived. The statistical scores in the model represent the probability that a peptide match is a random occurrence based on the number or the total abundance of matched product ions in the experimental spectrum. The model also calculates probability based scores to assess protein matches. Thus the protein scores in the model reflect the significance of protein matches and can be used to differentiate true from random protein matches.</p> <p>Conclusion</p> <p>The model is sensitive to high mass accuracy and implicitly takes mass accuracy into account during scoring. High mass accuracy will not only reduce false positives, but also improves the scores of true positive matches. The algorithm is incorporated in an automated database search program MassMatrix.</p

Correlating chemical sensitivity and basal gene expression reveals mechanism of action

Changes in cellular gene expression in response to small-molecule or genetic perturbations have yielded signatures that can connect unknown mechanisms of action (MoA) to ones previously established. We hypothesized that differential basal gene expression could be correlated with patterns of small-molecule sensitivity across many cell lines to illuminate the actions of compounds whose MoA are unknown. To test this idea, we correlated the sensitivity patterns of 481 compounds with ~19,000 basal transcript levels across 823 different human cancer cell lines and identified selective outlier transcripts. This process yielded many novel mechanistic insights, including the identification of activation mechanisms, cellular transporters, and direct protein targets. We found that ML239, originally identified in a phenotypic screen for selective cytotoxicity in breast cancer stem-like cells, most likely acts through activation of fatty acid desaturase 2 (FADS2). These data and analytical tools are available to the research community through the Cancer Therapeutics Response Portal.Chemistry and Chemical Biolog

Diversity-oriented synthesis yields novel multistage antimalarial inhibitors

Antimalarial drugs have thus far been chiefly derived from two sources—natural products and synthetic drug-like compounds. Here we investigate whether antimalarial agents with novel mechanisms of action could be discovered using a diverse collection of synthetic compounds that have three-dimensional features reminiscent of natural products and are underrepresented in typical screening collections. We report the identification of such compounds with both previously reported and undescribed mechanisms of action, including a series of bicyclic azetidines that inhibit a new antimalarial target, phenylalanyl-tRNA synthetase. These molecules are curative in mice at a single, low dose and show activity against all parasite life stages in multiple in vivo efficacy models. Our findings identify bicyclic azetidines with the potential to both cure and prevent transmission of the disease as well as protect at-risk populations with a single oral dose, highlighting the strength of diversity-oriented synthesis in revealing promising therapeutic targets