Target identification and mechanism of action studies play an important role in small-molecule discovery. Advances in miniaturization have made cell-based assays increasingly attractive as primary screening systems to discover new biologically active compounds, allowing initial tests in more disease-relevant settings but requiring follow-up studies to determine the precise protein target or pathway responsible for the observed phenotype.
Target identification can be approached by direct biochemical methods, genetic interactions, or computational inference. Combinations these approaches may be required to fully characterize mechanisms of small-molecule action. Accordingly, the Broad Institute uses a multi-faceted approach to the target identification problem in the context of genome-based drug discovery, including:
- quantitative proteomics based on mass spectrometry
- genetic complementation of small-molecule effects using RNA interference
- computational inference by connectivity analysis using reference compounds
Integrating these approaches depends on the ability to connect experimental data with annotations about both small molecule activities and the bioinformatics of candidate targets. We use public sources of term-based annotations (e.g., GO, MeSH) to connect small-molecule activities with existing biological knowledge, and publicly available interaction databases (e.g., STRING) to map results to candidate pathways and aid biological interpretations.
In our group, we apply bioinformatic analyses to connect proteomics, RNAi knockdown, gene-expression, and other data to generate target hypotheses. We have also advanced the development of a compound comparison method that uses small-molecule profiles based on historical screening data to assess ‘assay performance similarity’ of a pair of compounds. In combination with existing methods of hypothesis generation, such as the Connectivity Map, such approaches provide powerful insights into mechanism for small-molecules shown to be active in cells.
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