Small-molecule profiling experiments simultaneously annotate many possible consequences of small-molecule action, often using multiplexed or high-content assay readouts. Profiling experiments may also explore the consequences of small-molecule action on different cell types or cell states, such as genotype-dependent sensitivities to small molecules. Finally, profiles of small-molecule performance can be assembled from the contents of public databases. We are interested in methods that allow hypothesis generation of targets of novel small molecules based on performance similarity in cell-based assays, and in connections between small-molecule performance and decisions made during small-molecule library synthesis, such as build/couple/pair syntheses.
High-throughput small-molecule screens typically use a single measurement, for example, enzyme inhibition or the activity of a reporter gene, to find and prioritize ‘hit’ compounds for probe or drug development. By contrast, small-molecule profiling experiments simultaneously annotate many possible consequences of small-molecule action, often using multiplexed or high-content assay readouts. We are engaged in small-molecule profiling studies involving several such assay technologies, including:
Profiling experiments can also involve testing compounds in different cellular contexts. In one such example, we are engaged in data analysis following exposure of a collection of specific probe compounds to panels of cell lines with different lesions characteristic of human cancers. We aim to connect cancer genotype to acquired cancer dependencies and identify small molecules that target the dependencies.
The growing content of public databases of multiple parallel small-molecule experiments, such as ChemBank and PubChem, provide a source of performance profiles that integrate work done by many investigators. Rich annotation of small molecules can provide novel connections between compounds based on similar performance across many assays, which we exploit in target identification studies.
In our group, we specialize in the analysis of small-molecule profiling data from existing and emerging measurement technologies, and by assembling results from public data sources. We have established principles for normalization and analysis of small-molecule profiling data that allow similarities and differences between small molecules to be measured in terms of variation in performance in different biological contexts. This ‘compound-centric’ view of small-molecule performance provides a facile link to our parallel work in cheminformatics research, which links biological consequences to decisions made during synthesis.
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