High-content screening is transforming drug discovery by enabling simultaneous measurement of multiple features of cellular phenotype that are relevant to therapeutic and toxic activities of compounds. High-content screening studies typically generate immense datasets of image-based phenotypic information, and how best to mine relevant phenotypic data is an unsolved challenge. Here, we introduce factor analysis as a data-driven tool for defining cell phenotypes and profiling compound activities. This method allows a large data reduction while retaining relevant information, and the data-derived factors used to quantify phenotype have discernable biological meaning. We used factor analysis of cells stained with fluorescent markers of cell cycle state to profile a compound library and cluster the hits into seven phenotypic categories. We then compared phenotypic profiles, chemical similarity and predicted protein binding activities of active compounds. By integrating these different descriptors of measured and potential biological activity, we can effectively draw mechanism-of-action inferences.

Class II major histocompatibility complex (MHC) proteins are essential for normal immune system function but also drive many autoimmune responses. They bind peptide antigens in endosomes and present them on the cell surface for recognition by CD4(+) T cells. A small molecule could potentially block an autoimmune response by disrupting MHC-peptide interactions, but this has proven difficult because peptides bind tightly and dissociate slowly from MHC proteins. Using a high-throughput screening assay we discovered a class of noble metal complexes that strip peptides from human class II MHC proteins by an allosteric mechanism. Biochemical experiments indicate the metal-bound MHC protein adopts a 'peptide-empty' conformation that resembles the transition state of peptide loading. Furthermore, these metal inhibitors block the ability of antigen-presenting cells to activate T cells. This previously unknown allosteric mechanism may help resolve how gold(I) drugs affect the progress of rheumatoid arthritis and may provide a basis for developing a new class of anti-autoimmune drugs.