Drug Search and Design Considering Cell Specificity of Chemically Induced Gene Expression Profiles for Disease-Associated Tissues.

The use of omics data, including gene expression profiles, has recently gained increasing attention in drug discovery. Omics-based drug searches and designs are often based on the correlations between chemically induced and disease-induced gene expression profiles; however, the cell specificity has not been considered. In this study, we designed a novel computational method for drug search and design using cell-specific correlations between drugs and diseases. A data completion technique allowed the characterization of cell-specific gene expression patterns in diseased cells. This proposed method was applied to search for drug candidates and generate new chemical structures for gastric cancer and atopic dermatitis. The results of drug search demonstrated that compounds with diverse chemical structures were detected and were associated with target diseases at the molecular pathway levels. The results of drug design also demonstrated that newly generated compounds were reasonable in terms of the reproducibility of registered drugs. The proposed method is expected to be useful for omics-based drug discovery.