title: Relating Chemical Structure to Cellular Response: An Integrative Analysis of Gene Expression, Bioactivity, and Structural Data Across 11,000 Compounds.
abstract: A central premise in systems pharmacology is that structurally similar compounds have similar cellular responses; however, this principle often does not hold. One of the most widely used measures of cellular response is gene expression. By integrating gene expression data from Library of Integrated Network-based Cellular Signatures (LINCS) with chemical structure and bioactivity data from PubChem, we performed a large-scale correlation analysis of chemical structures and gene expression profiles of over 11,000 compounds taking into account confounding factors such as biological conditions (e.g., cell line, dose) and bioactivities. We found that structurally similar compounds do indeed yield similar gene expression profiles. There is an ∼20% chance that two structurally similar compounds (Tanimoto Coefficient ≥ 0.85) share significantly similar gene expression profiles. Regardless of structural similarity, two compounds tend to share similar gene expression profiles in a cell line when they are administrated at a higher dose or when the cell line is sensitive to both compounds.
authors.affiliation: Institute for Computational Health Sciences, University of California San Francisco, San Francisco, California, USA.
authors.forename: B
authors.initials: B
authors.lastname: Chen
authors.affiliation: Biomedical Informatics Training Program, Stanford University School of Medicine Stanford, California, USA.
authors.forename: P
authors.initials: P
authors.lastname: Greenside
authors.affiliation: Institute for Computational Health Sciences, University of California San Francisco, San Francisco, California, USA.
authors.forename: H
authors.initials: H
authors.lastname: Paik
authors.affiliation: Institute for Computational Health Sciences, University of California San Francisco, San Francisco, California, USA.
authors.forename: M
authors.initials: M
authors.lastname: Sirota
authors.affiliation: Institute for Computational Health Sciences, University of California San Francisco, San Francisco, California, USA.
authors.forename: D
authors.initials: D
authors.lastname: Hadley
authors.affiliation: Institute for Computational Health Sciences, University of California San Francisco, San Francisco, California, USA.
authors.forename: A J
authors.initials: AJ
authors.lastname: Butte