Fig2.

Computational approach to drug discovery and drug repurposing: Disease state can be either acquired (disease or substance of abuse changes gene networks and these changes drive disease) or predisposed (genetic variants cause disruptions in gene networks). The goal of in silico gene mapping is to integrate the targets (gene networks) of disease and drugs to find a drug (or combination of drugs) that affect similar targets as the disease. Drugs that oppose the disease-state’s molecular disruption (many targets) are chosen as candidate compounds to ameliorate disease phenotype. There are 3 steps to go from gene expression datasets to candidate compounds: (1) generate an input genomic signature or network. Shown is a gene-gene coexpression network of genes related to a disease state: nodes = genes, edges = gene-gene expression correlation, yellow = up-regulated genes, blue = down-regulated genes), (2) compare the disease signature to those induced by drugs to identify drugs that would reverse the disease signature. Shown are the effects of 3 different drugs in the reference database (e.g., LINCS-L1000) on the disease-related genes that served as the input, (3) prioritize candidate compounds for in vivo testing. The blue drug that received a perfect negative score would be prioritized since it down-regulated the genes that were up-regulated in the disease state and up-regulated the genes that were down-regulated in the disease state. The yellow drug would be predicted to mimic or worsen the disease state. Had the input been a desirable biological state (e.g., the gene expression profile of patients with AUD who had prolonged recovery vs those who relapsed quickly after ceasing alcohol consumption), then the yellow drug would be prioritized since it is predicted to mimic the beneficial biological state. Capsule images from http://smart.servier.com/category/general-items/drugs-and-treatments/. Servier Medical Art by Servier is licensed under CC BY 3.0 (https://creativecommons.org/licenses/by/3.0/). AUD = alcohol use disorder.