Aims: Efficient prediction of combinatorial drugs for complex diseases based on bioinformatics algorithms related to the identification of epistasis gene pairs.
Scientific rationale: Medical genetics reveals the genotype-phenotype links in diseases and therefore provides critical information for drug discovery and drug repositioning. Recently, genome wide association studies (GWAS) have identified a large number of disease-associated genes that are efficient sources of drug targets. Recent studies show that targeting multiple disease-associated genes has greater therapeutic potential, and genes often exert functions through molecular interactions. In addition, the therapeutic potential of chemical agents depends largely on the genetic links between targets and diseases. The factors that can consolidate these links will enhance an agent’s medicinal potential. Thus, it is reasonable to speculate that targeting interacting disease-related genes (termed epistatic disease genes) may bring synergistic effects for disease control, and combinatorial drugs aimed at epistatic disease genes will have higher medicinal potential.
Project duration: Complete original data collection, integration and standardization processing: 6 months; identification of epistatic genes: 6 to 10 months; combinatorial drug prediction: 6 months; results integration, report writing: 1 year. Total: 2 to 3 years.
Public health impact: The implementation of this project provides new ideas for combinatorial drug research, which is helpful for the treatment of complex diseases.
