Cause-effect relationships in medicine: a protein network perspective. Trends Pharmacol Sci
Current target-based drug discovery platforms are not able to predict drug efficacy and the full spectrum of drug effects in organisms. Hence, many experimental drugs do not survive the lengthy and costly process of drug development. Understanding how drugs affect cellular network structures and how the resulting signals are translated into drug effects is extremely important for the discovery of new medicines. This requires a greater understanding of cause-effect relationships at the organism, organ, tissue, cellular, and molecular level. There is a growing recognition that this information must be integrated into discovery paradigms, but a 'road map' for obtaining and integrating information about heterogeneous networks into drug-discovery platforms currently does not exist. This review explores recent network-centered approaches developed to investigate the genesis of medicine and disease effects, specifically highlighting protein-protein interaction network models and their use in cause-effect analyses in medicine.
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.