Cause-effect relationships in medicine: a protein network perspective.
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.
Fliri
Anton F
AF
SystaMedic Incorporated, 1084 Shennecossett Road, Groton, CT 06340, USA.
Loging
William T
WT
Volkmann
Robert A
RA
D054316:Biomarkers, Pharmacological / Q000378:metabolism; D004194:Disease; D015195:Drug Design; D055808:Drug Discovery; D004359:Drug Therapy, Combination; D053263:Gene Regulatory Networks; D006801:Humans; D053858:Metabolic Networks and Pathways; D058990:Molecular Targeted Therapy; D004364:Pharmaceutical Preparations / Q000378:metabolism*; D025941:Protein Interaction Mapping; D011506:Proteins / Q000378:metabolism* / Q000627:therapeutic use*; D013329:Structure-Activity Relationship; D016896:Treatment Outcome
D054316:Biomarkers, Pharmacological; D004364:Pharmaceutical Preparations; D011506:Proteins