SYSTEMS BIOLOGY APPROACH TO COMBINATORIAL DRUG TARGETING

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. In silico models of signal transduction pathways have been highly successful in describing, quantitatively, how complex protein networks govern overall cell function. We propose to analyze a recently developed model of oncogenesis in the Mitogen Activated Protein Kinase (MAPK) signal transduction pathway, to understand how drugs targeting the MAPK pathway can act synergistically to enhance efficacy. We have already developed quantitative ranking of putative targets that inhibit the transformation process where each drug acts alone. The inhibitor, a virtual drug, is constructed by specifying its parameters: initial concentration and binding affinity kd. Many of the targets found by this analysis have inhibitors that are currently under investigation. In addition, several novel targets not previously investigated have been found. Of the thirteen targets, Ras, Guanine Exchange Factor (GEF), and Raf, show the highest potential. In addition, the analysis finds that certain calcium blockers may have much potential as anti-tumor agents, functioning at much lower concentrations but requiring higher specificity. To expand this work to investigate multiple targets requires extensive computational time not available in our lab. Investigating, dose-dose response curves has a strong experimental analogue and the extension of systems biology to investigate such responses in parallel has implications in both the pharmaceutical industry and cancer research. A starter grant for a small amount of CPU time at PSC would greatly enhance the time needed to do this analysis.