title: Predicting Drug Combination Index and Simulating the Network-Regulation Dynamics by Mathematical Modeling of Drug-Targeted EGFR-ERK Signaling Pathway.
abstract: Synergistic drug combinations enable enhanced therapeutics. Their discovery typically involves the measurement and assessment of drug combination index (CI), which can be facilitated by the development and applications of in-silico CI predictive tools. In this work, we developed and tested the ability of a mathematical model of drug-targeted EGFR-ERK pathway in predicting CIs and in analyzing multiple synergistic drug combinations against observations. Our mathematical model was validated against the literature reported signaling, drug response dynamics, and EGFR-MEK drug combination effect. The predicted CIs and combination therapeutic effects of the EGFR-BRaf, BRaf-MEK, FTI-MEK, and FTI-BRaf inhibitor combinations showed consistent synergism. Our results suggest that existing pathway models may be potentially extended for developing drug-targeted pathway models to predict drug combination CI values, isobolograms, and drug-response surfaces as well as to analyze the dynamics of individual and combinations of drugs. With our model, the efficacy of potential drug combinations can be predicted. Our method complements the developed in-silico methods (e.g. the chemogenomic profile and the statistically-inferenced network models) by predicting drug combination effects from the perspectives of pathway dynamics using experimental or validated molecular kinetic constants, thereby facilitating the collective prediction of drug combination effects in diverse ranges of disease systems.
authors.affiliation: The Ministry-Province Jointly Constructed Base for State Key Lab and Shenzhen Technology and Engineering Lab for Personalized Cancer Diagnostics and Therapeutics Tsinghua University Shenzhen Graduate School, and Shenzhen Kivita Innovative Drug Discovery Institute, Shenzhen, 518055, P.R. China.|Institute of Molecular Biology (IMB), Ackermannweg 4, 55128 Mainz, Germany.|Department of Pharmacy, and Center for Computational Science and Engineering, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, 117543 Singapore.
authors.forename: Lu
authors.initials: L
authors.lastname: Huang
authors.affiliation: The Ministry-Province Jointly Constructed Base for State Key Lab and Shenzhen Technology and Engineering Lab for Personalized Cancer Diagnostics and Therapeutics Tsinghua University Shenzhen Graduate School, and Shenzhen Kivita Innovative Drug Discovery Institute, Shenzhen, 518055, P.R. China.
authors.forename: Yuyang
authors.initials: Y
authors.lastname: Jiang
authors.affiliation: Department of Pharmacy, and Center for Computational Science and Engineering, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, 117543 Singapore.|State Key Laboratory of Biotherapy, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China.
authors.forename: Yuzong
authors.initials: Y
authors.lastname: Chen
mesh_terms: D000970:Antineoplastic Agents / Q000494:pharmacology* / Q000627:therapeutic use; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use; D045744:Cell Line, Tumor; D049109:Cell Proliferation / Q000187:drug effects; D003198:Computer Simulation; D066246:ErbB Receptors / Q000378:metabolism*; D048049:Extracellular Signal-Regulated MAP Kinases / Q000378:metabolism*; D006801:Humans; D008962:Models, Theoretical; D047428:Protein Kinase Inhibitors / Q000494:pharmacology* / Q000627:therapeutic use; D048493:Proto-Oncogene Proteins B-raf / Q000378:metabolism; D015398:Signal Transduction / Q000187:drug effects*
chemical_list: D000970:Antineoplastic Agents; D047428:Protein Kinase Inhibitors; D066246:ErbB Receptors; D048493:Proto-Oncogene Proteins B-raf; D048049:Extracellular Signal-Regulated MAP Kinases