Mutation-induced protein interaction kinetics changes affect apoptotic network dynamic properties and facilitate oncogenesis

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 112; no. 30; pp. E4046 - E4054
• Main Authors: Zhao, Linjie, Tanlin Sun, Jianfeng Pei, Qi Ouyang
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 28.07.2015; National Acad Sciences
• Series: PNAS Plus
• Subjects: antineoplastic agents; Antineoplastic Agents - chemistry; Apoptosis; Apoptosis Regulatory Proteins - metabolism; Biological Sciences; Cancer; carcinogenesis; Carcinogenesis - genetics; Cell Transformation, Neoplastic - genetics; Cluster Analysis; Correlation analysis; dynamic bifurcation; genotype; Humans; Kinetics; Mitochondria - metabolism; Models, Theoretical; molecular dynamics; Molecular Dynamics Simulation; Mutation; mutation enrichment; mutation-induced oncogenesis; neoplasms; Neoplasms - genetics; Neoplasms - metabolism; parameter sensitivity analysis; phenotype; PNAS Plus; Polymorphism, Single Nucleotide; protein interaction kinetics; Protein Interaction Mapping; Protein Multimerization; Protein Structure, Tertiary; protein-protein interactions; Proteins; Simulation; somatic mutation; Thermodynamics; dynamic bifurcation; mutation-induced oncogenesis; parameter sensitivity analysis; mutation enrichment; protein interaction kinetics
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.1502126112

It has been a consensus in cancer research that cancer is a disease caused primarily by genomic alterations, especially somatic mutations. However, the mechanism of mutation-induced oncogenesis is not fully understood. Here, we used the mitochondrial apoptotic pathway as a case study and performed a systematic analysis of integrating pathway dynamics with protein interaction kinetics to quantitatively investigate the causal molecular mechanism of mutation-induced oncogenesis. A mathematical model of the regulatory network was constructed to establish the functional role of dynamic bifurcation in the apoptotic process. The oncogenic mutation enrichment of each of the protein functional domains involved was found strongly correlated with the parameter sensitivity of the bifurcation point. We further dissected the causal mechanism underlying this correlation by evaluating the mutational influence on protein interaction kinetics using molecular dynamics simulation. We analyzed 29 matched mutant–wild-type and 16 matched SNP—wild-type protein systems. We found that the binding kinetics changes reflected by the changes of free energy changes induced by protein interaction mutations, which induce variations in the sensitive parameters of the bifurcation point, were a major cause of apoptosis pathway dysfunction, and mutations involved in sensitive interaction domains show high oncogenic potential. Our analysis provided a molecular basis for connecting protein mutations, protein interaction kinetics, network dynamics properties, and physiological function of a regulatory network. These insights provide a framework for coupling mutation genotype to tumorigenesis phenotype and help elucidate the logic of cancer initiation. Cancer is highly correlated with somatic mutations. Understanding how mutation induces oncogenesis is an important task in cancer research. We proposed a strategy that combined network-based dynamics modeling with structural-based mutation analysis and molecular dynamics simulation to map cancer-related mutations to network dynamics changes via protein–protein interaction kinetics. This approach identifies the oncogenic role of mutations and subsequently determines the causal mechanism of mutation-induced oncogenesis. This work provides a framework for coupling mutation genotype to tumorigenesis phenotype. It is also a step toward seeking more effective anticancer drug targets in cellular pathways.