Intellectual Merit - In this post-genomic era, systems biology has provided a rational and quantitative approach to unify complex cellular interactions and comprehend modular outcomes that determine different cell fates. However, subtle differences in the molecular context of the intracellular environment (e.g., differences in phosphorylation states, between homologous proteins, isoforms, or mutants) nevertheless translate into crucial differences in the manifestations of the emergent signaling response, thereby representing a huge challenge in formulating quantitative systems-level models that truly capture such variations across distinctive cell-lines. In the context of ErbB family receptor-mediated signaling, the molecular context shapes the finer controls exercised by the cell and a quantitative description of this level of control has been a challenge. This project on molecular systems biology is based on utilizing standard and established biomolecular simulations (molecular dynamics and free energy computations) of the ErbB family receptors by leveraging the anchors (crystal structures) provided by recent progress in structural biology and introducing molecular resolution to the systems biology of ErbB-mediated signaling. The expected outcome of this project is to quantitatively and predictively describe how differences in the molecular architecture of ErbB family receptor-mediated interactions influence early signaling events and verify key predictions through collaborative cell-biology experiments performed in the laboratory. The results from this work will directly complement prior efforts in modeling differential signaling in the ErbB pathway, and together, one can expect to gain an integrated multiscale understanding of the Molecular Systems Biology of ErbB signaling.
Broader Impact - This project is expected to benefit many novel applications of multiscale systems biology and nanobiotechnology. In particular, the study of ErbB signaling at the level of receptor activation will provide a direct route to discern signaling triggered by molecular perturbations which can impact our understanding of the link between cellular proliferative signals and higher order functions such as tissue-growth homeostasis, cardiac and neuronal development. Complementing the interdisciplinary research program, the educational and outreach programs are constituted by rigorous and visionary research training for undergraduate students in engineering and biology. To achieve broader impact in complementing the undergraduate research experience, a three dimensional stereo environment for visualizing biomolecular structure and animations is established and utilized for the instruction of molecular modeling and simulation techniques at the undergraduate and graduate levels.
Defining a Role for Structural Systems Biology in Oncology Recent clinical success with many of the cancer drugs known as targeted small-molecule inhibitors in clinical use underscore both the promise and the challenges of personalized cancer medicine. Numerous gene mutations in the class of molecules called kinases, which largely regulate cell growth and which these drugs target, have been identified. As tumor sequencing studies on patients advance, it is becoming increasingly clear that efficacy of the drugs and the treatment outcome in patients both depend on the mutational landscape. Quantifying the mapping between the mutational landscape in these proteins and the response of the patient to a drug is the ultimately clinical frontier in oncology. Intellectual Merit: In this project we have been able to lay the foundations of quantitatively modeling this process at the molecular level of protein-drug interaction as well as the cellular level on how the molecular interactions can impact cell-fate decisions in normal and cancer cells. We have established algorithms and modeling techniques for this process through multiscale modeling, which we term structural systems biology. Using our approach, we incorporate the molecular/mutational context in the network analysis, thereby developing systems biology models with molecular specificity. Broader Impact: We have applied this approach to the study of a class of kinases implicated in non-small-cell lung cancer, breast cancer, colon cancer, prostate cancer, and brain tumors. We intend to further develop these computational methods and validate them in the cancer setting. These protocols will be important in silico tools for guiding personalized cancer therapy. The project has also resulted in the training of 10 scholars at the Doctoral and Postdoctoral level and four students at the Undergraduate level. In addition, several undergraduate, graduate, and high-school students benefitted from dissemination of methods and results of the project through elective course and workshops. This project was instrumental in fostering a transatlantic collaboration between scientists and oncologists in the USA and the European Union member countries. It has also contributed to a multiagency consortium on multiscale modeling involving NSF, NIH, NASA, DOE, and DOD.
