Exploration of MOMP at the membrane level using molecular, coarse-grain, and continuum descriptions of the signaling network.
The Bcl-2 family of proteins exhibit a rich interplay between activators, inhibitors, and sensitizers that leads to eventual mitochondrial outer membrane permeabilization (MOMP). Despite great advances in our understanding of the mechanisms that lead to MOMP, we still are faced with gaps in our knowledge of the protein-protein interactions at the molecular level that lead to MOMP. In this work we combine molecular simulation at the atomic and coarse-grain levels of description as well as continuum mass-action mechanistic modeling to better understand the MOMP regulation network.
Studies of multi-pathway representations of cell signaling to understand the balance of life and death in healthy and cancer cells.
Multiple pathways have been described for cellular functions such as proliferation, growth, and programmed cell death. These pathways have been studied in isolation, both experimentally and theoretically. Recent advances in experiments, however, have started to yield information about multiple pathways and how they compete for different outcomes. We are particularly interested in the life and death balance in healthy cells and how these pathways become dysregulated in cancer cells. This work involves experimental collaborations to understand how treatments with single or combinations of drugs affect the outcome of healthy as well as cancer phenotypes.
Toward a better description of cellular environments.
The common practice in systems biology modeling is to use mass-action approximations, suitable for well-mixed systems, to simulate biochemical reactions in cellular environments. However, due to confined spaces, low number of molecules, compartmentalization, etc the cell is far from a well-mixed system. In addition most studies employ simulations of “average cells” to represent a multitude of cells within a tissue. We are currently investigating addressing two aspects of this problem, at the interface of particle-continuum description and at the interface of single-multiple cell descriptions. For this goal we develop toos for the PySB programming framework (www.pysb.org) which enable us to express biological concepts in a programming environment. This project involves the use of techniques such as statistical mechanics, molecular simulation, mass-action kinetics, and fluid dynamics as applied to cellular systems.
From functional genomics to cell-signaling dynamics.
The advent of genomics has resulted in a plethora of data about gene expression, functions, and interactions. However, even this data still leaves gaps about how the protein products resulting from genes interact and drive the cell toward different phenotypes. In this work, in collaboration with Prof. Ian Overton (U of Edinburgh / MRC), we aim to bridge the gap between functional genomics and cellular biochemical signaling. The goal of this work has an ambitious translational component by employing the developed simulation tools to explain observed phenotypes from genotypes and predict the response of cells to drug treatments.