Crowding and Complexity: Simulation Studies of Biologically Realistic Membrane Models

Membranes surround all cells, controlling access and exchange between a cell and its environment. Membranes are crowded environments, composed of up to ca. 50% protein by mass. This crowding may result in the formation of membrane protein clusters, which will have altered physical and biological properties compared to the same membrane proteins in isolation. The use of high performance computing provides a 'computational microscope' which allows simulations of the dynamic behaviour of crowded membrane systems. We will use such advanced simulations to understand the organization and dynamics of proteins and lipids in biologically realistic models of crowded and complex membrane systems. The resultant membrane models and computer simulation methodologies will be used to explore two key applications of importance to industry: (i) receptor/ligand interactions and drug efficacy, of relevance to the pharmaceutical industry; and (ii) crowding effects in membrane-based synthetic 'factories', of relevance to the development of new biotechnologies for synthesis of drugs and other complex chemicals.

Cell membranes are crowded environments, composed of up to ca. 50% protein by mass corresponding to a membrane area fraction (theta) of ca. 25% or more occupied by proteins. In addition to crowding per se, the spatial and compositional complexities of membranes may result in the formation of membrane protein nano-clusters. However, detailed molecular simulations of crowded membrane systems have been limited. Given advances in high performance computing, it is timely to extend the scale and complexity of molecular simulations in order to understand the organization and dynamics of proteins and lipids in biologically realistic models of crowded and complex membrane systems.

The overall aim of this proposal is to characterise dynamic properties of crowded and complex biomembranes using multiscale molecular dynamics (MD) simulations. In particular we will examine these properties in terms of their implications for our understanding of drug/receptor interactions, and of membranes for use in synthetic metabolons. We will building upon our preliminary studies to develop biologically realistic membrane models composed of complex mixtures of lipids. These complex lipid bilayers will be combined with multiple membrane proteins to yield crowded-complex membrane systems. Quantification of protein-protein and protein-lipid-protein interactions in these crowded systems will yield free energy landscapes for biologically realistic membranes. These free energy landscapes will be used to parameterize ultra-coarse-grained models based on hybrid Brownian Dynamics/Monte Carlo approaches which will allow us to simulate emergent properties of very large (1000s of proteins) planar and vesicular membrane systems. The resultant membrane models and simulation methodologies will be used to explore two key applications: (i) receptor/ligand interactions and drug efficacy; and (ii) crowding effects in membrane-based synthetic metabolons.

Who will benefit from this research?
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The major potential industrial impacts are likely to be in the pharmaceutical and biotechnology sectors, both of which have interests in membrane proteins, the former in receptors (GPCRs, ion channels, etc.) for many drugs, and the latter in the context of developing membrane-based synthetic metabolons for novel compound syntheses.

How will they benefit from this research?
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1. From a pharmaceutical perspective, our studies will yield fundamental insights, revealing the nature of an 'extended pharmacophore' for hydrophobic drugs as provided by the (local) lipid environment of (crowded) membrane receptors.
2. From a biotechnology perspective, a more general impact will be to increase the general expertise and awareness of the role of simulations in studying membrane proteins as components of synthetic biology systems.
3. There will also be a significant impact in terms of providing trained researchers in modelling and simulation of membrane systems. (I note that a number of my former graduate students and postdocs are currently researchers in the pharmaceutical and biotechnology industries.)