Computational approaches to designing extracellular matrix mimetics


A major challenge in neural tissue engineering and regenerative medicine is one of tissue construction: what biomaterial, in terms of chemical composition and physical properties, might best mimic the native extracellular matrix (ECM) that houses neurons, glia, neural stem cells (NSCs), and other cells? Engineered biopolymers afford an opportunity to systematically control both biological functionality and the structural/mechanical properties of the resulting ECM mimetic, thus enabling one to modify the behavior of encapsulated cells.

Progress in biomaterials discovery has been limited by a lack of high-resolution data about the structural dynamics of the underlying polymeric network. The properties of any material stem from the three-dimensional (3D) structures and dynamics of its molecular constituents—from the level of individual proteins to their higher–order assembly into matrices. These structural and dynamical properties, in turn, are deeply linked to the patterns of intra- and inter-molecular interactions that are thermodynamically accessible, and substantially populated, under a given set of experimental conditions. The structural and thermodynamic properties of a designed fusion protein can be quantitatively characterized via experimental means (e.g., X-ray scattering), but systematically doing so on the scale of many dozens or even hundreds of designs would be prohibitively laborious and resource-intensive. Moreover, such approaches do not, in general, provide the atomic-resolution structural and dynamical information to iteratively refine and systematically improve protein designs.

Using classical, all-atom MD simulations we have examined the molecular behavior of our LG-ELP design (Figure a & b) near its putative phase transition, as well as the temperature-dependent conformational and structural dynamics leading up to the LCST. These simulations supply picosecond-resolved, atomically-detailed information on discrete structural and functional states for our protein, on the overall timescale of ca. 100 nsec. Thus, we can comprehensively analyze the molecular mechanism of the presumed LCST transition of our fusion protein, and also obtain an a priori view of the structural properties of this design, before dedicating experimental resources to the synthesis and characterization of a novel biopolymer with unknown LCST behavior.