MechStiff: A New Tool for Evaluating Stress-Induced Dynamics and Application to Cell Adhesion Proteins

Based on recent findings, there is growing evidence that many biological systems in the brain integrate biochemical information with mechanical signals making critical decisions about cell differentiation, synaptic regulation, axonal growth, neuronal migration or proliferation. These events seem to be controlled by the mechanical behavior of intervening proteins in addition to their well-studied biochemistry; and therefore to obtain a quantitative understanding of the mechanical events implicated in neurosignaling events is becoming increasingly important. We have developed to this aim the MechStiff module that we implemented in ProDy API (1), based on an earlier comparison (2) of anisotropic network model predictions with single molecule atomic force microscopy (smAFM) data. We further used MechStiff module to evaluate the effective resistance of individual domains in the neuronal adhesion protein, contactin, to uniaxial tension. Contactins play an important role in maintaining the mechanical integrity and signaling properties of chemical synapses in the brain. To validate the predictions on the the molecular-level stress-strain behavior of contactin, we compared MechStiff predictions with smAFM measurements as well as results from steered molecular dynamics simulations. The multiscale approach combining anisotropic network model with molecular simulations emerges as a useful tool for interpreting experimental data and characterizing contactin nanomechanics. It also helps reveal the stress-induced conformational changes being accommodated by cell adhesion proteins and can be readily extended to elucidating the stress-induced dynamics of multicomponent or modular proteins.1.Bakan, A., A. Dutta, W. Mao, Y. Liu, C. Chennubhotla, T. R. Lezon, and I. Bahar. 2014. Evol and ProDy for bridging protein sequence evolution and structural dynamics. Bioinformatics 30:2681-2683.2.Eyal, E., and I. Bahar. 2008. Toward a molecular understanding of the anisotropic response of proteins to external forces: insights from elastic network models. Biophys. J. 94:3424-3435.