ORIGINAL PAPER Nanomechanics of β-rich proteins related to neuronal disorders studied by AFM, all-atom and coarse-grained MD methods

Abstract Computer simulations of protein unfolding sub-stantially help to interpret force-extension curves measured in single-molecule atomic force microscope (AFM) experi-ments. Standard all-atom (AA) molecular dynamics simula-tions (MD) give a good qualitative mechanical unfolding picture but predict values too large for the maximum AFM forces with the common pulling speeds adopted here. Fine tuned coarse-grain MD computations (CG MD) offer quanti-tative agreement with experimental forces. In this paper we address an important methodological aspect of MDmodeling, namely the impact of numerical noise generated by random assignments of bead velocities on maximum forces (Fmax) calculated within the CG MD approach. Distributions of CG forces from 2000MD runs for several model proteins rich inβ structures and having folds with increasing complexity are presented. It is shown that Fmax have nearly Gaussian distri-butions and that values of Fmax for each of those β-structures may vary from 93.2±28.9 pN (neurexin) to 198.3±25.2 pN (fibronectin). The CG unfolding spectra are compared with AA steeredMDdata and with results of our AFM experiments for modules present in contactin, fibronectin and neurexin. The stability of these proteins is critical for the proper func-tioning of neuronal synaptic clefts. Our results confirm that CG modeling of a single molecule unfolding is a good auxil-iary tool in nanomechanics but large sets of data have to be collected before reliable comparisons of protein mechanical stabilities are made