Diphtheria toxin translocation T-domain is a ten alpha-helical protein at neutral pH. T-domain undergoes major conformational changes upon decrease of pH, which brings the protein from its initial soluble to a final trans-membrane inserted state. Initial studies have indicated the pH-dependent formation of a membrane competent state of T-domain in solution, which was suggested to undergo conformational changes in preparation for subsequent T-domain membrane binding. Recently, we have characterized the formation of membrane competent state structures at low pH by a combined approach of multi microsecond long molecular dynamics (MD) simulations and spectroscopy methods.1In this work, we focus on the generation of partially unfolded ensembles of a low pH T-domain model in explicit solvent using an efficient enhanced sampling method. Accelerated molecular dynamics (aMD) is an enhancing sampling method used to generate conformations and to explore the free energy landscape of proteins in explicit solvent. Its success resides on its ability to reduce energy barriers in the dihedral and the total potential energy space. However, aMD simulations of large proteins can generate large fluctuations of the dihedral and total potential energy with little conformational changes in the protein structure. To facilitate the conformational sampling of large proteins in explicit solvent, we propose a modification of this enhanced sampling method by only reducing the energy barrier in the direct electrostatic space of solute-solute interactions. Moreover, reweighting calculations can be performed to recover the Boltzmann-weighted ensemble. Based on simulations of low pH destabilized T-domain structures, we show that this modified method is a more efficient enhanced sampling method than multiple standard aMD simulations and microsecond long unbiased MD simulations.1. Kurnikov, I. et al. J. Mol. Biol. 2013,  425, 2752-2764

Accelerated molecular dynamics of low pH destabilized diphtheria toxin translocation T-domain

248th National Meeting (2014)

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