Abstract

The principles governing protein folding stand as one of the biggest challenges of Biophysics. Modeling the global stability of proteins and predicting their tertiary structure are hard tasks, due in part to the variety and large number of forces involved and the difficulties to describe them with sufficient accuracy. We have developed a fast, physics-based empirical potential, intended to be used in global structure prediction methods. This model considers four main contributions: Two entropic factors, the hydrophobic effect and configurational entropy, and two terms resulting from a decomposition of close-packing interactions, namely the balance of the dispersive interactions of folded and unfolded states and electrostatic interactions between residues. The parameters of the model were fixed from a protein data set whose unfolding free energy has been measured at the “standard” experimental conditions proposed by Maxwell et al. (2005) and a large data set of 1151 monomeric proteins obtained from the PDB. A blind test with proteins taken from ProTherm database, at similar experimental conditions, was carried out. We found a good correlation with the test data set, proving the effectiveness of our model for predicting protein folding free energies in considered standard conditions. Such a prediction compares favorably against estimations made with FoldX’s function and the force field GROMOS96. This model constitutes a valuable tool for the fast evaluation of protein structure stability in 3D structure prediction methods.

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