Database-derived potentials dependent on protein size for in silico folding and design

Biophysical Journal
Yves DehouckM J Rooman

Abstract

Knowledge-based potentials are widely used in simulations of protein folding, structure prediction, and protein design. Their advantages include limited computational requirements and the ability to deal with low-resolution protein models compatible with long-scale simulations. Their drawbacks comprehend their dependence on specific features of the dataset from which they are derived, such as the size of the proteins it contains, and their physical meaning is still a subject of debate. We address these issues by probing the theoretical validity of these potentials as mean-force potentials that take the solvent implicitly into account and involve entropic contributions due to atomic degrees of freedom and solvation. The dependence on the size of the system is checked on distance-dependent amino acid pair potentials, derived from six protein structure sets containing proteins of increasing length N. For large inter-residue distances, they are found to display the theoretically predicted 1/N behavior weighted by a factor depending on the boundaries and the compressibility of the system. For short distances, different trends are observed according to the nature of the residue pairs and their ability to form, for example, electrosta...Continue Reading

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Citations

Apr 29, 2008·Biophysical Journal·A SzilágyiP Závodszky
Mar 15, 2006·Biophysical Journal·Y DehouckM Rooman
Oct 5, 2016·Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences·Fabrizio Pucci, Marianne Rooman
Aug 21, 2019·Scientific Reports·Mame Ndew MbayeMarianne Rooman
Dec 29, 2007·Journal of Chemical Information and Modeling·Benjamin FolchYves Dehouck

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