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Title: Iterative derivation of effective potentials to sample the conformational space of proteins at atomistic scale

Abstract

The current capacity of computers makes it possible to perform simulations of small systems with portable, explicit-solvent potentials achieving high degree of accuracy. However, simplified models must be employed to exploit the behavior of large systems or to perform systematic scans of smaller systems. While powerful algorithms are available to facilitate the sampling of the conformational space, successful applications of such models are hindered by the availability of simple enough potentials able to satisfactorily reproduce known properties of the system. We develop an interatomic potential to account for a number of properties of proteins in a computationally economic way. The potential is defined within an all-atom, implicit solvent model by contact functions between the different atom types. The associated numerical values can be optimized by an iterative Monte Carlo scheme on any available experimental data, provided that they are expressible as thermal averages of some conformational properties. We test this model on three different proteins, for which we also perform a scan of all possible point mutations with explicit conformational sampling. The resulting models, optimized solely on a subset of native distances, not only reproduce the native conformations within a few Angstroms from the experimental ones, but show the cooperativemore » transition between native and denatured state and correctly predict the measured free-energy changes associated with point mutations. Moreover, differently from other structure-based models, our method leaves a residual degree of frustration, which is known to be present in protein molecules.« less

Authors:
 [1];  [2];  [3];  [4]
  1. Department of Physics, Università degli Studi di Milano, via Celoria 16, 20133 Milano (Italy)
  2. Department of Chemistry, Università degli Studi di Milano, via Venezian 21, 20133 Milano (Italy)
  3. Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW (United Kingdom)
  4. Department of Physics, Università degli Studi di Milano and INFN, via Celoria 16, 20133 Milano (Italy)
Publication Date:
OSTI Identifier:
22254860
Resource Type:
Journal Article
Journal Name:
Journal of Chemical Physics
Additional Journal Information:
Journal Volume: 140; Journal Issue: 19; Other Information: (c) 2014 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0021-9606
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY; ACCURACY; FREE ENERGY; ITERATIVE METHODS; MONTE CARLO METHOD; POTENTIALS; PROTEINS; SIMULATION; SOLVENTS

Citation Formats

Capelli, Riccardo, Paissoni, Cristina, Biomolecular NMR Unit, S. Raffaele Scientific Institute, via Olgettina 58, 20132 Milano, Sormanni, Pietro, and Tiana, Guido. Iterative derivation of effective potentials to sample the conformational space of proteins at atomistic scale. United States: N. p., 2014. Web. doi:10.1063/1.4876219.
Capelli, Riccardo, Paissoni, Cristina, Biomolecular NMR Unit, S. Raffaele Scientific Institute, via Olgettina 58, 20132 Milano, Sormanni, Pietro, & Tiana, Guido. Iterative derivation of effective potentials to sample the conformational space of proteins at atomistic scale. United States. https://doi.org/10.1063/1.4876219
Capelli, Riccardo, Paissoni, Cristina, Biomolecular NMR Unit, S. Raffaele Scientific Institute, via Olgettina 58, 20132 Milano, Sormanni, Pietro, and Tiana, Guido. 2014. "Iterative derivation of effective potentials to sample the conformational space of proteins at atomistic scale". United States. https://doi.org/10.1063/1.4876219.
@article{osti_22254860,
title = {Iterative derivation of effective potentials to sample the conformational space of proteins at atomistic scale},
author = {Capelli, Riccardo and Paissoni, Cristina and Biomolecular NMR Unit, S. Raffaele Scientific Institute, via Olgettina 58, 20132 Milano and Sormanni, Pietro and Tiana, Guido},
abstractNote = {The current capacity of computers makes it possible to perform simulations of small systems with portable, explicit-solvent potentials achieving high degree of accuracy. However, simplified models must be employed to exploit the behavior of large systems or to perform systematic scans of smaller systems. While powerful algorithms are available to facilitate the sampling of the conformational space, successful applications of such models are hindered by the availability of simple enough potentials able to satisfactorily reproduce known properties of the system. We develop an interatomic potential to account for a number of properties of proteins in a computationally economic way. The potential is defined within an all-atom, implicit solvent model by contact functions between the different atom types. The associated numerical values can be optimized by an iterative Monte Carlo scheme on any available experimental data, provided that they are expressible as thermal averages of some conformational properties. We test this model on three different proteins, for which we also perform a scan of all possible point mutations with explicit conformational sampling. The resulting models, optimized solely on a subset of native distances, not only reproduce the native conformations within a few Angstroms from the experimental ones, but show the cooperative transition between native and denatured state and correctly predict the measured free-energy changes associated with point mutations. Moreover, differently from other structure-based models, our method leaves a residual degree of frustration, which is known to be present in protein molecules.},
doi = {10.1063/1.4876219},
url = {https://www.osti.gov/biblio/22254860}, journal = {Journal of Chemical Physics},
issn = {0021-9606},
number = 19,
volume = 140,
place = {United States},
year = {Wed May 21 00:00:00 EDT 2014},
month = {Wed May 21 00:00:00 EDT 2014}
}