title: Equilibrium simulations of proteins using molecular fragment replacement and NMR chemical shifts.
abstract: Methods of protein structure determination based on NMR chemical shifts are becoming increasingly common. The most widely used approaches adopt the molecular fragment replacement strategy, in which structural fragments are repeatedly reassembled into different complete conformations in molecular simulations. Although these approaches are effective in generating individual structures consistent with the chemical shift data, they do not enable the sampling of the conformational space of proteins with correct statistical weights. Here, we present a method of molecular fragment replacement that makes it possible to perform equilibrium simulations of proteins, and hence to determine their free energy landscapes. This strategy is based on the encoding of the chemical shift information in a probabilistic model in Markov chain Monte Carlo simulations. First, we demonstrate that with this approach it is possible to fold proteins to their native states starting from extended structures. Second, we show that the method satisfies the detailed balance condition and hence it can be used to carry out an equilibrium sampling from the Boltzmann distribution corresponding to the force field used in the simulations. Third, by comparing the results of simulations carried out with and without chemical shift restraints we describe quantitatively the effects that these restraints have on the free energy landscapes of proteins. Taken together, these results demonstrate that the molecular fragment replacement strategy can be used in combination with chemical shift information to characterize not only the native structures of proteins but also their conformational fluctuations.
authors.affiliation: Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark; mv245@cam.ac.uk wb@bio.ku.dk.
authors.forename: Wouter
authors.initials: W
authors.lastname: Boomsma
authors.affiliation: Niels Bohr Institute, University of Copenhagen, 2100 Copenhagen, Denmark;
authors.forename: Pengfei
authors.initials: P
authors.lastname: Tian
authors.affiliation: Department of Engineering, University of Cambridge, Cambridge, CB2 1PZ, United Kingdom;
authors.forename: Jes
authors.initials: J
authors.lastname: Frellsen
authors.affiliation: Biotech Research and Innovation Center, University of Copenhagen, Technical University of Denmark Campus, 2800 Kongens Lyngby, Denmark; and.
authors.forename: Jesper
authors.initials: J
authors.lastname: Ferkinghoff-Borg
authors.affiliation: Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark;
authors.forename: Thomas
authors.initials: T
authors.lastname: Hamelryck
authors.affiliation: Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark;
authors.forename: Kresten
authors.initials: K
authors.lastname: Lindorff-Larsen
authors.affiliation: Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, United Kingdom mv245@cam.ac.uk wb@bio.ku.dk.
authors.forename: Michele
authors.initials: M
authors.lastname: Vendruscolo
mesh_terms: D003198:Computer Simulation; D008390:Markov Chains; D008958:Models, Molecular; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000379:methods*; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins