Probabilistic Determination of Native State Ensembles of Proteins

Publication: Research - peer-reviewJournal article – Annual report year: 2014

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The motions of biological macromolecules are tightly coupled to their functions. However, while the study of fast motions has become increasingly feasible in recent years, the study of slower, biologically important motions remains difficult. Here, we present a method to construct native state ensembles of proteins by the combination of physical force fields and experimental data through modern statistical methodology. As an example, we use NMR residual dipolar couplings to determine a native state ensemble of the extensively studied third immunoglobulin binding domain of protein G (GB3). The ensemble accurately describes both local and nonlocal backbone fluctuations as judged by its reproduction of complementary experimental data. While it is difficult to assess precise time-scales of the observed motions, our results suggest that it is possible to construct realistic conformational ensembles of biomolecules very efficiently. The approach may allow for a dramatic reduction in the computational as well as experimental resources needed to obtain accurate conformational ensembles of biological macromolecules in a statistically sound manner.
Original languageEnglish
JournalJournal of Chemical Theory and Computation
Volume10
Issue number8
Pages (from-to)3484-3491
Number of pages8
ISSN1549-9618
DOIs
StatePublished - 2014
CitationsWeb of Science® Times Cited: 23

    Keywords

  • CHEMISTRY, PHYSICS, RESIDUAL DIPOLAR COUPLINGS, DISPERSION NMR-SPECTROSCOPY, LIQUID-CRYSTALLINE MEDIUM, SMALL ALPHA/BETA PROTEIN, MONTE-CARLO-SIMULATION, BOND SCALAR COUPLINGS, CORRELATED MOTIONS, MOLECULAR-DYNAMICS, CONSERVATIVE MUTAGENESIS, MAXIMUM-LIKELIHOOD
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