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| Content Provider | World Health Organization (WHO)-Global Index Medicus |
|---|---|
| Author | Vendruscolo, Michele Camilloni, Carlo Granata, Daniele Laio, Alessandro |
| Description | Author Affiliation: Granata D ( International School for Advanced Studies (SISSA), Trieste 34136, Italy.); |
| Abstract | The use of free-energy landscapes rationalizes a wide range of aspects of protein behavior by providing a clear illustration of the different states accessible to these molecules, as well as of their populations and pathways of interconversion. The determination of the free-energy landscapes of proteins by computational methods is, however, very challenging as it requires an extensive sampling of their conformational spaces. We describe here a technique to achieve this goal with relatively limited computational resources by incorporating nuclear magnetic resonance (NMR) chemical shifts as collective variables in metadynamics simulations. As in this approach the chemical shifts are not used as structural restraints, the resulting free-energy landscapes correspond to the force fields used in the simulations. We illustrate this approach in the case of the third Ig-binding domain of protein G from streptococcal bacteria (GB3). Our calculations reveal the existence of a folding intermediate of GB3 with nonnative structural elements. Furthermore, the availability of the free-energy landscape enables the folding mechanism of GB3 to be elucidated by analyzing the conformational ensembles corresponding to the native, intermediate, and unfolded states, as well as the transition states between them. Taken together, these results show that, by incorporating experimental data as collective variables in metadynamics simulations, it is possible to enhance the sampling efficiency by two or more orders of magnitude with respect to standard molecular dynamics simulations, and thus to estimate free-energy differences among the different states of a protein with a k(B)T accuracy by generating trajectories of just a few microseconds. |
| ISSN | 00278424 |
| e-ISSN | 10916490 |
| Journal | Proceedings of the National Academy of Sciences of the United States of America |
| Issue Number | 17 |
| Volume Number | 110 |
| Language | English |
| Publisher | National Academy of Sciences |
| Publisher Date | 2013-04-01 |
| Publisher Place | United States |
| Access Restriction | Open |
| Subject Keyword | Bacterial Proteins Chemistry Magnetic Resonance Spectroscopy Models, Molecular Protein Conformation Protein Folding Molecular Dynamics Simulation Thermodynamics Research Support, Non-U.S. Gov't Multidisciplinary |
| Content Type | Text |
| Resource Type | Article |
| Subject | Multidisciplinary |
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