Visualization of protein folding funnels in lattice models.
Protein folding occurs in a very high dimensional phase space with an exponentially large number of states, and according to the energy landscape theory it exhibits a topology resembling a funnel. In this statistical approach, the folding mechanism is unveiled by describing the local minima in an ef...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2014-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC4091862?pdf=render |
| _version_ | 1818291569515560960 |
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| author | Antonio B Oliveira Francisco M Fatore Fernando V Paulovich Osvaldo N Oliveira Vitor B P Leite |
| author_facet | Antonio B Oliveira Francisco M Fatore Fernando V Paulovich Osvaldo N Oliveira Vitor B P Leite |
| author_sort | Antonio B Oliveira |
| collection | DOAJ |
| description | Protein folding occurs in a very high dimensional phase space with an exponentially large number of states, and according to the energy landscape theory it exhibits a topology resembling a funnel. In this statistical approach, the folding mechanism is unveiled by describing the local minima in an effective one-dimensional representation. Other approaches based on potential energy landscapes address the hierarchical structure of local energy minima through disconnectivity graphs. In this paper, we introduce a metric to describe the distance between any two conformations, which also allows us to go beyond the one-dimensional representation and visualize the folding funnel in 2D and 3D. In this way it is possible to assess the folding process in detail, e.g., by identifying the connectivity between conformations and establishing the paths to reach the native state, in addition to regions where trapping may occur. Unlike the disconnectivity maps method, which is based on the kinetic connections between states, our methodology is based on structural similarities inferred from the new metric. The method was developed in a 27-mer protein lattice model, folded into a 3×3×3 cube. Five sequences were studied and distinct funnels were generated in an analysis restricted to conformations from the transition-state to the native configuration. Consistent with the expected results from the energy landscape theory, folding routes can be visualized to probe different regions of the phase space, as well as determine the difficulty in folding of the distinct sequences. Changes in the landscape due to mutations were visualized, with the comparison between wild and mutated local minima in a single map, which serves to identify different trapping regions. The extension of this approach to more realistic models and its use in combination with other approaches are discussed. |
| first_indexed | 2024-12-13T02:46:09Z |
| format | Article |
| id | doaj.art-ff2467d47b2744359addcd6af05547ce |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-13T02:46:09Z |
| publishDate | 2014-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-ff2467d47b2744359addcd6af05547ce2022-12-22T00:02:12ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0197e10086110.1371/journal.pone.0100861Visualization of protein folding funnels in lattice models.Antonio B OliveiraFrancisco M FatoreFernando V PaulovichOsvaldo N OliveiraVitor B P LeiteProtein folding occurs in a very high dimensional phase space with an exponentially large number of states, and according to the energy landscape theory it exhibits a topology resembling a funnel. In this statistical approach, the folding mechanism is unveiled by describing the local minima in an effective one-dimensional representation. Other approaches based on potential energy landscapes address the hierarchical structure of local energy minima through disconnectivity graphs. In this paper, we introduce a metric to describe the distance between any two conformations, which also allows us to go beyond the one-dimensional representation and visualize the folding funnel in 2D and 3D. In this way it is possible to assess the folding process in detail, e.g., by identifying the connectivity between conformations and establishing the paths to reach the native state, in addition to regions where trapping may occur. Unlike the disconnectivity maps method, which is based on the kinetic connections between states, our methodology is based on structural similarities inferred from the new metric. The method was developed in a 27-mer protein lattice model, folded into a 3×3×3 cube. Five sequences were studied and distinct funnels were generated in an analysis restricted to conformations from the transition-state to the native configuration. Consistent with the expected results from the energy landscape theory, folding routes can be visualized to probe different regions of the phase space, as well as determine the difficulty in folding of the distinct sequences. Changes in the landscape due to mutations were visualized, with the comparison between wild and mutated local minima in a single map, which serves to identify different trapping regions. The extension of this approach to more realistic models and its use in combination with other approaches are discussed.http://europepmc.org/articles/PMC4091862?pdf=render |
| spellingShingle | Antonio B Oliveira Francisco M Fatore Fernando V Paulovich Osvaldo N Oliveira Vitor B P Leite Visualization of protein folding funnels in lattice models. PLoS ONE |
| title | Visualization of protein folding funnels in lattice models. |
| title_full | Visualization of protein folding funnels in lattice models. |
| title_fullStr | Visualization of protein folding funnels in lattice models. |
| title_full_unstemmed | Visualization of protein folding funnels in lattice models. |
| title_short | Visualization of protein folding funnels in lattice models. |
| title_sort | visualization of protein folding funnels in lattice models |
| url | http://europepmc.org/articles/PMC4091862?pdf=render |
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