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Mapping the Conformation Space of Wildtype and Mutant H-Ras with a Memetic, Cellular, and Multiscale Evolutionary Algorithm.

Clausen R, Ma B, Nussinov R, Shehu A - PLoS Comput. Biol. (2015)

Bottom Line: Many Ras mutations are oncogenic, but detailed energy landscapes have not been reported until now.Analysis of SIfTER-computed energy landscapes for the wildtype and two oncogenic variants, G12V and Q61L, suggests that these mutations cause constitutive activation through two different mechanisms.G12V directly affects binding specificity while leaving the energy landscape largely unchanged, whereas Q61L has pronounced, starker effects on the landscape.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America.

ABSTRACT
An important goal in molecular biology is to understand functional changes upon single-point mutations in proteins. Doing so through a detailed characterization of structure spaces and underlying energy landscapes is desirable but continues to challenge methods based on Molecular Dynamics. In this paper we propose a novel algorithm, SIfTER, which is based instead on stochastic optimization to circumvent the computational challenge of exploring the breadth of a protein's structure space. SIfTER is a data-driven evolutionary algorithm, leveraging experimentally-available structures of wildtype and variant sequences of a protein to define a reduced search space from where to efficiently draw samples corresponding to novel structures not directly observed in the wet laboratory. The main advantage of SIfTER is its ability to rapidly generate conformational ensembles, thus allowing mapping and juxtaposing landscapes of variant sequences and relating observed differences to functional changes. We apply SIfTER to variant sequences of the H-Ras catalytic domain, due to the prominent role of the Ras protein in signaling pathways that control cell proliferation, its well-studied conformational switching, and abundance of documented mutations in several human tumors. Many Ras mutations are oncogenic, but detailed energy landscapes have not been reported until now. Analysis of SIfTER-computed energy landscapes for the wildtype and two oncogenic variants, G12V and Q61L, suggests that these mutations cause constitutive activation through two different mechanisms. G12V directly affects binding specificity while leaving the energy landscape largely unchanged, whereas Q61L has pronounced, starker effects on the landscape. An implementation of SIfTER is made available at http://www.cs.gmu.edu/~ashehu/?q=OurTools. We believe SIfTER is useful to the community to answer the question of how sequence mutations affect the function of a protein, when there is an abundance of experimental structures that can be exploited to reconstruct an energy landscape that would be computationally impractical to do via Molecular Dynamics.

No MeSH data available.


Related in: MedlinePlus

Projection of PDB-obtained Crystallographic Structures over Top Two PCs.Projections on the top two PCs are shown for all 86 collected structures of H-Ras. The 46 structures actually subjected to the PCA are in red (these correspond to the GTP-bound/inactive state) and in green (these correspond to the GDP-bound/active state). The 40 structures withheld from the PCA for validation purposes are shown in blue. The accumulation of variance subplot in the top left shows that PCA is effective for H-Ras. The 90% variance is achieved at 10 PCs. The two functional states of H-Ras are clearly separated by PC1. Projections of the 40 structures withheld from the PCA are contained in the same space.
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pcbi.1004470.g001: Projection of PDB-obtained Crystallographic Structures over Top Two PCs.Projections on the top two PCs are shown for all 86 collected structures of H-Ras. The 46 structures actually subjected to the PCA are in red (these correspond to the GTP-bound/inactive state) and in green (these correspond to the GDP-bound/active state). The 40 structures withheld from the PCA for validation purposes are shown in blue. The accumulation of variance subplot in the top left shows that PCA is effective for H-Ras. The 90% variance is achieved at 10 PCs. The two functional states of H-Ras are clearly separated by PC1. Projections of the 40 structures withheld from the PCA are contained in the same space.

Mentions: Detailed analysis of the effectiveness of the PCA is provided in the Materials and Methods section, but Fig 1 summarizes this analysis by showing the projections of crystallographic structures on the top two axes/PCs obtained by the PCA. Fig 1 shows that the two functional (active and inactive) states are clearly separated, which is also in agreement with the results presented originally by McCammon and colleagues [7, 25]. In addition, a cumulative variance analysis detailed in the Materials and Methods section and summarized in the top left panel of Fig 1 indicates that only 10 PCs need to be specified as axes of search for SIfTER and yet retain 90% of the variance among the crystallographic structures. Moreover, only two PCs are needed to capture more than 50% of the variance; these two can be used to project SIfTER-obtained energy surfaces and visualize energy landscapes.


Mapping the Conformation Space of Wildtype and Mutant H-Ras with a Memetic, Cellular, and Multiscale Evolutionary Algorithm.

Clausen R, Ma B, Nussinov R, Shehu A - PLoS Comput. Biol. (2015)

Projection of PDB-obtained Crystallographic Structures over Top Two PCs.Projections on the top two PCs are shown for all 86 collected structures of H-Ras. The 46 structures actually subjected to the PCA are in red (these correspond to the GTP-bound/inactive state) and in green (these correspond to the GDP-bound/active state). The 40 structures withheld from the PCA for validation purposes are shown in blue. The accumulation of variance subplot in the top left shows that PCA is effective for H-Ras. The 90% variance is achieved at 10 PCs. The two functional states of H-Ras are clearly separated by PC1. Projections of the 40 structures withheld from the PCA are contained in the same space.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4556523&req=5

pcbi.1004470.g001: Projection of PDB-obtained Crystallographic Structures over Top Two PCs.Projections on the top two PCs are shown for all 86 collected structures of H-Ras. The 46 structures actually subjected to the PCA are in red (these correspond to the GTP-bound/inactive state) and in green (these correspond to the GDP-bound/active state). The 40 structures withheld from the PCA for validation purposes are shown in blue. The accumulation of variance subplot in the top left shows that PCA is effective for H-Ras. The 90% variance is achieved at 10 PCs. The two functional states of H-Ras are clearly separated by PC1. Projections of the 40 structures withheld from the PCA are contained in the same space.
Mentions: Detailed analysis of the effectiveness of the PCA is provided in the Materials and Methods section, but Fig 1 summarizes this analysis by showing the projections of crystallographic structures on the top two axes/PCs obtained by the PCA. Fig 1 shows that the two functional (active and inactive) states are clearly separated, which is also in agreement with the results presented originally by McCammon and colleagues [7, 25]. In addition, a cumulative variance analysis detailed in the Materials and Methods section and summarized in the top left panel of Fig 1 indicates that only 10 PCs need to be specified as axes of search for SIfTER and yet retain 90% of the variance among the crystallographic structures. Moreover, only two PCs are needed to capture more than 50% of the variance; these two can be used to project SIfTER-obtained energy surfaces and visualize energy landscapes.

Bottom Line: Many Ras mutations are oncogenic, but detailed energy landscapes have not been reported until now.Analysis of SIfTER-computed energy landscapes for the wildtype and two oncogenic variants, G12V and Q61L, suggests that these mutations cause constitutive activation through two different mechanisms.G12V directly affects binding specificity while leaving the energy landscape largely unchanged, whereas Q61L has pronounced, starker effects on the landscape.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America.

ABSTRACT
An important goal in molecular biology is to understand functional changes upon single-point mutations in proteins. Doing so through a detailed characterization of structure spaces and underlying energy landscapes is desirable but continues to challenge methods based on Molecular Dynamics. In this paper we propose a novel algorithm, SIfTER, which is based instead on stochastic optimization to circumvent the computational challenge of exploring the breadth of a protein's structure space. SIfTER is a data-driven evolutionary algorithm, leveraging experimentally-available structures of wildtype and variant sequences of a protein to define a reduced search space from where to efficiently draw samples corresponding to novel structures not directly observed in the wet laboratory. The main advantage of SIfTER is its ability to rapidly generate conformational ensembles, thus allowing mapping and juxtaposing landscapes of variant sequences and relating observed differences to functional changes. We apply SIfTER to variant sequences of the H-Ras catalytic domain, due to the prominent role of the Ras protein in signaling pathways that control cell proliferation, its well-studied conformational switching, and abundance of documented mutations in several human tumors. Many Ras mutations are oncogenic, but detailed energy landscapes have not been reported until now. Analysis of SIfTER-computed energy landscapes for the wildtype and two oncogenic variants, G12V and Q61L, suggests that these mutations cause constitutive activation through two different mechanisms. G12V directly affects binding specificity while leaving the energy landscape largely unchanged, whereas Q61L has pronounced, starker effects on the landscape. An implementation of SIfTER is made available at http://www.cs.gmu.edu/~ashehu/?q=OurTools. We believe SIfTER is useful to the community to answer the question of how sequence mutations affect the function of a protein, when there is an abundance of experimental structures that can be exploited to reconstruct an energy landscape that would be computationally impractical to do via Molecular Dynamics.

No MeSH data available.


Related in: MedlinePlus