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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

Structural Displacements Along Each of the Top Three PCs.Displacements of CAs along each of the three top PCs are visualized on the right by plotting the coordinates of each PC. The SI and SII regions are annotated to show that they undergo some of the largest internal fluctuations captured by PC1 and PC2. The displacements along each PC are visualized on the left on an H-Ras structure using Pymol [44]. The colored sections correspond to the switch regions of H-Ras, with SI in green and SII in blue. Sections colored in light green show regions with structural changes of a similar magnitude to the switch regions.
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pcbi.1004470.g002: Structural Displacements Along Each of the Top Three PCs.Displacements of CAs along each of the three top PCs are visualized on the right by plotting the coordinates of each PC. The SI and SII regions are annotated to show that they undergo some of the largest internal fluctuations captured by PC1 and PC2. The displacements along each PC are visualized on the left on an H-Ras structure using Pymol [44]. The colored sections correspond to the switch regions of H-Ras, with SI in green and SII in blue. Sections colored in light green show regions with structural changes of a similar magnitude to the switch regions.

Mentions: One can analyze in further detail the molecular motions associated with the top three PCs. Each PC is a vector containing 166 × 3 displacements for each of the x, y, z cartesian coordinates of the 166 CA atoms in the catalytic domain of H-Ras. These displacements are visualized in the right panel of Fig 2 by plotting the coordinates of each PC. The SI and SII regions are annotated. The displacements along each PC are additionally visually illustrated on an H-Ras structure in the left panel of Fig 2.


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)

Structural Displacements Along Each of the Top Three PCs.Displacements of CAs along each of the three top PCs are visualized on the right by plotting the coordinates of each PC. The SI and SII regions are annotated to show that they undergo some of the largest internal fluctuations captured by PC1 and PC2. The displacements along each PC are visualized on the left on an H-Ras structure using Pymol [44]. The colored sections correspond to the switch regions of H-Ras, with SI in green and SII in blue. Sections colored in light green show regions with structural changes of a similar magnitude to the switch regions.
© Copyright Policy
Related In: Results  -  Collection

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

pcbi.1004470.g002: Structural Displacements Along Each of the Top Three PCs.Displacements of CAs along each of the three top PCs are visualized on the right by plotting the coordinates of each PC. The SI and SII regions are annotated to show that they undergo some of the largest internal fluctuations captured by PC1 and PC2. The displacements along each PC are visualized on the left on an H-Ras structure using Pymol [44]. The colored sections correspond to the switch regions of H-Ras, with SI in green and SII in blue. Sections colored in light green show regions with structural changes of a similar magnitude to the switch regions.
Mentions: One can analyze in further detail the molecular motions associated with the top three PCs. Each PC is a vector containing 166 × 3 displacements for each of the x, y, z cartesian coordinates of the 166 CA atoms in the catalytic domain of H-Ras. These displacements are visualized in the right panel of Fig 2 by plotting the coordinates of each PC. The SI and SII regions are annotated. The displacements along each PC are additionally visually illustrated on an H-Ras structure in the left panel of Fig 2.

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