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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

Reproduction of Crystallographic Structures Among SIfTER-generated Functional Conformations.Each crystallographic structure is compared to the sub-ensemble of functional conformations obtained by SIfTER, and the lowest CA RMSD is reported. CA RMSDs corresponding to GTP-bound structures are drawn in red, those corresponding to GDP-bound structures are drawn in green, and those corresponding to the 40 crystallographic structure withheld from the PCA for the purpose of validation are drawn in blue.
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pcbi.1004470.g003: Reproduction of Crystallographic Structures Among SIfTER-generated Functional Conformations.Each crystallographic structure is compared to the sub-ensemble of functional conformations obtained by SIfTER, and the lowest CA RMSD is reported. CA RMSDs corresponding to GTP-bound structures are drawn in red, those corresponding to GDP-bound structures are drawn in green, and those corresponding to the 40 crystallographic structure withheld from the PCA for the purpose of validation are drawn in blue.

Mentions: We validate first the capability of SIfTER to discover known functional conformations of H-Ras. We show data for the WT. For each of the 86 crystallographic structures, we find the closest conformation to that structure among the functional conformations obtained by SIfTER for WT H-Ras (all-atom conformations whose energies meet the energetic threshold described above). The distance between two conformations is measured through the well-known root-mean-squared-deviation (RMSD)after an optimal superimposition has been found that removes structural differences due to rigid-body motions [45]. In particular, Fig 3 shows CA RMSDs (the distribution of backbone RMSDs is very similar). It is not possible to report all-atom RMSDs, because many of these crystallographic structures may be on different sequences or have missing side-chain atoms even if reported for the WT sequence.


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)

Reproduction of Crystallographic Structures Among SIfTER-generated Functional Conformations.Each crystallographic structure is compared to the sub-ensemble of functional conformations obtained by SIfTER, and the lowest CA RMSD is reported. CA RMSDs corresponding to GTP-bound structures are drawn in red, those corresponding to GDP-bound structures are drawn in green, and those corresponding to the 40 crystallographic structure withheld from the PCA for the purpose of validation are drawn in blue.
© Copyright Policy
Related In: Results  -  Collection

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

pcbi.1004470.g003: Reproduction of Crystallographic Structures Among SIfTER-generated Functional Conformations.Each crystallographic structure is compared to the sub-ensemble of functional conformations obtained by SIfTER, and the lowest CA RMSD is reported. CA RMSDs corresponding to GTP-bound structures are drawn in red, those corresponding to GDP-bound structures are drawn in green, and those corresponding to the 40 crystallographic structure withheld from the PCA for the purpose of validation are drawn in blue.
Mentions: We validate first the capability of SIfTER to discover known functional conformations of H-Ras. We show data for the WT. For each of the 86 crystallographic structures, we find the closest conformation to that structure among the functional conformations obtained by SIfTER for WT H-Ras (all-atom conformations whose energies meet the energetic threshold described above). The distance between two conformations is measured through the well-known root-mean-squared-deviation (RMSD)after an optimal superimposition has been found that removes structural differences due to rigid-body motions [45]. In particular, Fig 3 shows CA RMSDs (the distribution of backbone RMSDs is very similar). It is not possible to report all-atom RMSDs, because many of these crystallographic structures may be on different sequences or have missing side-chain atoms even if reported for the WT sequence.

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