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A Generative Angular Model of Protein Structure Evolution
- Source :
- Molecular Biology and Evolution, Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela, instname, Golden, M, Garcia-Portugues, E, Sørensen, M, Mardia, K V, Hamelryck, T & Hein, J 2017, ' A Generative Angular Model of Protein Structure Evolution ', Molecular Biology and Evolution, vol. 34, no. 8, pp. 2085-2100 . https://doi.org/10.1093/molbev/msx137
- Publication Year :
- 2017
- Publisher :
- Oxford University Press, 2017.
-
Abstract
- Recently described stochastic models of protein evolution have demonstrated that the inclusion of structural information in addition to amino acid sequences leads to a more reliable estimation of evolutionary parameters. We present a generative, evolutionary model of protein structure and sequence that is valid on a local length scale. The model concerns the local dependencies between sequence and structure evolution in a pair of homologous proteins. The evolutionary trajectory between the two structures in the protein pair is treated as a random walk in dihedral angle space, which is modelled using a novel angular diffusion process on the two-dimensional torus. Coupling sequence and structure evolution in our model allows for modelling both "smooth" conformational changes and "catastrophic" conformational jumps, conditioned on the amino acid changes. The model has interpretable parameters and is comparatively more realistic than previous stochastic models, providing new insights into the relationship between sequence and structure evolution. For example, using the trained model we were able to identify an apparent sequence-structure evolutionary motif present in a large number of homologous protein pairs. The generative nature of our model enables us to evaluate its validity and its ability to simulate aspects of protein evolution conditioned on an amino acid sequence, a related amino acid sequence, a related structure or any combination thereof.<br />Comment: 23 pages, 10 figures. Supplementary material: 5 pages, 4 figures
- Subjects :
- 0106 biological sciences
0301 basic medicine
Models, Molecular
FOS: Computer and information sciences
Stochastic modelling
Protein Conformation
Evolution
Sequence alignment
Dihedral angle
Biology
Bioinformatics
010603 evolutionary biology
01 natural sciences
Evolution, Molecular
Methodology (stat.ME)
03 medical and health sciences
Directional statistics
probabilistic model
Protein structure
Protein Structural Elements
Sequence Analysis, Protein
evolution
Genetics
Methods
Computer Simulation
Amino Acid Sequence
protein structure
Quantitative Biology - Populations and Evolution
Molecular Biology
Peptide sequence
Ecology, Evolution, Behavior and Systematics
Statistics - Methodology
Quantitative Biology::Biomolecules
Models, Genetic
Errata
Probabilistic model
Populations and Evolution (q-bio.PE)
Proteins
directional statistics
Protein superfamily
Random walk
030104 developmental biology
FOS: Biological sciences
60J60, 60K40, 62H11, 62M05
Biological system
Sequence Alignment
Subjects
Details
- Language :
- English
- ISSN :
- 15371719 and 07374038
- Volume :
- 34
- Issue :
- 8
- Database :
- OpenAIRE
- Journal :
- Molecular Biology and Evolution
- Accession number :
- edsair.doi.dedup.....d43750408fa898dc1340b73e4bf5a681