DANGLE: A Bayesian inferential method for predicting protein backbone dihedral angles and secondary structure.
2010
Abstract This paper introduces DANGLE, a new algorithm that employs Bayesian inference to estimate the likelihood of all possible values of the backbone dihedral angles ϕ and ψ for each residue in a query protein, based on observed chemical shifts and the conformational preferences of each amino acid type. The method provides robust estimates of ϕ and ψ within realistic boundary ranges, an indication of the degeneracy in the relationship between shift measurements and conformation at each site, and faithful secondary structure state assignments. When a simple degeneracy-based filtering procedure is applied, DANGLE offers an ideal compromise between accuracy and coverage when compared with other shift-based dihedral angle prediction methods. In addition, per residue analysis of shift/structure degeneracy has potential to be a useful new approach for studying the properties of unfolded proteins, with sufficient sensitivity to identify regions of residual structure in the acid denatured state of apomyoglobin.
Keywords:
- Protein structure
- Computational chemistry
- Nuclear magnetic resonance
- Residue (complex analysis)
- Protein secondary structure
- Residual
- Compromise
- Graphical models for protein structure
- Degeneracy (mathematics)
- Crystallography
- Chemistry
- Dihedral angle
- Chemical shift
- Denaturation (biochemistry)
- Bayesian inference
- Analytical chemistry
- Statistical physics
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
60
References
181
Citations
NaN
KQI