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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
Published on: January 26, 2024
Improving amino-acid identification, fit and C(alpha) prediction using the Simplex method in automated model building
Tod D Romo1, James C Sacchettini, Thomas R Ioerger
1Texas A&M Center for Structural Biology, Institute for Biosciences and Technology, Houston, TX 77030, USA.
Acta Crystallographica. Section D, Biological Crystallography
|October 24, 2006
Summary
Improving automated protein model building, this study introduces a Simplex search to enhance side-chain identification accuracy in X-ray crystallography. This method refines protein models, especially in challenging
Area of Science:
- Structural Biology
- Computational Biology
- Biophysics
Background:
- Automated protein model building in X-ray crystallography involves backbone modeling and side-chain placement.
- Accurate side-chain identification is crucial but challenging due to potential errors in backbone atom coordinates and density fitting.
- Sequence alignment can correct errors but is not always sufficient, especially in the 'twilight zone' of low sequence identity.
Purpose of the Study:
- To improve the accuracy of automated amino-acid side-chain identification and model building in protein crystallography.
- To assess the impact of incorporating a Nelder-Mead Simplex search into the TEXTAL algorithm for side-chain refinement.
- To evaluate the combined effect of the Simplex search and sequence alignment on overall model accuracy.
Main Methods:
- Integration of a Nelder-Mead Simplex search into TEXTAL's side-chain identification and model-building routines.
- Implementation of residue-by-residue rigid-body real-space refinement, allowing C(alpha) atom shifts.
- Testing the method on a dataset of five representative proteins, comparing results with and without sequence alignment.
Main Results:
- The Simplex search improved initial side-chain selection accuracy by over 25% (from 25% to 32% average identity) without sequence alignment.
- This enhancement often moved pairwise amino-acid identity out of the 'twilight zone' for sequence alignment methods.
- Coupling the Simplex search with sequence alignment improved side-chain accuracy by an average of 13 percentage points (64% to 77%), with a maximum improvement of 38 percentage points.
Conclusions:
- Incorporating a Nelder-Mead Simplex search significantly enhances automated side-chain identification accuracy in protein model building.
- The refined accuracy aids in resolving ambiguities and improving the reliability of crystallographic protein models.
- This approach offers a valuable improvement, particularly when combined with sequence alignment, for challenging structural biology datasets.
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