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Prediction and evaluation of side-chain conformations for protein backbone structures
P S Shenkin1, H Farid, J S Fetrow
1Department of Chemistry, Columbia University, New York 10027, USA.
Proteins
|November 1, 1996
Summary
A new algorithm rapidly models protein side chains using atomic overlap and rotamer probability. This method accurately predicts side chain configurations and identifies reliable predictions using calculated side chain entropies.
Area of Science:
- Computational Biology
- Protein Structure Prediction
- Bioinformatics
Background:
- Protein modeling often involves building side chains onto a predetermined backbone structure.
- Accurate side chain placement is crucial for understanding protein function and interactions.
Purpose of the Study:
- To develop and test a fast algorithm for predicting protein side chain conformations.
- To evaluate the accuracy of side chain prediction using simulated annealing and Monte Carlo methods.
- To assess the utility of side chain entropy as a predictor of modeling reliability.
Main Methods:
- A novel algorithm utilizing atomic overlap and rotamer probability for side chain modeling.
- Exhaustive searches in protein cores and application to 49 known protein structures.
- Simulated annealing and low-temperature Monte Carlo simulations for conformational sampling and entropy calculation.
Main Results:
- The algorithm achieved correct rotamer prediction for 57% and correct chi 1 values for 74% of residues.
- Subsequent Monte Carlo simulations improved prediction accuracy.
- Calculated side chain entropies accurately indicated prediction reliability, with low entropy correlating strongly with correct predictions (79% rotamer, 84% chi 1).
Conclusions:
- The proposed algorithm provides an efficient and accurate method for protein side chain modeling.
- Side chain entropy is a robust indicator of prediction accuracy, independent of solvent accessibility.
- This finding has implications for understanding protein stability and design.