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Analyzing Fluctuation Properties in Protein Elastic Networks with Sequence-Specific and Distance-Dependent
Romain Amyot1, Yuichi Togashi2,3,4, Holger Flechsig5
1Department of Mathematical and Life Sciences, Graduate School of Science, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8526, Japan. romain-amyot@hiroshima-u.ac.jp.
Biomolecules
|October 3, 2019
Summary
Protein elastic network models predict dynamics, but new variants struggle with flexible regions. Overestimation of fluctuations in weakly connected residues persists, hindering model improvement.
Area of Science:
- Computational Biology
- Biophysics
- Structural Biology
Background:
- Protein elastic network models (ENMs) are widely used for predicting protein dynamics.
- Recent ENM variants incorporate sequence-specific and distance-dependent residue interactions, improving experimental agreement.
Purpose of the Study:
- To systematically study protein fluctuation properties using new ENM variants.
- To compare predictions from new ENM variants with conventional anisotropic network models (ANMs).
Main Methods:
- Application of novel sequence-specific and distance-dependent ENM variants.
- Systematic analysis of protein fluctuation properties across a large dataset of protein structures.
- Comparison of ENM predictions against conventional anisotropic network models.
Main Results:
- New ENM variants frequently show poor predictions in highly flexible protein regions.
- All models, including new variants, tend to overestimate fluctuations of weakly connected residues.
- Sequence information and soft long-ranged interactions do not resolve the overestimation issue.
Conclusions:
- Overestimation of fluctuations in flexible regions remains a significant challenge for ENMs.
- Integration of chemical information shows limited impact on predicting individual residue fluctuations.
- Inherent drawbacks in current ENMs may hinder future model improvements.
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