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Updated: Jul 3, 2026
09:51
Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
Published on: July 16, 2017
Quantifying the peripheral surface information entropy from conformational ensembles of globular protein-peptide
Tyler J Grear1, Donald J Jacobs2
1Department of Physics and Optical Science, University of North Carolina at Charlotte, 9201 University City Boulevard, Charlotte, NC, USA; Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Boulevard, Charlotte, NC, USA.
Biophysical Journal
|July 2, 2026
Summary
Peripheral Surface Information (PSI) entropy quantifies protein-peptide binding. Favorable interactions show low-entropy states, revealing specific non-interacting surface configurations selected by evolution.
Area of Science:
- Biophysics
- Computational Biology
- Structural Biology
Background:
- Predicting protein-peptide binding is crucial but challenging.
- The role of nonlocal effects on binding energy landscapes is unclear.
Purpose of the Study:
- Introduce Peripheral Surface Information (PSI) entropy (SΨ) as a novel measure.
- Propose SΨ as a computationally tractable entropic proxy for binding.
- Investigate the statistical variability of non-interacting surface (NIS) proportions.
Main Methods:
- Utilized energy-directed molecular docking (HADDOCK3).
- Employed explicit-solvent molecular dynamics simulations.
- Analyzed conformational ensembles and NIS state space.
Main Results:
- Favorable binding partners exhibit low-entropy N-states in NIS.
- These states indicate preferential apolar/charged surface configurations.
- Dominant NIS modes were consistent across various systems and conditions.
Conclusions:
- SΨ encodes favorable binding constraints into statistical NIS signatures.
- Findings suggest evolutionary selection for specific NIS fingerprints.
- SΨ offers a new thermoinformatic descriptor for binding interactions.
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