ArticleBiophysical chemistry2016
Predicting unfolding thermodynamics and stable intermediates for alanine-rich helical peptides with the aid of coarse-grained molecular simulation.
Article in Biophysical chemistry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Computational Study on Potential Novel Anti-Ebola Virus Protein VP35 Natural Compounds.Biomedicines · 2021Article
- Characterizing aggregate growth and morphology of alanine-rich polypeptides as a function of sequence chemistry and solution temperature from scattering, spectroscopy, and microscopy.Biophysical chemistry · 2020Article
- Recent Advances in Coarse-Grained Models for Biomolecules and Their Applications.International journal of molecular sciences · 2019Review
- Multiconfigurational Coarse-Grained Molecular Dynamics.Journal of chemical theory and computation · 2019Article
- Review
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5 authors.
Funding
Abstract
This report focuses on the molecular-level processes and thermodynamics of unfolding of a series of helical peptides using a coarse-grained (CG) molecular model. The CG model was refined to capture thermodynamics and structural changes as a function of temperature for a set of published peptide sequences. Circular dichroism spectroscopy (CD) was used to experimentally monitor the temperature-dependent conformational changes and stability of published peptides and new sequences introduced here. The model predictions were quantitatively or semi-quantitatively accurate in all cases. The simulations and CD results showed that, as expected, in most cases the unfolding of helical peptides is well described by a simply 2-state model, and conformational stability increased with increased length of the helices. A notable exception in a 19-residue helix was when two Ala residues were each replaced with Phe. This stabilized a partly unfolded intermediate state via hydrophobic contacts, and also promoted aggregates at higher peptide concentrations.
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