Randomizing of Oligopeptide Conformations by Nearest Neighbor Interactions between Amino Acid Residues

Biomolecules. 2022 May 11;12(5):684. doi: 10.3390/biom12050684.

Abstract

Flory's random coil model assumes that conformational fluctuations of amino acid residues in unfolded poly(oligo)peptides and proteins are uncorrelated (isolated pair hypothesis, IPH). This implies that conformational energies, entropies and solvation free energies are all additive. Nearly 25 years ago, analyses of coil libraries cast some doubt on this notion, in that they revealed that aromatic, but also β-branched side chains, could change the 3J(HNH) coupling of their neighbors. Since then, multiple bioinformatical, computational and experimental studies have revealed that conformational propensities of amino acids in unfolded peptides and proteins depend on their nearest neighbors. We used recently reported and newly obtained Ramachandran plots of tetra- and pentapeptides with non-terminal homo- and heterosequences of amino acid residues to quantitatively determine nearest neighbor coupling between them with a Ising type model. Results reveal that, depending on the choice of amino acid residue pairs, nearest neighbor interactions either stabilize or destabilize pairs of polyproline II and β-strand conformations. This leads to a redistribution of population between these conformations and a reduction in conformational entropy. Interactions between residues in polyproline II and turn(helix)-forming conformations seem to be cooperative in most cases, but the respective interaction parameters are subject to large statistical errors.

Keywords: Ramachandran distributions; intrinsically disordered proteins; isolated pair hypothesis; model peptides; nearest neighbor interactions.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Amino Acids* / chemistry
  • Molecular Conformation
  • Oligopeptides / chemistry
  • Peptides* / chemistry
  • Proteins / chemistry

Substances

  • Amino Acids
  • Oligopeptides
  • Peptides
  • Proteins

Grants and funding

This research was funded by the National Science Foundation, grant number MCB-1817650.