Abstract

Disordered proline-rich motifs are common across the proteomes of many species and are often involved in protein-protein interactions. Proline is a unique amino acid due to the covalent bond between the backbone nitrogen and the proline side chain. The resulting five-membered ring allows proline to sample the cis state about its peptide bond, which other residues cannot do as readily. Because proline-rich disordered sequences exist as ensembles that likely include structures with the proline peptide bond in cis, a robust methodology to accurately account for these conformations in the overall ensemble is crucial. Observing the cis conformations of proline in a disordered sequence is challenging both experimentally and computationally. Nitrogen-hydrogen NMR spectroscopy cannot directly observe proline residues, which lack an amide bond, and computational methods struggle to overcome the large kinetic barrier between the cis and trans states, since isomerization usually occurs on the order of seconds. In the current work, Gaussian accelerated molecular dynamics was used to overcome this free energy barrier and simulate proline isomerization in a tetrapeptide (KPTP) and in the 12-residue proline-rich SH3 binding peptide, ArkA. We found that Gaussian accelerated molecular dynamics, when combined with a lowered peptide bond dihedral angle potential energy barrier (15 kcal/mol), allowed sufficient sampling of the proline cis and trans states on a microsecond timescale. All ArkA prolines spend a significant fraction of time in cis, leading to a more compact ensemble with less polyproline II helix structure than an ArkA ensemble with all peptide bonds in trans. The ensemble containing cis prolines also matches more closely to in vitro circular dichroism data than the all-trans ensemble. The ability of the ArkA prolines to isomerize likely affects the peptide’s ability to bind its partner SH3 domain, and should be studied further. This is the first molecular dynamics simulation study of proline isomerization in a biologically relevant proline-rich sequence that we know of, and a similar protocol could be applied to study multi-proline isomerization in other proline-containing proteins to improve conformational diversity and agreement with in vitro data.

Highlights

  • Proline-rich disordered sequences are one of the common binding motifs for protein-protein interaction domains found in biology

  • It is still a large barrier to overcome in molecular dynamics (MD) simulations, and even using the Gaussian accelerated MD (GaMD) method we only saw isomerization occur on a time scale of around once every 8 ns(Figure 1A)

  • Both the default barrier and lowered barrier simulations showed that the proline peptide bond ω dihedral angle can clearly occupy two distinct states that are similar to the canonical cis and trans values (Supplementary Figure S2)

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Summary

Introduction

Proline-rich disordered sequences are one of the common binding motifs for protein-protein interaction domains found in biology. Proline-rich regions are found widely in prokaryotes and eukaryotes and are present in twenty-five percent of human proteins (Williamson, 1994; Kaneko et al, 2008) Despite their prevalence, much is unknown about the structural properties of disordered proline-rich sequences since they are challenging to study both experimentally and computationally. A proline-rich region will canonically adopt a polyproline II (PPII) helix when bound to its interaction partner, such as an SH3 domain, these sequences are flexible and their structures can vary based on the identity of the other amino acids present (Williamson, 1994; Kaneko et al, 2008). In the case of proline, the unique ring structure means that the δ-carbon atom of the proline side chain is bonded to the nitrogen in the backbone, causing an unfavorable steric interaction between the δ-carbon and the α-carbon of the preceding residue in the trans conformation. If just a single peptide bond in a disordered sequence is in the cis conformation, this results in a kink at that point in the peptide chain

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Conclusion

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