Short peptides as predictors for the structure of polyarginine sequences in disordered proteins

Abstract

Intrinsically disordered proteins are rich in charged and deficient in hydrophobic residues. High net charges of disordered protein segments favor statistical coil ensembles which are more extended than a self-avoiding random coil. It is unclear whether the chain extension solely reflects the avoidance of non-local interactions or also local nearest neighbor interactions provide significant contributions. The relevance of nearest neighbor interactions, which are neglected in random coil models, has been emphasized in the literature, but only sporadically considered in molecular modellings of disordered proteins and peptides. We determined the Ramachandran distributions of protonated arginine in GRRG and GRRRG peptides. Our results reveal the contribution of nearest neighbor interactions to the extended conformations reported for a variety of poly-arginine protein segments.

Do molecular dynamics force fields accurately model Ramachandran distributions of amino acid residues in water?

“…S1-S3 (ESI †) demonstrate that extending the total simulation time per trajectory to 500 ns is not required for convergence, in line with previously published studies. 26,28,29,58 MD-derived J-coupling constants and all amide I 0 profiles for all guest residues x in GxG peptides under study are thus calculated from MD trajectories using the time interval 50-300 ns.…”

“…27 The optimization of the Gaussian model parameters is carried out by using the empirical Karplus equations [54][55][56][57] and an exitonic coupling formalism to calculate conformational averages of J-coupling constants and amide I 0 band profiles. 27,30,32,58 In the current study, some Gaussian model parameters for guest residues x in GxG peptides are revisited and slightly modified. In the evaluation of the MD-derived Ramachandran distributions, the same algorithm described above is used to calculate force fieldspecific MD-derived J-coupling constants and amide I 0 band profiles.…”

“…33 Previous studies suggested that the water model play an important role in the MD force field development. 10,22,26,58 Meral et al tested OPLS-AA/L combined with TIP3P or SPC/E to assess the intrinsic conformational dynamics of 15 guest residues in GxG peptides, trialanine, and alanine dipeptide, 22 Fig. 8 Assessment of the Gaussian model and MD force fields with respect to their ability to reproduce the experimental data for the guest residues A, I, F, D P , R, and S in cationic GxG in water using (a) w J 2 and (b) w VCD 2 functions.…”

“…The average (h i) and standard deviation (s) of w J Zhang et al examined OPLS-AA/L and OPLS-AA/M, each combined with 4 water models with respect to conformational ensembles of central alanine in GAG in AAA,26 and Milorey et al evaluated Amber ff14SB and CHARMM36m combined with TIP3P or OPC for guest arginine in GRG 58. None of these substitutions lead to a major improvement in the reproduction of experimental data for short oligopeptides.…”

Alternative Causal Link between Peptide Fibrillization and β-Strand Conformation

“…More detailed information in the disordered secondary structure could be further exploited, for example, by analyzing the peptide sequence in detail. 35 , 36 This would be important for further clarifying how such disordered peptide monomers support fibrillization.…”