Dataset Information

PEP-FOLD4: a pH-dependent force field for peptide structure prediction in aqueous solution.

ABSTRACT: Accurate and fast structure prediction of peptides of less 40 amino acids in aqueous solution has many biological applications, but their conformations are pH- and salt concentration-dependent. In this work, we present PEP-FOLD4 which goes one step beyond many machine-learning approaches, such as AlphaFold2, TrRosetta and RaptorX. Adding the Debye-Hueckel formalism for charged-charged side chain interactions to a Mie formalism for all intramolecular (backbone and side chain) interactions, PEP-FOLD4, based on a coarse-grained representation of the peptides, performs as well as machine-learning methods on well-structured peptides, but displays significant improvements for poly-charged peptides. PEP-FOLD4 is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-FOLD4. This server is free and there is no login requirement.

SUBMITTER: Rey J

PROVIDER: S-EPMC10320157 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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Publications

PEP-FOLD4: a pH-dependent force field for peptide structure prediction in aqueous solution.

Rey Julien J Murail Samuel S de Vries Sjoerd S Derreumaux Philippe P Tuffery Pierre P

Nucleic acids research 20230701 W1

Accurate and fast structure prediction of peptides of less 40 amino acids in aqueous solution has many biological applications, but their conformations are pH- and salt concentration-dependent. In this work, we present PEP-FOLD4 which goes one step beyond many machine-learning approaches, such as AlphaFold2, TrRosetta and RaptorX. Adding the Debye-Hueckel formalism for charged-charged side chain interactions to a Mie formalism for all intramolecular (backbone and side chain) interactions, PEP-FO ...[more]

PMID: 37166962

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Project description:By applying REMD simulations we have performed comparative analysis of the conformational ensembles of amino-truncated Aβ10-40 peptide produced with five force fields, which combine four protein parameterizations (CHARMM36, CHARMM22*, CHARMM22/cmap, and OPLS-AA) and two water models (standard and modified TIP3P). Aβ10-40 conformations were analyzed by computing secondary structure, backbone fluctuations, tertiary interactions, and radius of gyration. We have also calculated Aβ10-40 3JHNHα-coupling and RDC constants and compared them with their experimental counterparts obtained for the full-length Aβ1-40 peptide. Our study led us to several conclusions. First, all force fields predict that Aβ adopts unfolded structure dominated by turn and random coil conformations. Second, specific TIP3P water model does not dramatically affect secondary or tertiary Aβ10-40 structure, albeit standard TIP3P model favors slightly more compact states. Third, although the secondary structures observed in CHARMM36 and CHARMM22/cmap simulations are qualitatively similar, their tertiary interactions show little consistency. Fourth, two force fields, OPLS-AA and CHARMM22* have unique features setting them apart from CHARMM36 or CHARMM22/cmap. OPLS-AA reveals moderate β-structure propensity coupled with extensive, but weak long-range tertiary interactions leading to Aβ collapsed conformations. CHARMM22* exhibits moderate helix propensity and generates multiple exceptionally stable long- and short-range interactions. Our investigation suggests that among all force fields CHARMM22* differs the most from CHARMM36. Fifth, the analysis of 3JHNHα-coupling and RDC constants based on CHARMM36 force field with standard TIP3P model led us to an unexpected finding that in silico Aβ10-40 and experimental Aβ1-40 constants are generally in better agreement than these quantities computed and measured for identical peptides, such as Aβ1-40 or Aβ1-42. This observation suggests that the differences in the conformational ensembles of Aβ10-40 and Aβ1-40 are small and the former can be used as proxy of the full-length peptide. Based on this argument, we concluded that CHARMM36 force field with standard TIP3P model produces the most accurate representation of Aβ10-40 conformational ensemble.

Dataset Information

PEP-FOLD4: a pH-dependent force field for peptide structure prediction in aqueous solution.

Publications

PEP-FOLD4: a pH-dependent force field for peptide structure prediction in aqueous solution.

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