ArticleScientific data2019
PEPCONF, a diverse data set of peptide conformational energies.
Article in Scientific data, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Fine-tuning molecular mechanics force fields to experimental free energy measurements.bioRxiv : the preprint server for biology · 2025Article
- Quantum mechanical electronic and geometric parameters for DNA k-mers as features for machine learning.Scientific data · 2024Article
- Machine-learned molecular mechanics force fields from large-scale quantum chemical data.Chemical science · 2024Article
- Revisiting Artifacts of Kohn-Sham Density Functionals for Biosimulation.Journal of chemical theory and computation · 2024Article
- CREMP: Conformer-rotamer ensembles of macrocyclic peptides for machine learning.Scientific data · 2024Article
- Article
- What are the minimal folding seeds in proteins? Experimental and theoretical assessment of secondary structure propensities of small peptide fragments.Chemical science · 2024Article
- A backbone-dependent rotamer library with high (ϕ, ψ) coverage using metadynamics simulations.Protein science : a publication of the Protein Society · 2022Article
- End-to-end differentiable construction of molecular mechanics force fields.Chemical science · 2022Article
- Estimating the Influence of Physicochemical and Biochemical Property Indexes on Selection for Amino Acids Usage in Eukaryotic Cells.Journal of molecular evolution · 2021Article
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Authors and funding
3 authors.
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Abstract
We present an extensive and diverse database of peptide conformational energies. Our database contains five different classes of model geometries: dipeptides, tripeptides, and disulfide-bridged, bioactive, and cyclic peptides. In total, the database consists of 3775 conformational energy data points and 4530 conformer geometries. All the reference energies have been calculated at the LC-ωPBE-XDM/aug-cc-pVTZ level of theory, which is shown to yield conformational energies with an accuracy in the order of tenths of a kcal/mol when compared to complete-basis-set coupled-cluster reference data. The peptide conformational data set (PEPCONF) is presented as a high-quality reference set for the development and benchmarking of molecular-mechanics and semi-empirical electronic structure methods, which are the most commonly used techniques in the modeling of medium to large proteins.
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