Evidence map›Paper›PMID 34496578›Full record

ArticleThe Journal of chemical physics2021

A comparison of three DFT exchange-correlation functionals and two basis sets for the prediction of the conformation distribution of hydrated polyglycine.

Ying Yuan, Feng Wang

Abstract read
In one paragraph

Article in The Journal of chemical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. AsRSC advances · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ying YuanDepartment of Chemistry and Biochemistry, University of Arkansas, Fayetteville, Arkansas 72701, USA.ORCID 0000000233236912
Feng WangDepartment of Chemistry and Biochemistry, University of Arkansas, Fayetteville, Arkansas 72701, USA.ORCID 0000000227403534

Funding

Understanding Hesitant AdoptersP20GM103429 · NIGMS · UNIV OF ARKANSAS FOR MED SCIS · PI Lawrence E Cornett, JERRY WARE · 2012 to 2026
$60.9M
Efficient and Accurate Force Fields for Computer-Aided Drug DesignR01GM120578 · NIGMS · UNIVERSITY OF ARKANSAS AT FAYETTEVILLE · PI Feng Wang · 2017 to 2026
$1.9M
NIGMS NIH HHS P20 GM103429NIGMS NIH HHS R01 GM120578
6 · The paper itself

Abstract

The performance of three density functional theory (DFT) exchange-correlation functionals, namely, Perdew-Burke-Ernzerhof (PBE), BP86, and B3LYP, in predicting conformational distributions of a hydrated glycine peptide is tested with two different basis sets in the framework of adaptive force matching (AFM). The conformational distributions yielded the free energy profiles of the DFT functional and basis set combinations. Unlike traditional validations of potential energy and structural parameters, our approach allows the free energy of DFT to be validated. When compared to experimental distributions, the def2-TZVP basis set provides better agreement than a slightly trimmed aug-cc-pVDZ basis set. B3LYP is shown to be better than BP86 and PBE. The glycine model fitted against B3LYP-D3(BJ) with the def2-TZVP basis set is the most accurate and named the AFM2021 model for glycine. The AFM2021 glycine model provides better agreement with experimental J-coupling constants than C36m and ff14SB, although the margin is very small when compared to C36m. Our previously published alanine model is also refitted with the slightly simplified AFM2021 energy expression. This work shows good promise of AFM for developing force fields for a range of proteinogenic peptides using only DFT as reference.

Indexed as

Models, MolecularMolecular ConformationPeptidesQuantum TheoryWaterPeptidespolyglycineWater

Identifiers

PMID34496578
PMCPMC8425985

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.