Evidence map›Paper›PMID 22677388›Full record

ArticleBiophysical journal2012

The power of hard-sphere models: explaining side-chain dihedral angle distributions of Thr and Val.

Alice Qinhua Zhou, Corey S O'Hern, Lynne Regan

Open access · bronzeAbstract read
In one paragraph

Article in Biophysical journal, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.3field-weighted citation impact, top 20% of its field
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

12 citing papers in PubMed, 31 citations in OpenAlex.

  1. Residue burial encodes a protein's fold.bioRxiv : the preprint server for biology · 2026
    Article
  2. Core packing of well-defined X-ray and NMR structures is the same.Protein science : a publication of the Protein Society · 2022
    Article
  3. A threonine zipper that mediates protein-protein interactions: Structure and prediction.Protein science : a publication of the Protein Society · 2018
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. 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

3 authors at 1 institution in 1 country.

Alice Qinhua ZhouDepartment of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, USA.
Corey S O'Hern
Lynne Regan
Yale University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The energy functions used to predict protein structures typically include both molecular-mechanics and knowledge-based terms. In contrast, our approach is to develop robust physics- and geometry-based methods. Here, we investigate to what extent simple hard-sphere models can be used to predict side-chain conformations. The distributions of the side-chain dihedral angle χ(1) of Val and Thr in proteins of known structure show distinctive features: Val side chains predominantly adopt χ(1) = 180°, whereas Thr side chains typically adopt χ(1) = 60° and 300° (i.e., χ(1) = ±60° or g- and g(+) configurations). Several hypotheses have been proposed to explain these differences, including interresidue steric clashes and hydrogen-bonding interactions. In contrast, we show that the observed side-chain dihedral angle distributions for both Val and Thr can be explained using only local steric interactions in a dipeptide mimetic. Our results emphasize the power of simple physical approaches and their importance for future advances in protein engineering and design.

Indexed as

Models, MolecularDatabases, ProteinDipeptidesProtein Structure, SecondaryThreonineValineDipeptidesThreonineValine

Identifiers

PMID22677388
PMCPMC3353012
OpenAlexW2099360544

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.