Evidence map›Paper›PMID 34310137›Full record

ArticleJournal of chemical theory and computation2021

Diverse Scientific Benchmarks for Implicit Membrane Energy Functions.

Rebecca F Alford, Rituparna Samanta, Jeffrey J Gray

Abstract read
In one paragraph

Article in Journal of chemical theory and computation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Modeling membrane geometries implicitly in Rosetta.Protein science : a publication of the Protein Society · 2024
    Article
  7. Article
  8. Challenges of Protein-Protein Docking of the Membrane Proteins.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  9. 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.

Rebecca F AlfordDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States.ORCID https://orcid.org/0000-0003-0306-8476
Rituparna SamantaDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States.
Jeffrey J GrayDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States.ORCID https://orcid.org/0000-0001-6380-2324

Funding

Prediction of the Structure of Therapeutic Antibodies with their AntigensR01GM078221 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI GRAY, JEFFREY J · 2006 to 2020
$4.0M
NIGMS NIH HHS R01 GM078221
6 · The paper itself

Abstract

Energy functions are fundamental to biomolecular modeling. Their success depends on robust physical formalisms, efficient optimization, and high-resolution data for training and validation. Over the past 20 years, progress in each area has advanced soluble protein energy functions. Yet, energy functions for membrane proteins lag behind due to sparse and low-quality data, leading to overfit tools. To overcome this challenge, we assembled a suite of 12 tests on independent data sets varying in size, diversity, and resolution. The tests probe an energy function's ability to capture membrane protein orientation, stability, sequence, and structure. Here, we present the tests and use the

Identifiers

PMID34310137
PMCPMC9084325

What OpenQuestion holds

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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.