Evidence map›Paper›PMID 34324224›Full record

ArticleProteins2021

Protein oligomer modeling guided by predicted interchain contacts in CASP14.

Minkyung Baek, Ivan Anishchenko, Hahnbeom Park, Ian R Humphreys, David Baker

Abstract read
In one paragraph

Article in Proteins, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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

5 authors.

Minkyung BaekDepartment of Biochemistry, University of Washington, Seattle, Washington, USA.ORCID 0000-0003-3414-9404
Ivan AnishchenkoDepartment of Biochemistry, University of Washington, Seattle, Washington, USA.
Hahnbeom ParkDepartment of Biochemistry, University of Washington, Seattle, Washington, USA.ORCID 0000-0002-7129-1912
Ian R HumphreysDepartment of Biochemistry, University of Washington, Seattle, Washington, USA.
David BakerDepartment of Biochemistry, University of Washington, Seattle, Washington, USA.

Funding

Howard Hughes Medical InstituteNIAID NIH HHS HHSN272201700059C
6 · The paper itself

Abstract

For CASP14, we developed deep learning-based methods for predicting homo-oligomeric and hetero-oligomeric contacts and used them for oligomer modeling. To build structure models, we developed an oligomer structure generation method that utilizes predicted interchain contacts to guide iterative restrained minimization from random backbone structures. We supplemented this gradient-based fold-and-dock method with template-based and ab initio docking approaches using deep learning-based subunit predictions on 29 assembly targets. These methods produced oligomer models with summed Z-scores 5.5 units higher than the next best group, with the fold-and-dock method having the best relative performance. Over the eight targets for which this method was used, the best of the five submitted models had average oligomer TM-score of 0.71 (average oligomer TM-score of the next best group: 0.64), and explicit modeling of inter-subunit interactions improved modeling of six out of 40 individual domains (ΔGDT-TS > 2.0).

Indexed as

Models, MolecularProtein ConformationProteinsSoftwareComputational BiologyDatabases, ProteinDeep LearningProtein BindingProtein SubunitsSequence Analysis, ProteinProteinsProtein Subunitsdeep learninginterchain contact predictionprotein complex structure predictionprotein-protien docking

Identifiers

PMID34324224
PMCPMC8616806

What OpenQuestion holds

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Registered trials

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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.