Evidence map›Paper›PMID 37679431›Full record

ArticleCommunications chemistry2023

Improving AlphaFold2-based protein tertiary structure prediction with MULTICOM in CASP15.

Jian Liu, Zhiye Guo, Tianqi Wu, Raj S Roy, Chen Chen, Jianlin Cheng

Abstract read
In one paragraph

Article in Communications chemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

20 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Modeling Alternative Conformational States in CASP16.bioRxiv : the preprint server for biology · 2025
    Article
  6. Review
  7. Review
  8. Modification of Non-photochemical Quenching Pathways in the CbioRxiv : the preprint server for biology · 2025
    Article
  9. Article
  10. Review
  11. Article
  12. Petabase-Scale Homology Search for Structure Prediction.Cold Spring Harbor perspectives in biology · 2024
    Review
  13. Review
  14. Article
  15. Protein structure accuracy estimation using geometry-complete perceptron networks.Protein science : a publication of the Protein Society · 2024
    Article
  16. Article
  17. Article
  18. Article
  19. Petascale Homology Search for Structure Prediction.bioRxiv : the preprint server for biology · 2023
    Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Jian LiuDepartment of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, 65211, USA.
Zhiye GuoDepartment of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, 65211, USA.ORCID http://orcid.org/0000-0001-5598-4834
Tianqi WuDepartment of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, 65211, USA.
Raj S RoyDepartment of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, 65211, USA.
Chen ChenDepartment of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, 65211, USA.
Jianlin ChengDepartment of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, 65211, USA. chengji@missouri.edu.ORCID http://orcid.org/0000-0003-0305-2853

Funding

Integrated Prediction of Protein Struture at 1D, 2D and 3D LevelsR01GM093123 · NIGMS · UNIVERSITY OF MISSOURI-COLUMBIA · PI CHENG, JIANLIN · 2010 to 2023
$3.8M
Deep learning methods for automated and accurate reconstruction of protein structures from cryo-EM image dataR01GM146340 · NIGMS · UNIVERSITY OF MISSOURI-COLUMBIA · PI CHENG, JIANLIN · 2022 to 2025
$1.4M
NIGMS NIH HHS R01 GM093123NIGMS NIH HHS R01 GM146340
6 · The paper itself

Abstract

Since the 14th Critical Assessment of Techniques for Protein Structure Prediction (CASP14), AlphaFold2 has become the standard method for protein tertiary structure prediction. One remaining challenge is to further improve its prediction. We developed a new version of the MULTICOM system to sample diverse multiple sequence alignments (MSAs) and structural templates to improve the input for AlphaFold2 to generate structural models. The models are then ranked by both the pairwise model similarity and AlphaFold2 self-reported model quality score. The top ranked models are refined by a novel structure alignment-based refinement method powered by Foldseek. Moreover, for a monomer target that is a subunit of a protein assembly (complex), MULTICOM integrates tertiary and quaternary structure predictions to account for tertiary structural changes induced by protein-protein interaction. The system participated in the tertiary structure prediction in 2022 CASP15 experiment. Our server predictor MULTICOM_refine ranked 3rd among 47 CASP15 server predictors and our human predictor MULTICOM ranked 7th among all 132 human and server predictors. The average GDT-TS score and TM-score of the first structural models that MULTICOM_refine predicted for 94 CASP15 domains are ~0.80 and ~0.92, 9.6% and 8.2% higher than ~0.73 and 0.85 of the standard AlphaFold2 predictor respectively.

Identifiers

PMID37679431
PMCPMC10484931

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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.