Cited by 86Protein Structure and DynamicsEnzyme Structure and FunctionMachine Learning in Bioinformatics

Enhancing alphafold-multimer-based protein complex structure prediction with MULTICOM in CASP15

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Liu, Jian, Guo, Zhiye, Wu, Tianqi, Roy, Raj S., Quadir, Farhan, Chen, Chen, Cheng, Jianlin·2023·Communications Biology

Published version of a preprint

Abstract

To enhance the AlphaFold-Multimer-based protein complex structure prediction, we developed a quaternary structure prediction system (MULTICOM) to improve the input fed to AlphaFold-Multimer and evaluate and refine its outputs. MULTICOM samples diverse multiple sequence alignments (MSAs) and templates for AlphaFold-Multimer to generate structural predictions by using both traditional sequence alignments and Foldseek-based structure alignments, ranks structural predictions through multiple complementary metrics, and refines the structural predictions via a Foldseek structure alignment-based refinement method. The MULTICOM system with different implementations was blindly tested in the assembly structure prediction in the 15 th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022 as both server and human predictors. MULTICOM_qa ranked 3 rd among 26 CASP15 server predictors and MULTICOM_human ranked 7 th among 87 CASP15 server and human predictors. The average TM-score of the first predictions submitted by MULTICOM_qa for CASP15 assembly targets is ~0.76, 5.3% higher than ~0.72 of the standard AlphaFold-Multimer. The average TM-score of the best of top 5 predictions submitted by MULTICOM_qa is ~0.80, about 8% higher than ~0.74 of the standard AlphaFold-Multimer. Moreover, the Foldseek Structure Alignment-based Multimer structure Generation (FSAMG) method outperforms the widely used sequence alignment-based multimer structure generation.

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Authors
Liu, J., Guo, Z., Wu, T., Roy, R. S., Quadir, F., Chen, C., & Cheng, J.
Affiliations
University of Missouri (US)
Corresponding author
Cheng, Jianlin
Venue
Communications Biology
Published
2023-11-10
Volume
6
Issue
1
Pages
1140-1140
ISSN
2399-3642 (ISSN-L)
OpenAlex
W4388571183
Cited by
86
References
6
Citations by year
2026: 21 · 2025: 27 · 2024: 31 · 2023: 7
FWCI
7.66
Type
journal article
Language
en
Open access
Locations
  • Communications Biology (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
  • PubMed Central (submittedVersion, cc-by-nc-nd)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
U.S. Department of Health & Human Services | National Institutes of Health (R01GM093123 and R01GM146340)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
Keywords
protein complex structure prediction, quaternary structure prediction, AlphaFold-Multimer, multiple sequence alignment, CASP15, TM-score

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