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

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

doi:10.1038/s42004-023-00991-6

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

Journal Article · Thu Sep 07 00:00:00 UTC 2023 · Communications Chemistry

DOI:https://doi.org/10.1038/s42004-023-00991-6· OSTI ID:2278950

Liu, Jian ^[1]; ^[2]; Wu, Tianqi ^[2]; Roy, Raj S. ^[2]; Chen, Chen ^[2]; ^[2]

Univ. of Missouri, Columbia, MO (United States); University of Missouri-Columbia
Univ. of Missouri, Columbia, MO (United States)

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.

View Accepted Manuscript (DOE)

Research Organization:: Donald Danforth Plant Science Center, St. Louis, MO (United States)

Sponsoring Organization:: National Institutes of Health (NIH); National Science Foundation (NSF); USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: SC0020400; SC0021303

OSTI ID:: 2278950

Alternate ID(s):: OSTI ID: 2318505

Journal Information:: Communications Chemistry, Journal Name: Communications Chemistry Journal Issue: 1 Vol. 6; ISSN 2399-3669

Publisher:: Springer NatureCopyright Statement

Country of Publication:: United States

Language:: English

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