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

Jian Liu1, Zhiye Guo1, Tianqi Wu1

  • 1Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, 65211, USA.

Communications Chemistry
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Researchers improved protein structure prediction by enhancing AlphaFold2 inputs with diverse data and refining models. This new MULTICOM system achieved top rankings in the CASP15 experiment, outperforming standard AlphaFold2.

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Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Protein structure prediction

Background:

  • AlphaFold2 is the leading method for protein tertiary structure prediction post-CASP14.
  • Improving AlphaFold2's prediction accuracy remains an active research area.
  • Protein structure prediction is crucial for understanding biological function and disease.

Purpose of the Study:

  • To enhance AlphaFold2's protein structure prediction capabilities.
  • To develop a refined prediction system integrating diverse inputs and advanced refinement techniques.
  • To evaluate the system's performance in a large-scale, blind prediction experiment (CASP15).

Main Methods:

  • Developed a new MULTICOM system version to generate diverse multiple sequence alignments (MSAs) and structural templates.
  • Improved AlphaFold2 input quality for generating multiple structural models.
  • Ranked models using pairwise similarity and AlphaFold2's quality score.
  • Refined top-ranked models using a novel structure alignment-based method (Foldseek).
  • Integrated tertiary and quaternary structure predictions for protein complex subunits.

Main Results:

  • The MULTICOM_refine server ranked 3rd out of 47 server predictors in CASP15.
  • The MULTICOM human predictor ranked 7th out of 132 total predictors in CASP15.
  • MULTICOM_refine achieved average GDT-TS and TM-scores of ~0.80 and ~0.92, respectively, for 94 CASP15 domains.
  • These scores represent a significant improvement over the standard AlphaFold2 predictor (~0.73 GDT-TS, ~0.85 TM-score).

Conclusions:

  • The enhanced MULTICOM system significantly improves upon standard AlphaFold2 for protein tertiary structure prediction.
  • The integration of diverse MSAs, templates, and advanced refinement strategies is effective.
  • The system's strong performance in CASP15 validates its utility for accurate protein structure modeling, including for protein complexes.