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AlphaFold at CASP13.

Mohammed AlQuraishi1,2

  • 1Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.

Bioinformatics (Oxford, England)
|May 23, 2019
PubMed
Summary

DeepMind

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Biochemistry

Background:

  • Protein structure prediction is a fundamental challenge in bioinformatics.
  • The Critical Assessment of protein Structure Prediction (CASP) benchmarks progress in the field.
  • DeepMind's AlphaFold achieved top performance in the Free Modeling category at CASP13.

Discussion:

  • AlphaFold integrates co-evolutionary analysis and deep neural networks.
  • This approach maps residue co-variation to physical contacts in protein structures.
  • The method identifies patterns in sequence and co-evolutionary data to generate contact maps.

Key Insights:

  • AlphaFold's success highlights the power of integrating diverse computational methods.
  • The approach builds upon decade-long academic research in co-evolutionary analysis and deep learning.

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  • This marks a significant advancement in the accuracy of computational protein structure prediction.

    • Outlook:

    • DeepMind's entry signifies growing industrial involvement in academic challenges.
    • Future research may focus on refining deep learning models for protein structure prediction.
    • Advancements in this area have profound implications for drug discovery and biological research.