The transformative power of transformers in protein structure prediction.

Journal: Proceedings of the National Academy of Sciences of the United States of America
Published Date:

Abstract

Transformer neural networks have revolutionized structural biology with the ability to predict protein structures at unprecedented high accuracy. Here, we report the predictive modeling performance of the state-of-the-art protein structure prediction methods built on transformers for 69 protein targets from the recently concluded 15th Critical Assessment of Structure Prediction (CASP15) challenge. Our study shows the power of transformers in protein structure modeling and highlights future areas of improvement.

Authors

  • Bernard Moussad
    Department of Computer Science, Virginia Tech, Blacksburg, VA 24061.
  • Rahmatullah Roche
    Department of Computer Science, Virginia Tech, Blacksburg, VA 24061.
  • Debswapna Bhattacharya
    Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, KS, 67260, USA.