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article · Science · 2023

Accurate proteome-wide missense variant effect prediction with AlphaMissense

Jun Cheng, Guido Novati, Joshua Pan, Clare Bycroft, Akvilė Žemgulytė, Taylor Applebaum, Alexander Pritzel, Lai Hong Wong, Michal Zielinski, Tobias Sargeant, Rosalia G. Schneider, Andrew Senior, John Jumper, Demis Hassabis, Pushmeet Kohli, Žiga Avsec

Cited by 1,759Abstract and details only

Abstract

The vast majority of missense variants observed in the human genome are of unknown clinical significance. We present AlphaMissense, an adaptation of AlphaFold fine-tuned on human and primate variant population frequency databases to predict missense variant pathogenicity. By combining structural context and evolutionary conservation, our model achieves state-of-the-art results across a wide range of genetic and experimental benchmarks, all without explicitly training on such data. The average pathogenicity score of genes is also predictive for their cell essentiality, capable of identifying short essential genes that existing statistical approaches are underpowered to detect. As a resource to the community, we provide a database of predictions for all possible human single amino acid substitutions and classify 89% of missense variants as either likely benign or likely pathogenic.

Cite this paper

APA 7

Cheng, J., Novati, G., Pan, J., Bycroft, C., Žemgulytė, A., Applebaum, T., Pritzel, A., Wong, L. H., Zielinski, M., Sargeant, T., Schneider, R. G., Senior, A., Jumper, J., Hassabis, D., Kohli, P., & Avsec, Ž. (2023). Accurate proteome-wide missense variant effect prediction with AlphaMissense. Science, 381(6664), eadg7492. https://doi.org/10.1126/science.adg7492

MLA 9

Cheng, Jun, et al. “Accurate proteome-wide missense variant effect prediction with AlphaMissense.” Science, vol. 381, no. 6664, 2023, p. eadg7492, https://doi.org/10.1126/science.adg7492.

Chicago

Cheng, Jun, Guido Novati, Joshua Pan, Clare Bycroft, Akvilė Žemgulytė, Taylor Applebaum, Alexander Pritzel, et al. 2023. “Accurate proteome-wide missense variant effect prediction with AlphaMissense.” Science 381 (6664): eadg7492. https://doi.org/10.1126/science.adg7492.

Harvard

Cheng, J. et al. (2023) ‘Accurate proteome-wide missense variant effect prediction with AlphaMissense’, Science, 381(6664), p. eadg7492. Available at: https://doi.org/10.1126/science.adg7492.

BibTeX
@article{cheng2023accurate,
  title = {{Accurate proteome-wide missense variant effect prediction with AlphaMissense}},
  author = {Cheng, Jun and Novati, Guido and Pan, Joshua and Bycroft, Clare and Žemgulytė, Akvilė and Applebaum, Taylor and Pritzel, Alexander and Wong, Lai Hong and Zielinski, Michal and Sargeant, Tobias and Schneider, Rosalia G. and Senior, Andrew and Jumper, John and Hassabis, Demis and Kohli, Pushmeet and Avsec, Žiga},
  journal = {Science},
  volume = {381},
  number = {6664},
  pages = {eadg7492},
  year = {2023},
  doi = {10.1126/science.adg7492}
}

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