AlphaFold2: A Role for Disordered Protein/Region Prediction?

By Carter J. Wilson, Wing Yiu Choy, Mikko Karttunen. 2022

136 citations recorded by the source corpus.

The development of AlphaFold2 marked a paradigm-shift in the structural biology community. Herein, we assess the ability of AlphaFold2 to predict disordered regions against traditional sequence-based disorder predictors. We find that AlphaFold2 performs well at discriminating disordered regions, but also note that the disorder predictor one constructs from an AlphaFold2 structure determines accuracy. In particular, a naïve, but non-trivial assumption that residues assigned to helices, strands, and H-bond stabilized turns are likely ordered and all other residues are disordered results in a dramatic overestimation in disorder; conversely, the predicted local distance difference test (pLDDT) provides an excellent measure of residue-wise disorder. Furthermore, by employing molecular dynamics (MD) simulations, we note an interesting relationship between the pLDDT and secondary structure, that may explain our observations and suggests a broader application of the pLDDT for characterizing the local dynamics of intrinsically disordered proteins and regions (IDPs/IDRs).

Subfields: Materials Chemistry, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Materials Chemistry

1. Jianzhu Ma
2. Jian Peng
3. Bonnie Berger
4. Shitong Luo
5. Jinbo Xu
6. Sheng Wang
7. Liisa Holm

In Molecular Biology

1. Jianzhu Ma
2. Jian Peng
3. Jinbo Xu
4. Bonnie Berger
5. Shitong Luo
6. Sheng Wang
7. Shiwang Liu
8. Siqi Sun

Citations in the corpus

• High-resolution de novo structure prediction from primary sequence (2022, methodology): “Furthermore, many methods have since built upon AlphaFold2 for other prediction tasks in structural biology, including protein-protein interactions, disordered regions, and binding sites ( 17 – 20 ).”