TY - JOUR
T1 - AlphaFold and Implications for Intrinsically Disordered Proteins
AU - Ruff, Kiersten M.
AU - Pappu, Rohit V.
N1 - Funding Information:
We are grateful to our collaborators (Richard Kriwacki, Danny Hatters, Hilal Lashuel, Edward Lemke, and Tanja Mittag), and past and current members of the Pappu lab for their insights, expertise, and efforts in developing and interpreting quantitative sequence-ensemble relationships for IDPs/IDRs. The current perspective benefited from inputs provided by Alan Chen, Furqan Dar, Alex Holehouse, Matthew King, Min Kyung Shinn, and Andreas Vitalis.
Publisher Copyright:
© 2021 The Author(s)
PY - 2021/10/1
Y1 - 2021/10/1
N2 - Accurate predictions of the three-dimensional structures of proteins from their amino acid sequences have come of age. AlphaFold, a deep learning-based approach to protein structure prediction, shows remarkable success in independent assessments of prediction accuracy. A significant epoch in structural bioinformatics was the structural annotation of over 98% of protein sequences in the human proteome. Interestingly, many predictions feature regions of very low confidence, and these regions largely overlap with intrinsically disordered regions (IDRs). That over 30% of regions within the proteome are disordered is congruent with estimates that have been made over the past two decades, as intense efforts have been undertaken to generalize the structure–function paradigm to include the importance of conformational heterogeneity and dynamics. With structural annotations from AlphaFold in hand, there is the temptation to draw inferences regarding the “structures” of IDRs and their interactomes. Here, we offer a cautionary note regarding the misinterpretations that might ensue and highlight efforts that provide concrete understanding of sequence-ensemble-function relationships of IDRs. This perspective is intended to emphasize the importance of IDRs in sequence-function relationships (SERs) and to highlight how one might go about extracting quantitative SERs to make sense of how IDRs function.
AB - Accurate predictions of the three-dimensional structures of proteins from their amino acid sequences have come of age. AlphaFold, a deep learning-based approach to protein structure prediction, shows remarkable success in independent assessments of prediction accuracy. A significant epoch in structural bioinformatics was the structural annotation of over 98% of protein sequences in the human proteome. Interestingly, many predictions feature regions of very low confidence, and these regions largely overlap with intrinsically disordered regions (IDRs). That over 30% of regions within the proteome are disordered is congruent with estimates that have been made over the past two decades, as intense efforts have been undertaken to generalize the structure–function paradigm to include the importance of conformational heterogeneity and dynamics. With structural annotations from AlphaFold in hand, there is the temptation to draw inferences regarding the “structures” of IDRs and their interactomes. Here, we offer a cautionary note regarding the misinterpretations that might ensue and highlight efforts that provide concrete understanding of sequence-ensemble-function relationships of IDRs. This perspective is intended to emphasize the importance of IDRs in sequence-function relationships (SERs) and to highlight how one might go about extracting quantitative SERs to make sense of how IDRs function.
KW - AlphaFold
KW - cautionary notes
KW - intrinsically disordered proteins
UR - http://www.scopus.com/inward/record.url?scp=85113526526&partnerID=8YFLogxK
U2 - 10.1016/j.jmb.2021.167208
DO - 10.1016/j.jmb.2021.167208
M3 - Review article
C2 - 34418423
AN - SCOPUS:85113526526
SN - 0022-2836
VL - 433
JO - Journal of Molecular Biology
JF - Journal of Molecular Biology
IS - 20
M1 - 167208
ER -