AlphaFold and Implications for Intrinsically Disordered Proteins. Issue 20 (1st October 2021)
- Record Type:
- Journal Article
- Title:
- AlphaFold and Implications for Intrinsically Disordered Proteins. Issue 20 (1st October 2021)
- Main Title:
- AlphaFold and Implications for Intrinsically Disordered Proteins
- Authors:
- Ruff, Kiersten M.
Pappu, Rohit V. - Abstract:
- Graphical abstract: Highlights: Predicted structures generated by AlphaFold, highlight the importance of IDRs. Caution is essential when using predicted "structures" for inferring IDR functions. We highlight the importance of quantitative sequence-ensemble relationships for IDRs. We showcase insights from specific examples of sequence-ensemble relationships. Abstract: 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 provideGraphical abstract: Highlights: Predicted structures generated by AlphaFold, highlight the importance of IDRs. Caution is essential when using predicted "structures" for inferring IDR functions. We highlight the importance of quantitative sequence-ensemble relationships for IDRs. We showcase insights from specific examples of sequence-ensemble relationships. Abstract: 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. … (more)
- Is Part Of:
- Journal of molecular biology. Volume 433:Issue 20(2021)
- Journal:
- Journal of molecular biology
- Issue:
- Volume 433:Issue 20(2021)
- Issue Display:
- Volume 433, Issue 20 (2021)
- Year:
- 2021
- Volume:
- 433
- Issue:
- 20
- Issue Sort Value:
- 2021-0433-0020-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-10-01
- Subjects:
- AlphaFold -- intrinsically disordered proteins -- cautionary notes
Molecular biology -- Periodicals
Biology -- Periodicals
Biochemistry -- Periodicals
Bacteriology -- Periodicals
Molecular Biology -- Periodicals
Biochemistry -- Periodicals
Biologie moléculaire -- Périodiques
Biologie -- Périodiques
Biochimie -- Périodiques
Moleculaire biologie
Biochemistry
Biology
Molecular biology
Periodicals
572.805 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00222836 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jmb.2021.167208 ↗
- Languages:
- English
- ISSNs:
- 0022-2836
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5020.700000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 19615.xml