Varadi, M;
Bordin, N;
Orengo, C;
Velankar, S;
(2023)
The opportunities and challenges posed by the new generation of deep learning-based protein structure predictors.
Current Opinion in Structural Biology
, 79
, Article 102543. 10.1016/j.sbi.2023.102543.
(In press).
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Abstract
The function of proteins can often be inferred from their three-dimensional structures. Experimental structural biologists spent decades studying these structures, but the accelerated pace of protein sequencing continuously increases the gaps between sequences and structures. The early 2020s saw the advent of a new generation of deep learning-based protein structure prediction tools that offer the potential to predict structures based on any number of protein sequences. In this review, we give an overview of the impact of this new generation of structure prediction tools, with examples of the impacted field in the life sciences. We discuss the novel opportunities and new scientific and technical challenges these tools present to the broader scientific community. Finally, we highlight some potential directions for the future of computational protein structure prediction.
| Type: | Article |
|---|---|
| Title: | The opportunities and challenges posed by the new generation of deep learning-based protein structure predictors |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.sbi.2023.102543 |
| Publisher version: | https://doi.org/10.1016/j.sbi.2023.102543 |
| Language: | English |
| Additional information: | © 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/). |
| Keywords: | Protein Structure Predictions, Deep learning, Structural biology, Structural Bioinformatics. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Structural and Molecular Biology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10165768 |
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