Institute of Biomedical Engineering, University of Toronto, 164 College Street, Toronto, ON, Canada M5S 3E2
| Received 28 Jan 2022 |
Accepted 20 Mar 2022 |
Published 15 Apr 2022 |
A major advancement has recently occurred in the ability to predict protein secondary structure from sequence using artificial neural networks. This new accessibility to high-quality predicted structures provides a big opportunity for the protein design community. It is particularly welcome for membrane protein design, where the scarcity of solved structures has been a major limitation of the field for decades. Here, we review the work done to date on the membrane protein design and set out established and emerging tools that can be used to most effectively exploit this new access to structures.
