How to predict structures with AlphaFold
From Proteopedia
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3. Paste in your sequence, making sure to completely replace the default sequence: | 3. Paste in your sequence, making sure to completely replace the default sequence: | ||
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This input slot can accept sequences >1,000 amino acids, even though it is only one line. | This input slot can accept sequences >1,000 amino acids, even though it is only one line. | ||
==References and Notes== | ==References and Notes== | ||
<references /> | <references /> | ||
Revision as of 20:40, 17 October 2021
In 2020, the AlphaFold project of Google's DeepMind team demonstrated a major breakthrough in predicting protein structure from sequence. Their success in the blind CASP competition astonished many experts. For an overview, see Theoretical models.
In July, 2021, DeepMind released AlphaFold as open source code. Subsequently, several Colabs became available offering free structure prediction for user-submitted protein sequences. These Google Colabs (collaboratories)[1]. enable users to submit sequences via web browser, executing the code in the Google cloud, using space private to each user, returning predicted structures.
Below are instructions for beginners who wish to predict structures. We recommend the "advanced" Colab by Sergey Ovchinnikov, Milot Mirdita and Martin Steinegger.
Instructions
1. Obtain the sequence of the protein of interest, e.g. at UniProt.
2. Login at AlphaFold2_advanced. Registration is free.
3. Paste in your sequence, making sure to completely replace the default sequence:
This input slot can accept sequences >1,000 amino acids, even though it is only one line.
References and Notes
- ↑ Collaboratory FAQ at Google.
