Predicting with Boltz-1
Click on 'Add protein', 'Add DNA', 'Add RNA' or 'Add ligand' to enter the corresponding sequences, CCD codes or ligand SMILES strings.
Click 'Add modification' if you want to alter the sequences (for proteins, DNA or RNA), and enter the position (the residue index) and the CCD code of the modification.
Click 'Start prediction'.
Calculations are performed on a dedicated A100 GPU in the cloud and use computing credits. A typical structure prediction with Boltz-1 will cost between 0.5 and 1 computing credit. You can obtain computing credits there.
[1] Jeremy Wohlwend, Gabriele Corso, Saro Passaro, Mateo Reveiz, Ken Leidal, Wojtek Swiderski, Tally Portnoi, Itamar Chinn, Jacob Silterra, Tommi Jaakkola, Regina Barzilay. Boltz-1: Democratizing Biomolecular Interaction Modeling. https://www.biorxiv.org/content/10.1101/2024.11.19.624167v1.
Predicting with Chai-1
Click on 'Add protein', 'Add DNA', 'Add RNA' or 'Add ligand' to enter the corresponding sequences or SMILES strings.
Click 'Add pocket restraint' if you want to add a distance restraint between a residue (for proteins, DNA or RNA) and a chain.
Click 'Add contact restraint' if you want to add a distance restraint between two residues.
Click 'Start prediction'.
Calculations are performed on a dedicated A100 GPU in the cloud and use computing credits. A typical structure prediction with Chai-1 will cost between 0.5 and 1 computing credit. You can obtain computing credits there.
[1] https://www.chaidiscovery.com/blog/introducing-chai-1.
Predicting with AlphaFold 2
Enter one or more FASTA files, choose the AlphaFold model (monomer, multimer, etc.) and the database for multiple sequence alignment, and click 'Start prediction'.
Predictions are performed using a choice of cloud machines with varying performances and costs, including powerful instances with A100 GPUs.
You can obtain computing credits there.
Any publication that discloses findings arising from using the AlphaFold service should cite the AlphaFold paper and, if applicable, the AlphaFold-Multimer paper.
https://doi.org/10.1038/s41586-021-03819-2