Use Protenix (AlphaFold3)

The amino acid, DNA, and RNA sequences corresponding to the molecules you want to predict. For complex prediction simply provide multiple sequences in this input and they will all be folded at the same time together. For DNA and RNA sequences enter them in the 5′-->3′ direction. If you wish to model double-stranded DNA, please add a second dna sequence representing the reverse complement strand.

Input small molecules to include in prediction. All inputs are converted to SMILES format, with SMILES strings being the preferred input for optimal results.

See above instructions for information on how to use this input.

Choose whether you want to use an MSA generated using mmseqs2 or if you want to use single sequence mode which leverages language model embeddings instead ("single_sequence"). The single sequence approach is much faster and achieves reasonable accuracy but MSA mode is generally preferred and more accurate. Warning: We query a 3rd party service to perform sequence searches, if you do not wish to share your sequence set this to "single_sequence".

Increased recycling steps tend to produce more accurate predictions but will also greatly increases prediction time. For smaller proteins and monomers we recommend 5 recycles, for bigger proteins we recommend 10 recycles.

The number of sampling steps to use for prediction.

The number of diffusion samples to use for prediction.