Update README.md

Author: joewatchwell

README.md

@@ -368,6 +368,25 @@ This just scales the amount of noise we add to the translations (`noise_scale_ca
 
 An additional example of PPI with fold conditioning is available here: `./examples/design_ppi_scaffolded.sh`
 
+In [Liu et al., 2024](https://www.biorxiv.org/content/10.1101/2024.07.16.603789v1), we demonstrate that RFdiffusion can be used to design binders to flexible peptides, where the 3D coordinates of the peptide *are not* specified, but the secondary structure can be. This allows a user to design binders to a peptide in e.g. either a helical or beta state.
+
+The principle here is that we provide an input pdb structure of a peptide, but specify that we want to mask the 3D structure:
+
+```
+inference.input_pdb=input_pdbs/tau_peptide.pdb 'contigmap.contigs=[70-100/0 B165-178]' 'contigmap.inpaint_str=[B165-178]'
+```
+
+Here, we're making 70-100 amino acid binders to the tau peptide (pdb indices B165-178), and we mask the structure with `configmap.inpaint_str` on this peptide. However, we can then specify that we want it to adopt a beta (strand) secondary structure:
+
+```
+scaffoldguided.scaffoldguided=True 'contigmap.inpaint_str_strand=[B165-178]'
+```
+
+Alternatively, you could specify `contigmap.inpaint_str_helix` to make it a helix!
+
+See the example in `examples/design_ppi_flexible_peptide_with_secondarystructure_specification.sh`.
+
+
 ---
 
 ### Generation of Symmetric Oligomers