add .sh examples, gabarap pdb, import numpy

examples/design_macrocyclic_binder.sh

@@ -0,0 +1,19 @@
+#!/bin/bash
+
+prefix=./outputs/diffused_binder_cyclic2
+
+# Note that the indices in this pdb file have been 
+# shifted by +2 in chain A relative to pdbID 7zkr.
+pdb='./input_pdbs/7zkr_GABARAP.pdb'
+
+num_designs=10
+script="../scripts/run_inference.py"
+$script --config-name base \
+inference.output_prefix=$prefix \
+inference.num_designs=$num_designs \
+'contigmap.contigs=[12-18 A3-117/0]' \
+inference.input_pdb=$pdb \
+inference.cyclic=True \
+diffuser.T=50 \
+inference.cyc_chains='a' \
+ppi.hotspot_res=[\'A51\',\'A52\',\'A50\',\'A48\',\'A62\',\'A65\'] \

examples/design_macrocyclic_monomer.sh

@@ -0,0 +1,17 @@
+#!/bin/bash 
+
+prefix=./outputs/uncond_cycpep
+# Note that the indices in this pdb file have been 
+# shifted by +2 in chain A relative to pdbID 7zkr.
+pdb='./input_pdbs/7zkr_GABARAP.pdb'
+
+num_designs=10
+script="../scripts/run_inference.py"
+$script --config-name base \
+inference.output_prefix=$prefix \
+inference.num_designs=$num_designs \
+'contigmap.contigs=[12-18]' \
+inference.input_pdb=$pdb \
+inference.cyclic=True \
+diffuser.T=50 \
+inference.cyc_chains='a'

rfdiffusion/Embeddings.py

@@ -8,6 +8,7 @@ from rfdiffusion.util_module import Dropout, create_custom_forward, rbf, init_le
 from rfdiffusion.Attention_module import Attention, FeedForwardLayer, AttentionWithBias
 from rfdiffusion.Track_module import PairStr2Pair
 import math
+import numpy as np 
 
 # Module contains classes and functions to generate initial embeddings
 

rfdiffusion/util_module.py

@@ -98,7 +98,7 @@ def rbf(D):
     RBF = torch.exp(-((D_expand - D_mu) / D_sigma)**2)
     return RBF
 
-def get_seqsep(idx):
+def get_seqsep(idx, cyclic=None):
     '''
     Input:
         - idx: residue indices of given sequence (B,L)