Side-chain cross conflicts in the example complex interface when run locally.

[zardda]

[zardda]

use the example code:
from esm.models.esmfold2 import (
DNAInput,
ESMFold2InputBuilder,
LigandInput,
Modification,
ProteinInput,
StructurePredictionInput,
)
from transformers.models.esmfold2.modeling_esmfold2 import ESMFold2Model

HHAI_SEQ = (
"MIEIKDKQLTGLRFIDLFAGLGGFRLALESCGAECVYSNEWDKYAQEVYEMNFGEKPEGDITQVNEKTIPDH"
"DILCAGFPCQAFSISGKQKGFEDSRGTLFFDIARIVREKKPKVVFMENVKNFASHDNGNTLEVVKNTMNELD"
"YSFHAKVLNALDYGIPQKRERIYMICFRNDLNIQNFQFPKPFELNTFVKDLLLPDSEVEHLVIDRKDLVMTN"
"QEIEQTTPKTVRLGIVGKGGQGERIYSTRGIAITLSAYGGGIFAKTGGYLVNGKTRKLHPRECARVMGYPDS"
"YKVHPSTSQAYKQFGNSVVINVLQYIAYNIGSSLNFKPY"
)

model = ESMFold2Model.from_pretrained("biohub/ESMFold2").cuda().eval()

spi = StructurePredictionInput(
sequences=[
ProteinInput(id="A", sequence=HHAI_SEQ),
DNAInput(
id="B",
sequence="GATAGCGCTATC",
modifications=[Modification(position=5, ccd="C36")],
),
DNAInput(
id="C",
sequence="TGATAGCGCTATC",
modifications=[Modification(position=6, ccd="C36")],
),
LigandInput(id="L", ccd=["SAH"]),
]
)

result = ESMFold2InputBuilder().fold(
model, spi, num_loops=3, num_sampling_steps=50, num_diffusion_samples=1, seed=0
)

print(f"pLDDT mean: {float(result.plddt.mean()):.3f}, pTM: {float(result.ptm):.3f}, ipTM: {float(result.iptm):.3f}")

with open("1mht_pred.cif", "w") as f:
f.write(result.complex.to_mmcif())