Examples¶
End-to-end, copy-pasteable examples in curl and Python, for the three common tasks: a plain fold, a co-fold with affinity, and a binder design. All use the async submit → poll → download flow.
BASE = https://api.japanfold.com
Fold a protein¶
curl¶
BASE=https://api.japanfold.com
JOB=$(curl -s -X POST $BASE/v1/predictions \
-H 'Content-Type: application/json' \
-d '{"model":"boltz2","name":"myprotein","sequence":"MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQ"}' \
| python3 -c 'import sys,json; print(json.load(sys.stdin)["id"])')
# poll (Prefer: wait blocks up to 60s per call)
until curl -s -H 'Prefer: wait=60' $BASE/v1/jobs/$JOB \
| grep -qE '"status":"(succeeded|failed|canceled)"'; do :; done
curl -s $BASE/v1/jobs/$JOB/results
curl -s $BASE/v1/jobs/$JOB/archive -o myprotein.zip && unzip -oq myprotein.zip -d myprotein
Python: stdlib only (no dependencies)¶
import json, time, urllib.request
BASE = "https://api.japanfold.com"
# The edge blocks urllib's default User-Agent as a bot — send a browser-like one.
HEADERS = {"Content-Type": "application/json", "User-Agent": "Mozilla/5.0"}
def api(method, path, body=None):
data = json.dumps(body).encode() if body is not None else None
req = urllib.request.Request(BASE + path, data=data, method=method, headers=HEADERS)
with urllib.request.urlopen(req) as r:
return json.load(r)
def wait(job_id):
while True:
job = api("GET", f"/v1/jobs/{job_id}")
if job["status"] in ("succeeded", "failed", "canceled"):
return job
time.sleep(5)
job = api("POST", "/v1/predictions",
{"model": "boltz2", "name": "myprotein",
"sequence": "MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQ"})
job = wait(job["id"])
assert job["status"] == "succeeded", job.get("error")
results = api("GET", f"/v1/jobs/{job['id']}/results")
for row in results["rows"]:
print(row["id"], "plddt=", row.get("plddt"), "ptm=", row.get("ptm"))
# download the zip bundle (urlretrieve doesn't take headers, so open it directly)
req = urllib.request.Request(BASE + results["archive_url"], headers=HEADERS)
with urllib.request.urlopen(req) as r, open("myprotein.zip", "wb") as f:
f.write(r.read())
Python: httpx¶
import time, httpx
BASE = "https://api.japanfold.com"
with httpx.Client(base_url=BASE, timeout=120) as c:
job = c.post("/v1/predictions", json={
"model": "boltz2", "name": "myprotein",
"sequence": "MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQ"}).json()
while job["status"] not in ("succeeded", "failed", "canceled"):
time.sleep(5)
job = c.get(f"/v1/jobs/{job['id']}").json()
results = c.get(f"/v1/jobs/{job['id']}/results").json()
print(results["rows"])
with open("myprotein.zip", "wb") as f:
f.write(c.get(results["archive_url"]).content)
Co-fold a protein + ligand, with affinity¶
Only Boltz-2 does affinity. Provide the complex as a Boltz YAML input
string with a ligand chain and a properties: affinity block.
curl¶
BASE=https://api.japanfold.com
read -r -d '' PAYLOAD <<'JSON'
{
"model": "boltz2",
"name": "prot-ligand",
"input": "sequences:\n - protein: {id: A, sequence: MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQ}\n - ligand: {id: L, smiles: \"CC(=O)Oc1ccccc1C(=O)O\"}\nproperties:\n - affinity: {binder: L}\n",
"params": {"use_msa_server": true}
}
JSON
JOB=$(curl -s -X POST $BASE/v1/predictions -H 'Content-Type: application/json' \
-d "$PAYLOAD" | python3 -c 'import sys,json; print(json.load(sys.stdin)["id"])')
curl -s -H 'Prefer: wait=120' $BASE/v1/jobs/$JOB # affinity runs take longer
curl -s $BASE/v1/jobs/$JOB/results
curl -s $BASE/v1/jobs/$JOB/archive -o prot-ligand.zip
Python: httpx¶
import time, httpx
BASE = "https://api.japanfold.com"
YAML = (
"sequences:\n"
" - protein: {id: A, sequence: MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQ}\n"
" - ligand: {id: L, smiles: \"CC(=O)Oc1ccccc1C(=O)O\"}\n"
"properties:\n"
" - affinity: {binder: L}\n"
)
with httpx.Client(base_url=BASE, timeout=180) as c:
job = c.post("/v1/predictions", json={
"model": "boltz2", "name": "prot-ligand",
"input": YAML, "params": {"use_msa_server": True}}).json()
while job["status"] not in ("succeeded", "failed", "canceled"):
time.sleep(5)
job = c.get(f"/v1/jobs/{job['id']}").json()
print(c.get(f"/v1/jobs/{job['id']}/results").json()["rows"])
The result rows include affinity fields alongside the structure/confidence
scores.
Binder design¶
De-novo binders with BoltzGen via POST /v1/designs. Poll and download like a
prediction; the results carry ranked designs.
curl¶
BASE=https://api.japanfold.com
read -r -d '' PAYLOAD <<'JSON'
{
"protocol": "nanobody-anything",
"name": "my-nanobodies",
"spec": "sequences:\n - protein: {id: A, sequence: MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQ}\n",
"params": {"num_designs": 10, "budget": 10, "fast": true}
}
JSON
JOB=$(curl -s -X POST $BASE/v1/designs -H 'Content-Type: application/json' \
-d "$PAYLOAD" | python3 -c 'import sys,json; print(json.load(sys.stdin)["id"])')
until curl -s $BASE/v1/jobs/$JOB \
| grep -qE '"status":"(succeeded|failed|canceled)"'; do sleep 10; done
curl -s $BASE/v1/jobs/$JOB/results
curl -s $BASE/v1/jobs/$JOB/archive -o designs.zip && unzip -oq designs.zip -d designs
Python: httpx¶
import time, httpx
BASE = "https://api.japanfold.com"
with httpx.Client(base_url=BASE, timeout=300) as c:
job = c.post("/v1/designs", json={
"protocol": "nanobody-anything", "name": "my-nanobodies",
"spec": "sequences:\n - protein: {id: A, sequence: MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQ}\n",
"params": {"num_designs": 10, "budget": 10, "fast": True}}).json()
while job["status"] not in ("succeeded", "failed", "canceled"):
time.sleep(10)
job = c.get(f"/v1/jobs/{job['id']}").json()
results = c.get(f"/v1/jobs/{job['id']}/results").json()
print(results.get("designs"))
with open("designs.zip", "wb") as f:
f.write(c.get(results["archive_url"]).content)