Run a FEP+ binding-affinity campaign over a ligand library

from apex import Aether

simos = Aether(api_key=os.environ["APEX_API_KEY"])

# Score a 120-ligand library across four protein targets using alchemical FEP+.
# Returns relative binding free energies vs the reference ligand and per-edge
# standard error. Run committed for production campaigns.
campaign = simos.fep(
    targets=["pdb:1abc", "pdb:2def", "pdb:3ghi", "pdb:4jkl"],
    library="s3://my-bucket/ligands.sdf",
    reference="ligand_001",
    method="fep+",
    forcefield="opls4",
    convergence={
        "target_se_kcal_per_mol": 0.3,
        "max_wall_time_h": 12,
    },
    committed=True,
)

# Stream results as edges converge.
for edge in campaign.edges(stream=True):
    if edge.converged:
        print(
            f"{edge.target}  {edge.ligand}  "
            f"ddG = {edge.ddg_kcal_per_mol:+.2f}  se = {edge.se:.2f}"
        )

# Top-10 by mean ddG across all four targets.
ranked = campaign.rank(across="targets", policy="mean_ddg_ascending")
for r in ranked[:10]:
    print(r.ligand, r.mean_ddg, r.per_target)