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HIF-2α Inhibitors (Synthetic Library) — Ligand–Receptor Complexes

69 computationally designed small-molecule ligands docked into Hypoxia-inducible factor 2-alpha (HIF-2α / EPAS1), each provided as a single-file protein–ligand complex in PDB format (69 unique ligand structures).

HIF-2α (EPAS1) drives the hypoxic transcriptional program; small molecules that occupy the buried cavity of its PAS-B domain are clinically validated in clear-cell renal cell carcinoma (e.g., belzutifan).

Receptor note: coordinates correspond to the HIF-2α PAS-B domain (chain A res 239–348). TODO: add the source RCSB PDB accession for the receptor template used to generate these complexes.

Dataset summary

Complex files 69 (*_cmpx.pdb)
Unique ligand SMILES 69
Receptor HIF-2α PAS-B domain (chain A res 239–348)
Generator Technetium structure-based docking pipeline (AutoDock Vina)
Pose scoring AutoDock Vina

These are candidate small molecules docked into the target pocket and scored with AutoDock Vina. Poses are provided as protein–ligand complexes for downstream structure-based analysis.

Each complex file is self-contained — receptor structure, the ligand's 3D docked pose, and a 2D↔3D atom map all travel inside the single PDB.

Property profile

Physicochemical ranges are computed with RDKit over the 69 unique ligand structures; docking energy is from the generation/docking pipeline.

Property Range Median
Docking energy (AutoDock Vina) ≤ -10.3 kcal/mol (down to -10.8)
Molecular weight 255.3 – 299.4 Da 285.3
cLogP 0.4 – 4.0 2.8
TPSA 27.1 – 100.9 Ų 53.1
Fsp3 (fraction sp³ C) 0.2 – 0.6 0.3
H-bond donors 0 – 3 1
H-bond acceptors 2 – 6 3
Rotatable bonds 1 – 4 1

File format

Each *_cmpx.pdb bundles the receptor and one docked ligand pose:

Record Content
REMARK VINA RESULT <energy> … AutoDock Vina docking score (kcal/mol)
REMARK SMILES <smiles> the docked ligand (2D structure)
REMARK SMILES IDX <pos> <serial> … map of each SMILES heavy-atom position ↔ its ligand atom serial (the 2D↔3D key)
ATOM … <chain> receptor heavy atoms
ATOM … UNL (after MODEL 1) ligand 3D pose (residue name UNL)

Usage

import glob

def read_complex(path):
    smiles, idx = None, {}
    with open(path) as fh:
        for line in fh:
            if line.startswith("REMARK SMILES IDX"):
                toks = line.split()[3:]            # flat list of (smiles_pos, atom_serial)
                for i in range(0, len(toks), 2):
                    idx[int(toks[i])] = int(toks[i + 1])
            elif line.startswith("REMARK SMILES"):
                smiles = line.split(None, 2)[2].strip()
    return smiles, idx                              # idx[smiles_atom_position] -> ligand atom serial

for f in glob.glob("*_cmpx.pdb"):
    smi, idx = read_complex(f)
    # ligand atoms are the `ATOM ... UNL` records following `MODEL 1`

Provenance & intended use

  • These are computationally generated designs and docked poses — not experimentally validated binders. No claim of activity or selectivity is made.
  • Intended for machine-learning, cheminformatics, generative-model benchmarking, and docking-pose research on a well-defined target.

Citation

Generated by Technetium Therapeutics. Poses scored with AutoDock Vina.

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