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Novel Myosin Motor Modulators — GA-II Designed Ligand–Receptor Complexes

Why this target matters. Direct myosin modulation is the first therapeutic strategy to target cardiac contractility at the motor protein itself, a mechanism validated clinically by mavacamten's approval in hypertrophic cardiomyopathy.

22 small molecules generated de novo by the Technetium TC-43.ai engine (GA-II), conditioned on the allosteric modulator site of the myosin motor domain. Each molecule was constructed against this pocket rather than selected from a compound library — docking (AutoDock Vina) came afterwards, to place and score the generated molecules in the site. Every design is supplied as a single-file protein–ligand complex in PDB format (21 unique ligand structures).

The myosin motor domain is the force-generating ATPase of muscle; allosteric small-molecule modulators of cardiac/skeletal myosin are an established cardiomyopathy modality (e.g., mavacamten).

Receptor note: coordinates correspond to the myosin motor domain (chain A res 33–782). TODO: add the source RCSB PDB accession for the receptor template used to generate these complexes.

Dataset summary

Complex files 22 (*_cmpx.pdb)
Unique ligand SMILES 21
Receptor myosin motor domain (chain A res 33–782)
Generator Technetium GA-II pocket-conditioned generative platform
Generation date 2025-09-13 – 2025-09-28
Pose scoring AutoDock Vina

These are de novo, scaffold-constrained generative designs produced by the Technetium GA-II pocket-conditioned generative platform. Each design is docked into the target pocket and scored with AutoDock Vina; a REMARK CORE record preserves the scaffold/attachment context.

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 21 unique ligand structures; docking energy is from the generation/docking pipeline.

Property Range Median
Docking energy (AutoDock Vina) ≤ -10.9 kcal/mol (down to -14.4)
Molecular weight 333.4 – 498.6 Da 420.5
cLogP 1.8 – 3.9 3.5
TPSA 68.8 – 99.5 Ų 87.9
Fsp3 (fraction sp³ C) 0.2 – 0.5 0.4
H-bond donors 1 – 2 1
H-bond acceptors 4 – 8 6
Rotatable bonds 3 – 7 5

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 CORE <smiles> the scaffold / attachment context of the design
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)

A combined SMILES index (Novel Myosin Motor Inhibitors.smi, SMILES<TAB>compound-id) is included for quick cheminformatics use.

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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