SMA Research Platform

Evidence graph for Spinal Muscular Atrophy

Biology-first target discovery
Christian Fischer / Bryzant Labs
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Molecular Docking

COMPUTATIONAL

Pharmacophore-based docking score prediction for SMA drug candidates against SMN2 target binding pockets. Scores compounds by shape complementarity, H-bond potential, hydrophobic match, electrostatic alignment, and strain penalty.

How does docking scoring work?

Docking scores predict how well a small molecule fits into a protein binding pocket. Higher composite scores indicate better predicted binding. Binding class: strong (composite ≥ 0.7, high-confidence), moderate (0.4–0.7, worth investigating), weak(< 0.4).

Sub-scores. Shape — geometric fit. H-Bond— donor/acceptor complementarity. Hydrophobic — contact area. Electrostatic — charge complementarity. Strain— penalty for unfavorable ligand conformation (lower is better). Benchmark: riluzole scores +0.082 against its best target.

Data source:sma-research/docking/— diffdock_results.json, vina_scores.json, per-campaign pocket folders
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