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Torsional Diffusion for Molecular Conformer Generation

NeurIPS 2022 · Image generation › Autoregressive and latent generation · approach: Equivariant diffusion for 3D molecules · 82 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
diffuse only over torsion angles (torsional diffusion) instead of Euclidean diffusion (GeoDiff)conformer generator · GEOM-DRUGSrecall AMR median: 0.809 -> 0.565Helped
diffuse over torsion angles instead of Euclidean, precisionconformer generator · GEOM-DRUGSprecision AMR median: 1.090 -> 0.729Helped
torsional diffusion vs OMEGA commercial softwareconformer generator · GEOM-DRUGSrecall coverage mean: 53.4 -> 72.7Helped
increase denoising steps from 5 to 20 (ablation)Torsional Diffusion · GEOM-DRUGSrecall AMR median: 0.685 -> 0.565Helped
increase denoising steps from 10 to 20 (ablation)Torsional Diffusion · GEOM-DRUGSrecall AMR median: 0.580 -> 0.565No clear effect
use 20 steps instead of 5000 steps of GeoDiffTorsional Diffusion · GEOM-DRUGSruntime (core-secs per conformer): 305 -> 4.90Helped
torsional diffusion vs RDKit on runtimeTorsional Diffusion · GEOM-DRUGSruntime: 0.10 -> 4.90Hurt
torsional diffusion vs baselines on dipole momentTorsional Diffusion · ensemble propertiesmedian error dipole: 0.34 (GeoMol) vs 0.35No clear effect
torsional diffusion for ensemble energy and minimum energyTorsional Diffusion · ensemble propertiesmedian error energy E (kcal/mol): 0.31 (GeoDiff) -> 0.22Helped
torsional Boltzmann generator vs annealed importance samplingTorsional BG · Boltzmann sampling ESSeffective sample size at 1000K: 6.72 (AIS 100 steps) -> 11.42Helped
increase torsional BG steps from 5 to 20 at test time (trained with 5-step resampler) (ablation)Torsional BG · Boltzmann sampling ESSeffective sample size at 1000K: 7.28 -> 11.42Helped
train on ground-truth local structures instead of conformer matching (ablation)Torsional Diffusion · GEOM-DRUGSRMSDHurt

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