Equivalent Distance Geometry Error for Molecular Conformation Comparison. (arXiv:2201.08714v1 [q-bio.BM])

Straight-forward conformation generation models, which generate 3-D
structures directly from input molecular graphs, play an important role in
various molecular tasks with machine learning, such as 3D-QSAR and virtual
screening in drug design. However, existing loss functions in these models
either cost overmuch time or fail to guarantee the equivalence during
optimization, which means treating different items unfairly, resulting in poor
local geometry in generated conformation. So, we propose Equivalent Distance
Geometry Error (EDGE) to calculate the differential discrepancy between …

arxiv bio comparison geometry