isayevlab/geom-drugs-3dgen-evaluation
A refined evaluation pipeline for 3D molecular generative models trained on GEOM-Drugs.
This project helps computational chemists and cheminformaticians rigorously evaluate the chemical accuracy of 3D molecular generative models. It takes outputs from these models (molecular structures in SDF files) and assesses them for chemical stability, geometric accuracy (bond lengths, angles, torsions), and energy improvements after quantum chemical optimization. The result is a comprehensive set of metrics to benchmark and compare different generative models.
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Use this if you are developing or using 3D molecular generative models and need a robust, chemically aware pipeline to benchmark their outputs for stability and geometric realism.
Not ideal if you are looking for a tool to generate molecules, or if you only need simple 2D molecular property calculations.
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Language
Python
License
MIT
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Last pushed
Sep 10, 2025
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