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GINGER - Graph Internal-coordinate Neural-network conformer Generator with Energy Refinement for Large Chemical Libraries


Conformer generation is an essential step of a variety of molecular modeling and computer-assisted drug discovery workflows such as 3D ligand-based virtual screening or fast GPU docking. GINGER (Graph Internal-coordinate Neural-network conformer Generator with Energy Refinement) is Molsoft's new cutting-edge software designed for lightning-fast high quality conformer library generation on GPUs. You can try a demo of GINGER here.


Eugene Raush Ruben Abagyan, and Maxim Totrov - Efficient Generation of Conformer Ensembles Using Internal Coordinates and a Generative Directional Graph Convolution Neural Network J. Chem. Theory Comput. 2024

Key Features:



MolSoft has conducted extensive testing on GINGER and a publication is expected soon. The benchmark standard for conformer generation is 'Platinum' (Friedrich et al JCIM 2017). Typically, recovery rates are reported at 0.5 / 1.0 / 1.5 Angstrom Root Mean Square Deviation (RMSD) from the bioactive conformation within an ensemble of approximately 30 conformations - considered a reasonable size for downstream applications such as RIDE and RIDGE. Our current results demonstrate recovery rates of 45% / 80% / 93% for ensembles as small as 20 conformations on average. The median RMSD from the bioactive conformation to the closest conformation within the Ginger ensemble is 0.54 A. These results were achieved using standard GINGER settings and were validated across a benchmark dataset comprising 2859 compounds.


GINGER is a separate add-on module to MolSoft's desktop modeling software ICM-Pro and ICM-Chemist-Pro or can be run by MolSoft as a service. Please contact MolSoft with any questions and to obtain an evaluation license or to purchase GINGER.