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DFT-level descriptor libraries were constructed to train 2D and 3D graph neural networks for on the-fly the prediction of carboxylic acid and alkyl amine descriptors suitable for statistical modeling of medicinally relevant molecules.more » « lessFree, publicly-accessible full text available January 15, 2026
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Haas, Brittany; Hardy, Melissa; Santhanalakkshmi_Vejaykummar, Shree Sowndarya; Adams, Keir; Coley, Connor W; Paton, Robert; Sigman, Matthew S (, figshare)This Figshare repository contains the datasets and models for our paper titled: Rapid Prediction of Conformationally-Dependent DFT-Level Descriptors using Graph Neural Networks for Carboxylic Acids and Alkyl Amines. It is organized into 2D and 3D, which represent the modeling architectures used in building graph neural networks for molecular descriptors corresponding to acids and amines. Carboxylic acid, primary alkyl amine, and secondary alkyl amine (as well as a combined alkyl amine) libraries are provided in their entirety, including conformer properties. Additional test and external validation statistics for each library are also provided within this repository.more » « less