A quantum chemical interaction energy dataset for accurately modeling protein-ligand interactions

• Published in: Scientific data Vol. 10; no. 1; pp. 619 - 14
• Main Authors: Spronk, Steven A., Glick, Zachary L., Metcalf, Derek P., Sherrill, C. David, Cheney, Daniel L.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 12-09-2023; Nature Publishing Group; Nature Portfolio
• Subjects: 639/638/563/606; 639/638/563/980; Data Descriptor; Datasets; Humanities and Social Sciences; Ligands; multidisciplinary; Science; Science (multidisciplinary)
• ISSN: 2052-4463; 2052-4463
• DOI: 10.1038/s41597-023-02443-1

Fast and accurate calculation of intermolecular interaction energies is desirable for understanding many chemical and biological processes, including the binding of small molecules to proteins. The Splinter [“
S
ymmetry-adapted perturbation theory (SAPT0)
p
rotein-
l
igand
inter
action”] dataset has been created to facilitate the development and improvement of methods for performing such calculations. Molecular fragments representing commonly found substructures in proteins and small-molecule ligands were paired into >9000 unique dimers, assembled into numerous configurations using an approach designed to adequately cover the breadth of the dimers’ potential energy surfaces while enhancing sampling in favorable regions. ~1.5 million configurations of these dimers were randomly generated, and a structurally diverse subset of these were minimized to obtain an additional ~80 thousand local and global minima. For all >1.6 million configurations, SAPT0 calculations were performed with two basis sets to complete the dataset. It is expected that Splinter will be a useful benchmark dataset for training and testing various methods for the calculation of intermolecular interaction energies.