AI Article Synopsis

  • * The research utilizes the fragment molecular orbital (FMO) method on a dataset comprising over 5,000 protein structures from the SCOP2 database, resulting in more than 200 million inter-fragment interaction energies.
  • * Multiple basis sets were applied to improve accuracy in energy calculations, and the total dataset size is approximately 6.7 GB, which can aid in functional analyses and machine learning applications related to protein properties.

Article Abstract

The function of a biomacromolecule is not only determined by its three-dimensional structure but also by its electronic state. Quantum chemical calculations are promising non-empirical methods available for determining the electronic state of a given structure. In this study, we used the fragment molecular orbital (FMO) method, which applies to biopolymers such as proteins, to provide physicochemical property values on representative structures in the SCOP2 database of protein families, a subset of the Protein Data Bank. Our dataset was constructed by over 5,000 protein structures, including over 200 million inter-fragment interaction energies (IFIEs) and their energy components obtained by pair interaction energy decomposition analysis (PIEDA) using FMO-MP2/6-31 G*. Moreover, three basis sets, 6-31 G*, 6-31 G**, and cc-pVDZ, were used for the FMO calculations of each structure, making it possible to compare the energies obtained with different basis functions for the same fragment pair. The total data size is approximately 6.7 GB. Our dataset will be useful for functional analyses and machine learning based on the physicochemical property values of proteins.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11499858PMC
http://dx.doi.org/10.1038/s41597-024-03999-2DOI Listing

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