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QTAIM analysis dataset for non-covalent interactions in furan clusters.

ABSTRACT: Furan clusters are very important to understand the dynamics and properties of the furan solvent. They can be used combined with quantum cluster equilibrium theory to theoretically determine the thermodynamics properties of the furan solvent. To understand the structures of the furan clusters, one needs to understand the non-covalent interactions that hold the furan molecules together. In this paper, we have provided the data necessary to understand the non-covalent interactions in furan clusters. Firstly, the structures of the furan clusters have been generated using classical molecular dynamics as implemented in the ABCluster code. Secondly, the generated structures have been fully optimized at the MP2/aug-cc-pVDZ level of theory. The optimized Cartesian coordinates of all the investigated structures are reported in this work to enable further investigations of the furan clusters. These Cartesian coordinates will save computational time for all further investigations involving the furan clusters. Thirdly, to understand the nature of the non-covalent interactions in furan clusters, we have performed a quantum theory of atoms in molecule (QTAIM) analysis using AIMAll program. Using QTAIM, we have provided the critical points, bond paths and their related properties for all the investigated structures. These data can be used to identify and classify the non-covalent interactions in furan clusters. The reader can refer to the original article for further information and discussion of the data provided herein Malloum and Conradie (2022) [1].

SUBMITTER: Malloum A

PROVIDER: S-EPMC8718740 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:A vast number of non-covalent interaction energies at the counterpoise corrected CCSD(T) level have been collected from the literature to build a diverse new dataset. The whole dataset, which consists of 2027 CCSD(T) energies, includes most of the published data at this level. A large subset of the data was then used to train a novel, B3LYP specific, empirical correction scheme for non-covalent interactions and basis set superposition error (abbreviated as B3LYP-MM). Results obtained with our new correction scheme were directly compared to benchmark results obtained with B3LYP-D3(1) and M06-2X(2) (two popular density functions designed specifically to accurately model non-covalent interactions). For non-covalent complexes dominated by dispersion or dipole-dipole interactions all three tested methods give accurate results with the medium size aug-cc-pVDZ(3-6) basis set with MUE's of 0.27 (B3LYP-MM), 0.32 (B3LYP-D3) and 0.47 kcal/mol (M06-2X) (with explicit counterpoise corrections). These results validate both B3LYP-D3 and M06-2X for interactions of this type using a much larger data set than was presented in prior work. However, our new dispersion correction scheme shows some clear advantages for dispersion and dipole-dipole dominated complexes with the small LACVP* basis set, which is very popular in use due to its low associated computational cost: The MUE for B3LYP-MM with the LACVP* basis set for this subset of complexes (without explicit counterpoise corrections) is only 0.28 kcal/mol, compared to 0.65 kcal/mol for M06-2X or 1.16 kcal/mol for B3LYP-D3. Additionally, our new correction scheme also shows major improvements in accuracy for hydrogen-bonded systems and for systems involving ionic interactions, for example cation-π interactions. Compared to B3LYP-D3 and M06-2X, we also find that our new B3LYP-MM correction scheme gives results of higher or equal accuracy for a large dataset of conformer energies of di- and tripeptides, sugars, and cysteine.

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QTAIM analysis dataset for non-covalent interactions in furan clusters.

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