Symmetry-adapted perturbation theory potential for the adenine dimer

文献信息

发布日期 2018-09-27

DOI 10.1039/C8CP03798A

影响因子 3.676

作者

Armağan Karatosun, Mehmet Çankaya, Adem Tekin

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摘要

A new intermolecular interaction potential for the adenine dimer has been developed with the help of a combination of symmetry-adapted perturbation theory and density functional theory (DFT-SAPT). Supermolecular intermolecular interaction energy computations on hydrogen-bonded and stacked adenine dimers at B3LYP-D, MP2, SCS-MP2, SCS-MI-MP2 and CCSD(T) levels showed that DFT-SAPT is in a very good agreement with CCSD(T). The developed ab initio intermolecular potential has been used to predict the cluster structure of adenine dimers, trimers and tetramers. These global cluster optimizations reproduced adenine dimers reported in the literature and moreover new low-energy structures were also located. For trimers and tetramers, new hydrogen-bonded and stacked low-energy structures have also been found. The current findings suggest that the new ab initio potential can further be exploited to reveal the structure and energy of much larger supramolecular adenine clusters.

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来源期刊

Physical Chemistry Chemical Physics

CiteScore: 5.5

自引率: 10.3%

年发文量: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.