Semi-empirical and linear-scaling DFT methods to characterize duplex DNA and G-quadruplexes in the presence of interacting small molecules

文献信息

发布日期 2022-03-25
DOI 10.1039/D2CP00214K
影响因子 3.676
作者

Sawssen Elleuchi, Khaled Jarraya


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摘要

The computational study of DNA and its interaction with ligands is a highly relevant area of research, with significant consequences for developing new therapeutic strategies. However, the computational description of such large and complex systems requires considering interactions of different types simultaneously in a balanced way, such as non-covalent weak interactions (namely hydrogen bonds and stacking), metal–ligand interactions, polarisation and charge transfer effects. All these considerations imply a real challenge for computational chemistry. The possibility of studying large biological systems using quantum methods for the entire system requires significant computational resources, with improvements in parallelisation and optimisation of theoretical strategies. Computational methods, such as Linear-Scaling Density Functional Theory (LS-DFT) and DLPNO-CCSD(T), may allow performing ab initio quantum mechanics calculations, including the electronic structure for large biological systems, in a reasonable computing time. In this work, we study the interaction of small molecules and cations with DNA (both duplex DNA and G-quadruplexes), comparing different computational methods: a LS-DFT method at the LMKLL/DZDP level of theory, semi-empirical methods (PM6-DH2 and PM7), mixed QM/MM, and DLPNO-CCSD(T). Our goal is to demonstrate the adequacy of LS-DFT to treat the different types of interactions present in DNA-dependent systems. We show that LMKLL/DZDP using SIESTA can yield very accurate geometries and energetics in all the different systems considered in this work: duplex DNA (dDNA), phenanthroline intercalating dDNA, G-quadruplexes, and metal-G-tetrads considering alkaline metals of different sizes. As far as we know, this is the first time that full G-quadruplex geometry optimisations have been carried out using a DFT method thanks to its linear-scaling capabilities. Moreover, we show that LS-DFT provides high-quality structures, and some semi-empirical Hamiltonians can also yield suitable geometries. However, DLPNO-CCSD(T) and LS-DFT are the only methods that accurately describe interaction energies for all the systems considered in our study.

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Physical Chemistry Chemical Physics

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.

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