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分子内氢键离子红外多光子离解振动光谱预测常用理论方法的评估

Evaluation of Common Theoretical Methods for Predicting Infrared Multiphotonic Dissociation Vibrational Spectra of Intramolecular Hydrogen-Bonded Ions.

作者信息

Rodrigues-Oliveira André F, M Ribeiro Francisco W, Cervi Gustavo, C Correra Thiago

机构信息

Department of Fundamental Chemistry, Institute of Chemistry, University of São Paulo, Avenue Prof. Lineu Prestes, 748, 05508-000 São Paulo, Brazil.

出版信息

ACS Omega. 2018 Aug 14;3(8):9075-9085. doi: 10.1021/acsomega.8b00815. eCollection 2018 Aug 31.

DOI:10.1021/acsomega.8b00815
PMID:31459042
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6644661/
Abstract

Infrared photodissociation analyses are supported by theoretical calculations that allow a trustworthy interpretation of experimental spectra of gaseous ions. B3LYP calculations are the most prominent method used to model IR spectra, as detailed in our bibliographic survey. However, this and other commonly used methods are known to provide inaccurate energy values and geometries, especially when it comes to long-range interactions, such as intramolecular H-bonds, which show increased anharmonicity. Therefore, we evaluated some of the most commonly used density functional theory methods (B3LYP, CAM-B3LYP, and M06-2X) and basis sets (6-31+G(d,p), 6-311++G(d,p), 6-311++G(3df,2pd), aug-cc-pVDZ, and aug-cc-pVTZ), including anharmonicity and dispersion corrections. The results were compared to MP2 calculations and to experimental high-frequency (2000-4000 cm) IR multiphotonic dissociation (IRMPD) spectra of two protonated model molecules containing intramolecular hydrogen bonds: biotin and tryptophan. M06-2X/6-31+G(d,p) was shown to be the most cost-effective level of theory, whereas CAM-B3LYP was the most efficient method to describe the van der Waals interactions. The use of the dispersion correction D3, proposed by Grimme, improved the description of O-H vibrations involved in H-bonding but worsened the description of N-H stretches. Anharmonic calculations were shown to be extremely expensive when compared to other approaches. The efficiencies of well-established scaling factors (SFs) in opposition to sample-dependent SFs were also discussed and the use of fitted SFs were shown to be the most cost-effective approach to predict IRMPD spectra. M06-2X/6-31+G(d,p) and CAM-B3LYP/aug-cc-pVDZ were also tested against the fingerprint region. Our results suggest that these methods can also be used for analysis in this lower frequency range and should be regarded as the methods of choice for cost-effective IRMPD simulations rather than the ubiquitous B3LYP method, especially when further molecular properties are needed.

摘要

红外光解离分析得到了理论计算的支持,这些计算使得对气态离子实验光谱的可靠解释成为可能。正如我们在文献综述中所详述的,B3LYP计算是用于模拟红外光谱的最突出方法。然而,众所周知,这种方法以及其他常用方法会提供不准确的能量值和几何结构,特别是在涉及长程相互作用时,例如分子内氢键,其表现出增加的非谐性。因此,我们评估了一些最常用的密度泛函理论方法(B3LYP、CAM - B3LYP和M06 - 2X)和基组(6 - 31 + G(d,p)、6 - 311++G(d,p)、6 - 311++G(3df,2pd)、aug - cc - pVDZ和aug - cc - pVTZ),包括非谐性和色散校正。将结果与MP2计算以及含有分子内氢键的两种质子化模型分子(生物素和色氨酸)的实验高频(2000 - 4000 cm)红外多光子解离(IRMPD)光谱进行了比较。结果表明,M06 - 2X/6 - 31 + G(d,p)是最具成本效益的理论水平,而CAM - B3LYP是描述范德华相互作用的最有效方法。Grimme提出的色散校正D3的使用改善了对氢键中O - H振动的描述,但恶化了对N - H伸缩振动的描述。与其他方法相比,非谐计算被证明极其昂贵。还讨论了既定标度因子(SFs)与依赖于样品的SFs的效率,并且表明使用拟合的SFs是预测IRMPD光谱最具成本效益的方法。M06 - 2X/6 - 31 + G(d,p)和CAM - B3LYP/aug - cc - pVDZ也针对指纹区域进行了测试。我们的结果表明,这些方法也可用于该较低频率范围的分析,并且应被视为进行具有成本效益IRMPD模拟的首选方法,而不是普遍使用的B3LYP方法,特别是在需要进一步分子性质时。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba9f/6644661/cfb847e8a962/ao-2018-008158_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba9f/6644661/e93dbb909772/ao-2018-008158_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba9f/6644661/b9976a8cdcb3/ao-2018-008158_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba9f/6644661/6e95366067eb/ao-2018-008158_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba9f/6644661/b743424392b7/ao-2018-008158_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba9f/6644661/cad64120e53b/ao-2018-008158_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba9f/6644661/cfb847e8a962/ao-2018-008158_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba9f/6644661/e93dbb909772/ao-2018-008158_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba9f/6644661/b9976a8cdcb3/ao-2018-008158_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba9f/6644661/6e95366067eb/ao-2018-008158_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba9f/6644661/b743424392b7/ao-2018-008158_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba9f/6644661/cad64120e53b/ao-2018-008158_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba9f/6644661/cfb847e8a962/ao-2018-008158_0006.jpg

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