Performance of revised STO(1M)‐3G basis set for prediction of 5‐fluorocytosine chemical shifts

Kupka, Teobald; Mnich, Adrianna; Broda, Małgorzata A.

doi:10.1002/mrc.4879

Cited by 7 publications

(4 citation statements)

References 54 publications

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“…However, the accuracy decreased significantly when the theory level was lowered, with values of 3.71 ppm/0.24 ppm (level B), 3.81 ppm/0.24 ppm (level C), and 6.00 ppm/0.42 ppm (level D). These results are consistent with previous findings and demonstrate that low quality basis sets (mainly the STO-3G) are unsuitable for accurate NMR calculations …”

supporting

confidence: 93%

“…These results are consistent with previous findings and demonstrate that low quality basis sets (mainly the STO-3G) are unsuitable for accurate NMR calculations. 14 The results obtained with iJ/dJ-DP4 (Figure 2b) were slightly better than the corresponding dJ-DP4 values (Figure 2a), but with a remarkable reduction in the computational cost. Using only a few 3 J HH couplings to constrain the conformational search (typically between 1 and 3), the total number of conformations was reduced by 60% on average (from 13% to 91%).…”

mentioning

confidence: 75%

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ML-J-DP4: An Integrated Quantum Mechanics-Machine Learning Approach for Ultrafast NMR Structural Elucidation

et al. 2022

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A new tool, ML-J-DP4, provides an efficient and accurate method for determining the most likely structure of complex molecules within minutes using standard computational resources. The workflow involves combining fast Karplus-type J calculations with NMR chemical shifts predictions at the cheapest HF/STO-3G level enhanced using machine learning (ML), all embedded in the J-DP4 formalism. Our ML provides accurate predictions, which compare favorably alongside with other ML methods.

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supporting

confidence: 93%

mentioning

confidence: 75%

ML-J-DP4: An Integrated Quantum Mechanics-Machine Learning Approach for Ultrafast NMR Structural Elucidation

et al. 2022

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“…However, the number of computational cycles needed to converge to optimized molecular geometry is reduced while compromising with total computational time when there is used the former method [129]. The small STO-3G basis set and sit improved modifications are used to compute high molecular weight analytes [130][131][132][133][134].…”

Section: Methodsmentioning

confidence: 99%

Stochastic dynamics mass spectrometric determination of ferrocenes

Ivanova

2024

Preprint

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The paper treats stochastic dynamics mass spectrometric formulas of exact data-processing of measurands; thus, answering a question: How can be inferred reliably analyte identification and annotation from mass spectrometric measurands when omics-methods produce comparable performances among structurally similar analytes? Omics-methods are treated in context of instrumental measurements and data-processing. Exact quantitative and multi-dimensional structural mass spectrometric-based methods for metabolomics contributes crucially to understand biochemical mechanisms, because of metabolites are downstream biochemical products in living systems. Reliable metabolomics provides in-depth knowledge of response within biological fluids and tissues depending on internal and external agents, which is crucial for real time monitoring of human diseases. The study deals with structural analysis of ferroquine and its metabolites in human hepatic models utilizing ultra-high accuracy mass spectrometry, static and molecular dynamics quantum chemical approaches, and chemometrics. It provides excellent-to-exact performances in examining standard organometallics ferrocene and [FeII(L)(CO)2(CH3CN)] (L = 2-(5-oxo-4,6-bis-trimethylsilanyl-3,5-dihydro-1H-cyclopenta[c]pyrrol-2-yl)-ethanesulfonic acid) (|r|=0.99992.) The analysis of ferroquine and its metabolites show |r|=0.99815–0.90814.

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“…This problem is important for many drugs containing heterocyclic fragments in their structures or F, Cl, Br or I atoms. For such molecules, a worse agreement between experimental and theoretically predicted chemical shifts and the indirect spin–spin coupling constant is usually observed [ 55 , 56 ].…”

Section: Introductionmentioning

confidence: 99%

Factors Governing the Chemical Stability and NMR Parameters of Uracil Tautomers and Its 5-Halogen Derivatives

et al. 2020

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We report on the density functional theory (DFT) modelling of structural, energetic and NMR parameters of uracil and its derivatives (5-halogenouracil (5XU), X = F, Cl, Br and I) in vacuum and in water using the polarizable continuum model (PCM) and the solvent model density (SMD) approach. On the basis of the obtained results, we conclude that the intramolecular electrostatic interactions are the main factors governing the stability of the six tautomeric forms of uracil and 5XU. Two indices of aromaticity, the harmonic oscillator model of aromaticity (HOMA), satisfying the geometric criterion, and the nuclear independent chemical shift (NICS), were applied to evaluate the aromaticity of uracil and its derivatives in the gas phase and water. The values of these parameters showed that the most stable tautomer is the least aromatic. A good performance of newly designed xOPBE density functional in combination with both large aug-cc-pVQZ and small STO(1M)−3G basis sets for predicting chemical shifts of uracil and 5-fluorouracil in vacuum and water was observed. As a practical alternative for calculating the chemical shifts of challenging heterocyclic compounds, we also propose B3LYP calculations with small STO(1M)−3G basis set. The indirect spin–spin coupling constants predicted by B3LYP/aug-cc-pVQZ(mixed) method reproduce the experimental data for uracil and 5-fluorouracil well.

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Performance of revised STO(1M)‐3G basis set for prediction of 5‐fluorocytosine chemical shifts

Cited by 7 publications

References 54 publications

ML-J-DP4: An Integrated Quantum Mechanics-Machine Learning Approach for Ultrafast NMR Structural Elucidation

ML-J-DP4: An Integrated Quantum Mechanics-Machine Learning Approach for Ultrafast NMR Structural Elucidation

Stochastic dynamics mass spectrometric determination of ferrocenes

Factors Governing the Chemical Stability and NMR Parameters of Uracil Tautomers and Its 5-Halogen Derivatives

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