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Computational Chemistry Insights into Molecular Interactions
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Computational Chemistry Insights into Molecular Interactions

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Computational and Theoretical Chemistry".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 6557

Special Issue Editor

Prof. Dr. Wim Buijs

E-Mail Website
Guest Editor
Process and Energy Department, Delft University of Technology (Retired), Delft, The Netherlands
Interests: molecular modeling; CO2 capture; cannabinoids; catalysis; oxidation; industrial chemistry; renewables; teaching

Special Issue Information

Dear Colleagues,

Thanks to the rise of computational power and decreasing cost of computers, computational chemistry has evolved to a tool that changes the way chemical research and teaching is carried out. A wide variety of methods and tools have become available which not only can improve our understanding of basic chemical concepts but also is applicable to real experimental problems in academic and industrial research. Nowadays properties of molecules and molecular ensembles can be determined with sufficient accuracy to be useful in limiting the amount of experimental work in catalysis, drug discovery, and the development of new materials. Among them are thermodynamic properties, spectroscopical properties, and reaction kinetics to mention just a few. Visualization plays an important role in many aspects and particularly in teaching. Computational chemistry has the potential to become the universal (visual) language, uniting the different descriptions of similar chemical phenomena in disciplines like physical chemistry, organic chemistry, inorganic chemistry and biochemistry, catalysis and biocatalysis, pharmacokinetics.

We welcome original articles and short communications, as well as a limited number of review articles, on new approaches and methods of computational chemistry for research and teaching. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on the website.

Prof. Dr. Wim Buijs
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • visualization
  • molecular mechanics
  • quantum mechanics
  • molecular dynamics
  • biomolecular modeling
  • drug development
  • catalysis
  • materials modeling
  • thermodynamics
  • method development
  • teaching

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (5 papers)

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Research

18 pages, 10465 KiB  
Article
Quantum Chemical Investigation into the Structural Analysis and Calculated Raman Spectra of Amylose Modeled with Linked Glucose Molecules
by Dapeng Zhang and Naoki Kishimoto
Molecules 2024, 29(12), 2842; https://doi.org/10.3390/molecules29122842 - 14 Jun 2024
Viewed by 1123
Abstract
This study presents a quantum chemical investigation into the structural analysis and calculated Raman spectra of modeled amylose with varying units of linked glucose molecules. We systematically examined the rotation of hydroxymethyl groups and intramolecular hydrogen bonds within these amylose models. Our study [...] Read more.
This study presents a quantum chemical investigation into the structural analysis and calculated Raman spectra of modeled amylose with varying units of linked glucose molecules. We systematically examined the rotation of hydroxymethyl groups and intramolecular hydrogen bonds within these amylose models. Our study found that as the number of linked glucose units increases, the linear structure becomes more complex, resulting in curled, cyclic, or helical structures facilitated by establishing various intramolecular interactions. The hydroxymethyl groups were confirmed to form interactions with oxygen atoms and with hydroxymethyl and hydroxyl groups from adjacent rings in the molecular structures. We identified distinct peaks and selected specific bands applicable in various analytical contexts by comparing their calculated Raman spectra. Representative vibrational modes within selected regions were identified across the different lengths of amylose models, serving as characteristic signatures for linear and more coiled structural conformations. Our findings contribute to a deeper understanding of amylose structures and spectroscopic signatures, with implications for theoretical studies and potential applications. This work provides valuable reference points for the detailed assignment of Raman peaks of amylose structure, facilitating their application in broader research on carbohydrate structures and their associated spectroscopic properties. Full article
(This article belongs to the Special Issue Computational Chemistry Insights into Molecular Interactions)
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18 pages, 1983 KiB  
Article
Core-Hole Excitation Spectra of the Oxides and Hydrates of Fullerene C60 and Azafullerene C59N
by Xiong Li, Shuyi Wang, Jingdong Guo, Ziye Wu, Changrui Guo, Shaohong Cai and Mingsen Deng
Molecules 2024, 29(3), 609; https://doi.org/10.3390/molecules29030609 - 26 Jan 2024
Cited by 1 | Viewed by 1127
Abstract
The interaction of fullerenes and their derivatives with environmental molecules such as oxygen or water was crucial for the rational design of low-dimensional materials and devices. In this paper, the near-edge X-ray absorption fine structure (NEXAFS), X-ray emission spectroscopy (XES) and X-ray photoelectron [...] Read more.
The interaction of fullerenes and their derivatives with environmental molecules such as oxygen or water was crucial for the rational design of low-dimensional materials and devices. In this paper, the near-edge X-ray absorption fine structure (NEXAFS), X-ray emission spectroscopy (XES) and X-ray photoelectron spectroscopy (XPS) shake-up satellites were employed to distinguish the oxides and hydrates of the fullerene C60 and azafullerene C59N families. The study includes various isomers, such as the open [5,6] and closed [6,6] isomers of C60O, C60H(OH), C60-O-C60, C60H-O-C60H, C59N(OH) and C59N-O-C59N, based on density functional theory. These soft X-ray spectra offered comprehensive insights into the molecular orbitals of these azafullerene molecular groups. The oxygen K-edge NEXAFS, carbon and oxygen K-edge XPS shake-up satellite spectra provided valuable tools for distinguishing oxides or hydrates of fullerene C60 and azafullerene C59N. Our findings could significantly benefit the development of fullerene functional molecular materials and expand the application scope of soft X-ray spectroscopy as a molecular fingerprinting tool for the fullerene family. Full article
(This article belongs to the Special Issue Computational Chemistry Insights into Molecular Interactions)
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15 pages, 3236 KiB  
Article
Fusing Sequence and Structural Knowledge by Heterogeneous Models to Accurately and Interpretively Predict Drug–Target Affinity
by Xin Zeng, Kai-Yang Zhong, Bei Jiang and Yi Li
Molecules 2023, 28(24), 8005; https://doi.org/10.3390/molecules28248005 - 8 Dec 2023
Cited by 6 | Viewed by 1551
Abstract
Drug–target affinity (DTA) prediction is crucial for understanding molecular interactions and aiding drug discovery and development. While various computational methods have been proposed for DTA prediction, their predictive accuracy remains limited, failing to delve into the structural nuances of interactions. With increasingly accurate [...] Read more.
Drug–target affinity (DTA) prediction is crucial for understanding molecular interactions and aiding drug discovery and development. While various computational methods have been proposed for DTA prediction, their predictive accuracy remains limited, failing to delve into the structural nuances of interactions. With increasingly accurate and accessible structure prediction of targets, we developed a novel deep learning model, named S2DTA, to accurately predict DTA by fusing sequence features of drug SMILES, targets, and pockets and their corresponding graph structural features using heterogeneous models based on graph and semantic networks. Experimental findings underscored that complex feature representations imparted negligible enhancements to the model’s performance. However, the integration of heterogeneous models demonstrably bolstered predictive accuracy. In comparison to three state-of-the-art methodologies, such as DeepDTA, GraphDTA, and DeepDTAF, S2DTA’s performance became more evident. It exhibited a 25.2% reduction in mean absolute error (MAE) and a 20.1% decrease in root mean square error (RMSE). Additionally, S2DTA showed some improvements in other crucial metrics, including Pearson Correlation Coefficient (PCC), Spearman, Concordance Index (CI), and R2, with these metrics experiencing increases of 19.6%, 17.5%, 8.1%, and 49.4%, respectively. Finally, we conducted an interpretability analysis on the effectiveness of S2DTA by bidirectional self-attention mechanism. The analysis results supported that S2DTA was an effective and accurate tool for predicting DTA. Full article
(This article belongs to the Special Issue Computational Chemistry Insights into Molecular Interactions)
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14 pages, 8624 KiB  
Article
Computational Modeling Study of the Binding of Aging and Non-Aging Inhibitors with Neuropathy Target Esterase
by Wenxiong Wu and Pan Wang
Molecules 2023, 28(23), 7747; https://doi.org/10.3390/molecules28237747 - 24 Nov 2023
Viewed by 892
Abstract
Neuropathy target esterase (NTE) is a serine hydrolase with phospholipase B activity, which is involved in maintaining the homeostasis of phospholipids. It can be inhibited by aging inhibitors such as some organophosphorus (OP) compounds, which leads to delayed neurotoxicity with distal degeneration of [...] Read more.
Neuropathy target esterase (NTE) is a serine hydrolase with phospholipase B activity, which is involved in maintaining the homeostasis of phospholipids. It can be inhibited by aging inhibitors such as some organophosphorus (OP) compounds, which leads to delayed neurotoxicity with distal degeneration of axons. However, the detailed binding conformation of aging and non-aging inhibitors with NTE is not known. In this study, new computational models were constructed by using MODELLER 10.3 and AlphaFold2 to further investigate the inhibition mechanism of aging and non-aging compounds using molecular docking. The results show that the non-aging compounds bind the hydrophobic pocket much deeper than aging compounds and form the hydrophobic interaction with Phe1066. Therefore, the unique binding conformation of non-aging compounds may prevent the aging reaction. These important differences of the binding conformations of aging and non-aging inhibitors with NTE may help explain their different inhibition mechanism and the protection of non-aging NTE inhibitors against delayed neuropathy. Full article
(This article belongs to the Special Issue Computational Chemistry Insights into Molecular Interactions)
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18 pages, 9037 KiB  
Article
A Holistic View of the Interactions between Electron-Deficient Systems: Clustering of Beryllium and Magnesium Hydrides and Halides
by Otilia Mó, M. Merced Montero-Campillo, Manuel Yáñez, Ibon Alkorta and José Elguero
Molecules 2023, 28(22), 7507; https://doi.org/10.3390/molecules28227507 - 9 Nov 2023
Cited by 2 | Viewed by 1121
Abstract
In the search for common bonding patterns in pure and mixed clusters of beryllium and magnesium derivatives, the most stable dimers and trimers involving BeX2 and MgX2 (X = H, F, Cl) have been studied in the gas phase using B3LYP [...] Read more.
In the search for common bonding patterns in pure and mixed clusters of beryllium and magnesium derivatives, the most stable dimers and trimers involving BeX2 and MgX2 (X = H, F, Cl) have been studied in the gas phase using B3LYP and M06-2X DFT methods and the G4 ab initio composite procedure. To obtain some insight into their structure, stability, and bonding characteristics, we have used two different energy decomposition formalisms, namely MBIE and LMO-EDA, in parallel with the analysis of the electron density with the help of QTAIM, ELF, NCIPLOT, and AdNDP approaches. Some interesting differences are already observed in the dimers, where the stability sequence observed for the hydrides differs entirely from that of the fluorides and chlorides. Trimers also show some peculiarities associated with the presence of compact trigonal cyclic structures that compete in stability with the more conventional hexagonal and linear forms. As observed for dimers, the stability of the trimers changes significantly from hydrides to fluorides or chlorides. Although some of these clusters were previously explored in the literature, the novelty of this work is to provide a holistic approach to the entire series of compounds by using chemical bonding tools, allowing us to understand the stability trends in detail and providing insights for a significant number of new, unexplored structures. Full article
(This article belongs to the Special Issue Computational Chemistry Insights into Molecular Interactions)
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