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Computation
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10th Anniversary of Computation—Computational Chemistry
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10th Anniversary of Computation—Computational Chemistry

A special issue of Computation (ISSN 2079-3197).

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 10065

Special Issue Editors

Prof. Dr. Karlheinz Schwarz

E-Mail Website
Guest Editor
Theoretical Chemistry Group, Materials Chemistry, TU Wien, A-1060 Vienna, Austria
Interests: density functional theory (DFT); electronic structure of solids and surfaces; chemical bonding; spectra; high-performance computing; Wien2k code
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Henry Chermette

E-Mail Website
Guest Editor
Institut des Sciences Analytiques, Université de Lyon, UMR 5280, CNRS, Université Lyon 1 - 5, rue de la Doua, F-69100 Villeurbanne, France
Interests: development and application of density functional theory; chemical reactivity and catalytic systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Computational chemistry is becoming increasingly important in the context of developing a basic understanding of the relation between the atomic structure and properties of a material. Many papers have already been published in this field, including in this journal. In these simulations, simplifications or idealizations are often used to make computations feasible. A critical analysis of the methodology is thus needed to improve the quality of such computations. For example, for the electronic structure, a quantum mechanical treatment is needed, often conducted by means of density functional theory (DFT) based on functionals. One crucial aspect that needs to be determined is which of them leads to agreement with experimental data. In this context, other topics can become important, such as temperature, pressure, magnetism, substitutions, or relativistic effects (for heavy elements). High accuracy is needed to evaluate rather similar cases (e.g., magnetic anisotropy). By improving efficiency, one can investigate more complex structures (which better represent a real system). With systematic studies, one can find trends, which allow for improving structure property relations based on new insights. For these reasons, we intend to publish a Special Issue focusing on current challenges and presenting future innovations.    

In addition to solid-state research, numerical analysis, machine learnings, artificial intelligence, computational biology, and bioinformatics are further topics of interest in the important developments in computational chemistry.

Prof. Dr. Karlheinz Schwarz
Prof. Dr. Henry Chermette
Guest Editors

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. Computation is an international peer-reviewed open access monthly 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 1800 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.

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Published Papers (6 papers)

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Research

25 pages, 6597 KiB  
Article
To Bind or Not to Bind? A Comprehensive Characterization of TIR1 and Auxins Using Consensus In Silico Approaches
by Fernando D. Prieto-Martínez, Jennifer Mendoza-Cañas and Karina Martínez-Mayorga
Computation 2024, 12(5), 94; https://doi.org/10.3390/computation12050094 - 9 May 2024
Viewed by 1050
Abstract
Auxins are chemical compounds of wide interest, mostly due to their role in plant metabolism and development. Synthetic auxins have been used as herbicides for more than 75 years and low toxicity in humans is one of their most advantageous features. Extensive studies [...] Read more.
Auxins are chemical compounds of wide interest, mostly due to their role in plant metabolism and development. Synthetic auxins have been used as herbicides for more than 75 years and low toxicity in humans is one of their most advantageous features. Extensive studies of natural and synthetic auxins have been made in an effort to understand their role in plant growth. However, molecular details of the binding and recognition process are still an open question. Herein, we present a comprehensive in silico pipeline for the assessment of TIR1 ligands using several structure-based methods. Our results suggest that subtle dynamics within the binding pocket arise from water–ligand interactions. We also show that this trait distinguishes effective binders. Finally, we construct a database of putative ligands and decoy compounds, which can aid further studies focusing on synthetic auxin design. To the best of our knowledge, this study is the first of its kind focusing on TIR1. Full article
(This article belongs to the Special Issue 10th Anniversary of Computation—Computational Chemistry)
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16 pages, 2428 KiB  
Article
Unraveling the Dual Inhibitory Mechanism of Compound 22ac: A Molecular Dynamics Investigation into ERK1 and ERK5 Inhibition in Cancer
by Elliasu Y. Salifu, Mbuso A. Faya, James Abugri and Pritika Ramharack
Computation 2024, 12(3), 45; https://doi.org/10.3390/computation12030045 - 1 Mar 2024
Cited by 1 | Viewed by 1943
Abstract
Cancer remains a major challenge in the field of medicine, necessitating innovative therapeutic strategies. Mitogen-activated protein kinase (MAPK) signaling pathways, particularly Extracellular Signal-Regulated Kinase 1 and 2 (ERK1/2), play pivotal roles in cancer pathogenesis. Recently, ERK5 (also known as MAPK7) has emerged as [...] Read more.
Cancer remains a major challenge in the field of medicine, necessitating innovative therapeutic strategies. Mitogen-activated protein kinase (MAPK) signaling pathways, particularly Extracellular Signal-Regulated Kinase 1 and 2 (ERK1/2), play pivotal roles in cancer pathogenesis. Recently, ERK5 (also known as MAPK7) has emerged as an attractive target due to its compensatory role in cancer progression upon termination of ERK1 signaling. This study explores the potential of Compound 22ac, a novel small molecule inhibitor, to simultaneously target both ERK1 and ERK5 in cancer cells. Using molecular dynamics simulations, we investigate the binding affinity, conformational dynamics, and stability of Compound 22ac when interacting with ERK1 and ERK5. Our results indicate that Compound 22ac forms strong interactions with key residues in the ATP-binding pocket of both ERK1 and ERK5, effectively inhibiting their catalytic activity. Furthermore, the simulations reveal subtle differences in the binding modes of Compound 22ac within the two kinases, shedding light on the dual inhibitory mechanism. This research not only elucidates a structural mechanism of action of Compound 22ac, but also highlights its potential as a promising therapeutic agent for cancer treatment. The dual inhibition of ERK1 and ERK5 by Compound 22ac offers a novel approach to disrupting the MAPK signaling cascade, thereby hindering cancer progression. These findings may contribute to the development of targeted therapies that could improve the prognosis for cancer patients. Full article
(This article belongs to the Special Issue 10th Anniversary of Computation—Computational Chemistry)
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11 pages, 3057 KiB  
Article
Adsorption of SO2 Molecule on Pristine, N, Ga-Doped and -Ga-N- co-Doped Graphene: A DFT Study
by Dinara Akhmetsadyk, Arkady Ilyin, Nazim Guseinov and Gary Beall
Computation 2023, 11(12), 235; https://doi.org/10.3390/computation11120235 - 22 Nov 2023
Cited by 1 | Viewed by 1895
Abstract
SO2 (sulfur dioxide) is a toxic substance emitted into the environment due to burning sulfur-containing fossil fuels in cars, factories, power plants, and homes. This issue is of grave concern because of its negative effects on the environment and human health. Therefore, [...] Read more.
SO2 (sulfur dioxide) is a toxic substance emitted into the environment due to burning sulfur-containing fossil fuels in cars, factories, power plants, and homes. This issue is of grave concern because of its negative effects on the environment and human health. Therefore, the search for a material capable of interacting to detect SO2 and the research on developing effective materials for gas detection holds significant importance in the realm of environmental and health applications. It is well known that one of the effective methods for predicting the structure and electronic properties of systems capable of interacting with a molecule is a method based on quantum mechanical approaches. In this work, the DFT (Density Functional Theory) program DMol3 in Materials Studio was used to study the interactions between the SO2 molecule and four systems. The adsorption energy, bond lengths, bond angle, charge transfer, and density of states of SO2 molecule on pristine graphene, N-doped graphene, Ga-doped graphene, and -Ga-N- co-doped graphene were investigated using DFT calculations. The obtained data indicate that the bonding between the SO2 molecule and pristine graphene is relatively weak, with a binding energy of −0.32 eV and a bond length of 3.06 Å, indicating physical adsorption. Next, the adsorption of the molecule on an N-doped graphene system was considered. The adsorption of SO2 molecules on N-doped graphene is negligible; generally, the interaction of SO2 molecules with this system does not significantly change the electronic properties. However, the adsorption energy of the gas molecule on Ga-doped graphene relative to pristine graphene increased significantly. The evidence of chemisorption is increased adsorption energy and decreased adsorption distance between SO2 and Ga-doped graphene. In addition, our results show that introducing -Ga-N- co-dopants of an “ortho” configuration into pristine graphene significantly affects the adsorption between the gas molecule and graphene. Thus, this approach is significantly practical in the adsorption of SO2 molecules. Full article
(This article belongs to the Special Issue 10th Anniversary of Computation—Computational Chemistry)
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17 pages, 2842 KiB  
Article
A Versatile Unitary Transformation Framework for an Optimal Bath Construction in Density-Matrix Based Quantum Embedding Approaches
by Quentin Marécat and Matthieu Saubanère
Computation 2023, 11(10), 203; https://doi.org/10.3390/computation11100203 - 11 Oct 2023
Cited by 1 | Viewed by 1675
Abstract
The performance of embedding methods is directly tied to the quality of the bath orbital construction. In this paper, we develop a versatile framework, enabling the investigation of the optimal construction of the orbitals of the bath. As of today, in state-of-the-art embedding [...] Read more.
The performance of embedding methods is directly tied to the quality of the bath orbital construction. In this paper, we develop a versatile framework, enabling the investigation of the optimal construction of the orbitals of the bath. As of today, in state-of-the-art embedding methods, the orbitals of the bath are constructed by performing a Singular Value Decomposition (SVD) on the impurity-environment part of the one-body reduced density matrix, as originally presented in Density Matrix Embedding Theory. Recently, the equivalence between the SVD protocol and the use of unitary transformation, the so-called Block-Householder transformation, has been established. We present a generalization of the Block-Householder transformation by introducing additional flexible parameters. The additional parameters are optimized such that the bath-orbitals fulfill physically motivated constraints. The efficiency of the approach is discussed and exemplified in the context of the half-filled Hubbard model in one-dimension. Full article
(This article belongs to the Special Issue 10th Anniversary of Computation—Computational Chemistry)
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Graphical abstract

15 pages, 321 KiB  
Article
Spherical Subspace Potential Functional Theory
by Ágnes Nagy
Computation 2023, 11(6), 119; https://doi.org/10.3390/computation11060119 - 15 Jun 2023
Cited by 1 | Viewed by 1173
Abstract
The recently introduced version of the density functional theory that employs a set of spherically symmetric densities instead of the density has a ‘set-representability problem’. It is not known if a density exists for a given set of the spherically symmetric densities. This [...] Read more.
The recently introduced version of the density functional theory that employs a set of spherically symmetric densities instead of the density has a ‘set-representability problem’. It is not known if a density exists for a given set of the spherically symmetric densities. This problem can be eliminated if potentials are applied instead of densities as basic variables. Now, the spherical subspace potential functional theory is established. Full article
(This article belongs to the Special Issue 10th Anniversary of Computation—Computational Chemistry)
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12 pages, 3338 KiB  
Article
Addressing the Folding of Intermolecular Springs in Particle Simulations: Fixed Image Convention
by Aristotelis P. Sgouros and Doros N. Theodorou
Computation 2023, 11(6), 106; https://doi.org/10.3390/computation11060106 - 26 May 2023
Cited by 1 | Viewed by 1144
Abstract
Mesoscopic simulations of long polymer chains and soft matter systems are conducted routinely in the literature in order to assess the long-lived relaxation processes manifested in these systems. Coarse-grained chains are, however, prone to unphysical intercrossing due to their inherent softness. This issue [...] Read more.
Mesoscopic simulations of long polymer chains and soft matter systems are conducted routinely in the literature in order to assess the long-lived relaxation processes manifested in these systems. Coarse-grained chains are, however, prone to unphysical intercrossing due to their inherent softness. This issue can be resolved by introducing long intermolecular bonds (the so-called slip-springs) which restore these topological constraints. The separation vector of intermolecular bonds can be determined by enforcing the commonly adopted minimum image convention (MIC). Because these bonds are soft and long (ca 3–20 nm), subjecting the samples to extreme deformations can lead to topology violations when enforcing the MIC. We propose the fixed image convention (FIC) for determining the separation vectors of overextended bonds, which is more stable than the MIC and applicable to extreme deformations. The FIC is simple to implement and, in general, more efficient than the MIC. Side-by-side comparisons between the MIC and FIC demonstrate that, when using the FIC, the topology remains intact even in situations with extreme particle displacement and nonaffine deformation. The accuracy of these conventions is the same when applying affine deformation. The article is accompanied by the corresponding code for implementing the FIC. Full article
(This article belongs to the Special Issue 10th Anniversary of Computation—Computational Chemistry)
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