Pub Date : 2025-02-17DOI: 10.1007/s00894-025-06300-3
R. Shanmugam, P. Dineshkumar, T. Sangeetha, P. Mounica, K. Ramya, A. Elangovan, G. Arivazhagan
Context
The dimethyl sulfoxide (DMSO), an excellent solvent, has many applications in biochemical and pharmacological technology and has self-associates. In the S = O stretching region of its infrared (IR) spectrum, it has been reported that two S = O stretching bands, each one for monomer and dimer, and two methyl stretching bands appear. The density functional theory (DFT) calculations reveal that one of the two methyl stretching bands is the dimer S = O stretching band. The analysis of IR spectrum of DMSO-water solution for the S = O stretching bands along with the theoretical bands shows that in the solution with water mole fraction less than 0.3, unlike the literature report that there are no DMSO-water interactions, DMSO-water H-bond complexation takes place. The second-order perturbation energy analysis indicates that the DMSO sulfur can act as H-bond acceptor and DMSO oxygen has three lone pair electrons when complexed with water. The (text{O}-text{H}cdots text{S}) interaction, represented by green region in the isosurfaces, is classified as weak by the topological parameters such as electron density and Laplacian of electron density. The results assume significance in view of understanding its self-association and H-bond interaction with water, of course any solute.
Method
The deconvolution of experimental envelop has been carried out using OriginPro 9.0 software. The DFT calculations were done with B3LYP/6–311 + + G(3df,3pd) basis set using Gaussian09W. The isosurface and topological parameters have been obtained using Multiwfn 3.8 package. The results have been visualized using GaussView 5.0 and visual molecular dynamics (VMD) softwares.
{"title":"Monomer, cyclic dimer of dimethyl sulfoxide, and dimethyl sulfoxide-water hydrogen bonded complexes: FTIR studies and quantum chemical calculations","authors":"R. Shanmugam, P. Dineshkumar, T. Sangeetha, P. Mounica, K. Ramya, A. Elangovan, G. Arivazhagan","doi":"10.1007/s00894-025-06300-3","DOIUrl":"10.1007/s00894-025-06300-3","url":null,"abstract":"<div><h3>Context</h3><p>The dimethyl sulfoxide (DMSO), an excellent solvent, has many applications in biochemical and pharmacological technology and has self-associates. In the S = O stretching region of its infrared (IR) spectrum, it has been reported that two S = O stretching bands, each one for monomer and dimer, and two methyl stretching bands appear. The density functional theory (DFT) calculations reveal that one of the two methyl stretching bands is the dimer S = O stretching band. The analysis of IR spectrum of DMSO-water solution for the S = O stretching bands along with the theoretical bands shows that in the solution with water mole fraction less than 0.3, unlike the literature report that there are no DMSO-water interactions, DMSO-water H-bond complexation takes place. The second-order perturbation energy analysis indicates that the DMSO sulfur can act as H-bond acceptor and DMSO oxygen has three lone pair electrons when complexed with water. The <span>(text{O}-text{H}cdots text{S})</span> interaction, represented by green region in the isosurfaces, is classified as weak by the topological parameters such as electron density and Laplacian of electron density. The results assume significance in view of understanding its self-association and H-bond interaction with water, of course any solute.</p><h3>Method</h3><p>The deconvolution of experimental envelop has been carried out using OriginPro 9.0 software. The DFT calculations were done with B3LYP/6–311 + + G(3df,3pd) basis set using Gaussian09W. The isosurface and topological parameters have been obtained using Multiwfn 3.8 package. The results have been visualized using GaussView 5.0 and visual molecular dynamics (VMD) softwares.</p></div>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143423178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-17DOI: 10.1007/s00894-025-06302-1
Zengzhi He, Chongpeng Du, Jun Yu, Siyi Jing, Zonggang Du, Lichuan Gao, Chong Wang, Jiaxi Lei, Yonghong Zhu, Louwei Cui, Wei Han, Dong Li
Context
As a substitute for traditional petroleum derived jet fuels, water in coal-based hydrocarbon fuels may precipitate into ice at low temperatures, leading to fuel system failures and endangering flight safety. This study employed Karl Fischer titration in conjunction with an optimized combination of an oil moisture detector to jointly measure the water solubility of coal-based hydrocarbon fuels at room temperature. The coefficient correction was performed on the oil moisture detector, and the water solubility curves of coal-based hydrocarbon fuels 233 to 313 K were finally measured and compared with other literature results. Due to the extremely low water content in actual fuel and the uneven distribution of water in the fuel, this study mainly considers the water enrichment zone in the fuel.
Methods
Materials Studio 2019 software was utilized to simulate a representative molecular model of coal-based hydrocarbon fuel and a molecular model of water. The positions and charges of the atoms were set and tested, with the COMPASS force field selected to describe interatomic interactions. This force field is the first de novo computing field capable of accurately predicting interactions between various molecules and polymers. Geometry optimization was performed in the Forcite module, and the Construction tool in the Amorphous Cell Tools module was used to construct a coal-based hydrocarbon fuel system. The two models consisted of 3674 and 3671 atoms, respectively, with initial dimensions of 33.2 × 33.2 × 33.2 Å, the boundary conditions are periodic boundary conditions, the energy of the two models is minimized, the conjugate gradient method is used as the optimization method, and then the NPT annealing and kinetic pre-equilibrium operations are carried out, and the molecular dynamics simulation is carried out after the system relaxes to steady state. Through the MD method, the macroscopic phenomenon of temperature decrease in coal-based hydrocarbon fuel systems was analyzed from a microscopic perspective using mean square displacement, diffusion coefficient, and radial distribution function. It was predicted that the crystallization process of coal-based hydrocarbon fuel systems was mainly around 248 to 258 K.
{"title":"The low-temperature dissolution characteristics of water in coal-based hydrocarbon fuels and its molecular dynamics simulation","authors":"Zengzhi He, Chongpeng Du, Jun Yu, Siyi Jing, Zonggang Du, Lichuan Gao, Chong Wang, Jiaxi Lei, Yonghong Zhu, Louwei Cui, Wei Han, Dong Li","doi":"10.1007/s00894-025-06302-1","DOIUrl":"10.1007/s00894-025-06302-1","url":null,"abstract":"<div><h3>Context</h3><p>As a substitute for traditional petroleum derived jet fuels, water in coal-based hydrocarbon fuels may precipitate into ice at low temperatures, leading to fuel system failures and endangering flight safety. This study employed Karl Fischer titration in conjunction with an optimized combination of an oil moisture detector to jointly measure the water solubility of coal-based hydrocarbon fuels at room temperature. The coefficient correction was performed on the oil moisture detector, and the water solubility curves of coal-based hydrocarbon fuels 233 to 313 K were finally measured and compared with other literature results. Due to the extremely low water content in actual fuel and the uneven distribution of water in the fuel, this study mainly considers the water enrichment zone in the fuel.</p><h3>Methods</h3><p>Materials Studio 2019 software was utilized to simulate a representative molecular model of coal-based hydrocarbon fuel and a molecular model of water. The positions and charges of the atoms were set and tested, with the COMPASS force field selected to describe interatomic interactions. This force field is the first de novo computing field capable of accurately predicting interactions between various molecules and polymers. Geometry optimization was performed in the Forcite module, and the Construction tool in the Amorphous Cell Tools module was used to construct a coal-based hydrocarbon fuel system. The two models consisted of 3674 and 3671 atoms, respectively, with initial dimensions of 33.2 × 33.2 × 33.2 Å, the boundary conditions are periodic boundary conditions, the energy of the two models is minimized, the conjugate gradient method is used as the optimization method, and then the NPT annealing and kinetic pre-equilibrium operations are carried out, and the molecular dynamics simulation is carried out after the system relaxes to steady state. Through the MD method, the macroscopic phenomenon of temperature decrease in coal-based hydrocarbon fuel systems was analyzed from a microscopic perspective using mean square displacement, diffusion coefficient, and radial distribution function. It was predicted that the crystallization process of coal-based hydrocarbon fuel systems was mainly around 248 to 258 K.</p></div>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143423177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Multi-epitope vaccine (MEV) construction is a technique which combines multiple epitopes, both B cell epitopes and T cell epitopes which have the potential to elicit a much stronger immune response compared to a subunit vaccine. Therefore, recently, a lot of research has been focused on development and improvement of multiepitope vaccines. The strategy of designing a MEV in silico lies in a few basic steps, including procuring the amino acid sequence of the B cell and T cell epitopes from literature search, bioinformatics approach, to construct a potent immunogen capable of eliciting both humoral and cell-mediated response and finally joining these epitopes by linkers. However, a vaccine constructed by merely joining the epitopes may not always result in a stable globular structured protein. In this study, we have focused on developing a strategy where a potential vaccine candidate of Mycobacterium tuberculosis has been used as a scaffold and the low complexity regions of this scaffold have been replaced by the predicated epitopes. Essentially, instead of joining the epitopes by linkers, they have been carefully positioned on a scaffold of a protein that is itself a vaccine candidate to derive a MEV against Mycobacterium tuberculosis.
Method
In this study, a methodology has been detailed to tackle this great challenge using a simple approach of protein engineering. A scaffold-based MEV has been designed against Mtb by converting a vaccine candidate protein, Ag85A, into a scaffold by truncating its low complexity non-immunogenic regions, and the gaps were supplemented by the highly immunogenic epitopes. Replicated 500 ns molecular dynamics simulation at different temperatures (300 K and 310 K) and principal component analysis proved that MEV built on the scaffold is more stable than the conventional one.
{"title":"Molecular dynamics simulation shows enhanced stability in scaffold-based macromolecule, designed by protein engineering: a novel methodology adapted for converting Mtb Ag85A to a multi-epitope vaccine","authors":"Ditipriya Hazra, Shakilur Rahman, Manisha Ganguly, Amit Kumar Das, Amlan Roychowdhury","doi":"10.1007/s00894-025-06301-2","DOIUrl":"10.1007/s00894-025-06301-2","url":null,"abstract":"<div><h3>Context</h3><p>Multi-epitope vaccine (MEV) construction is a technique which combines multiple epitopes, both B cell epitopes and T cell epitopes which have the potential to elicit a much stronger immune response compared to a subunit vaccine. Therefore, recently, a lot of research has been focused on development and improvement of multiepitope vaccines. The strategy of designing a MEV in silico lies in a few basic steps, including procuring the amino acid sequence of the B cell and T cell epitopes from literature search, bioinformatics approach, to construct a potent immunogen capable of eliciting both humoral and cell-mediated response and finally joining these epitopes by linkers. However, a vaccine constructed by merely joining the epitopes may not always result in a stable globular structured protein. In this study, we have focused on developing a strategy where a potential vaccine candidate of <i>Mycobacterium tuberculosis</i> has been used as a scaffold and the low complexity regions of this scaffold have been replaced by the predicated epitopes. Essentially, instead of joining the epitopes by linkers, they have been carefully positioned on a scaffold of a protein that is itself a vaccine candidate to derive a MEV against <i>Mycobacterium tuberculosis.</i></p><h3>Method</h3><p>In this study, a methodology has been detailed to tackle this great challenge using a simple approach of protein engineering. A scaffold-based MEV has been designed against Mtb by converting a vaccine candidate protein, Ag85A, into a scaffold by truncating its low complexity non-immunogenic regions, and the gaps were supplemented by the highly immunogenic epitopes. Replicated 500 ns molecular dynamics simulation at different temperatures (300 K and 310 K) and principal component analysis proved that MEV built on the scaffold is more stable than the conventional one.</p></div>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143423255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-13DOI: 10.1007/s00894-025-06307-w
Nicolás Amigo
Context
Understanding the shear response of metallic glasses is essential for predicting their mechanical performance and plasticity. Cu(_{100-x})Zr(_x) metallic glasses, in particular, exhibit complex shear-thinning behavior governed by atomic composition. Prior studies have highlighted the role of composition in influencing mechanical properties; however, the relationship between the structural characteristics of these alloys and their rheological behavior requires further investigation. This work focuses on the effects of Cu content on the plastic flow of CuZr metallic glasses, emphasizing how atomic-scale features influence yield stress, viscosity, and the onset of plasticity.
Methods
Molecular dynamics simulations using the embedded atom method potential in LAMMPS were conducted to study Cu(_{100-x})Zr(_x) metallic glasses. Samples were equilibrated at 2000 K and quenched to 300 K at 10(^{11}) K/s. Shear tests at six rates ((5 times 10^{7}) to (1 times 10^{10}) s(^{-1})) were performed at 300 K, with the flow stress modeled using the Herschel-Bulkley equation. Structural features were analyzed via Voronoi polyhedra, focusing on local five-fold symmetry and liquid-like polyhedra populations. Visualization and data analysis were conducted using OVITO and Scikit-learn library for the Python programming language.
{"title":"Rheological characterization of CuZr metallic glasses at the atomic scale","authors":"Nicolás Amigo","doi":"10.1007/s00894-025-06307-w","DOIUrl":"10.1007/s00894-025-06307-w","url":null,"abstract":"<div><h3>Context</h3><p>Understanding the shear response of metallic glasses is essential for predicting their mechanical performance and plasticity. Cu<span>(_{100-x})</span>Zr<span>(_x)</span> metallic glasses, in particular, exhibit complex shear-thinning behavior governed by atomic composition. Prior studies have highlighted the role of composition in influencing mechanical properties; however, the relationship between the structural characteristics of these alloys and their rheological behavior requires further investigation. This work focuses on the effects of Cu content on the plastic flow of CuZr metallic glasses, emphasizing how atomic-scale features influence yield stress, viscosity, and the onset of plasticity.</p><h3>Methods</h3><p>Molecular dynamics simulations using the embedded atom method potential in LAMMPS were conducted to study Cu<span>(_{100-x})</span>Zr<span>(_x)</span> metallic glasses. Samples were equilibrated at 2000 K and quenched to 300 K at 10<span>(^{11})</span> K/s. Shear tests at six rates (<span>(5 times 10^{7})</span> to <span>(1 times 10^{10})</span> s<span>(^{-1})</span>) were performed at 300 K, with the flow stress modeled using the Herschel-Bulkley equation. Structural features were analyzed via Voronoi polyhedra, focusing on local five-fold symmetry and liquid-like polyhedra populations. Visualization and data analysis were conducted using OVITO and Scikit-learn library for the Python programming language.</p></div>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143396669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-13DOI: 10.1007/s00894-025-06304-z
Nathália M. P. Rosa, Itamar Borges Jr.
Context
Organic solar cells (OSCs) represent a promising renewable energy technology due to their flexibility, low production cost, and environmental sustainability. To advance OSC efficiency and stability, density functional theory (DFT) has emerged as a powerful computational tool, enabling the prediction and optimization of critical properties at the molecular and device levels. This review highlights the key properties of bulk heterojunction solar (BHJ) solar cells and dye-sensitized solar cells (DSSCs) that can be accurately computed using DFT, including electronic structure properties (HOMO–LUMO energy levels, bandgap energies, and exciton binding energies, which influence charge separation and transport); optical properties (absorption spectra and light-harvesting efficiency, essential for maximizing photon capture); charge transport properties (reorganization energies, electron, and hole mobilities, and charge transfer rates that govern carrier dynamics within devices); interfacial properties (energy alignment at donor–acceptor interfaces, contributing to efficient charge separation and minimizing recombination); and chemical reactivity descriptors (ionization potential, electron affinity, chemical hardness, and electrophilicity, which facilitate material screening for OSC applications). We also show how to compute OSCs’ power conversion efficiency (PCE) from DFT.
Methods
The review also discusses the importance of selecting appropriate exchange–correlation functionals and basis sets to ensure the accuracy of DFT predictions. By providing reliable computational insights, DFT accelerates the rational design of OSC materials, guides experimental efforts, and reduces resource demands. This work underscores DFT’s pivotal role in optimizing OSC performance and fostering the development of next-generation photovoltaic technologies.
{"title":"Review on the DFT computation of bulk heterojunction and dye-sensitized organic solar cell properties","authors":"Nathália M. P. Rosa, Itamar Borges Jr.","doi":"10.1007/s00894-025-06304-z","DOIUrl":"10.1007/s00894-025-06304-z","url":null,"abstract":"<div><h3>Context</h3><p>Organic solar cells (OSCs) represent a promising renewable energy technology due to their flexibility, low production cost, and environmental sustainability. To advance OSC efficiency and stability, density functional theory (DFT) has emerged as a powerful computational tool, enabling the prediction and optimization of critical properties at the molecular and device levels. This review highlights the key properties of bulk heterojunction solar (BHJ) solar cells and dye-sensitized solar cells (DSSCs) that can be accurately computed using DFT, including <i>electronic structure properties</i> (HOMO–LUMO energy levels, bandgap energies, and exciton binding energies, which influence charge separation and transport); <i>optical properties</i> (absorption spectra and light-harvesting efficiency, essential for maximizing photon capture); <i>charge transport properties</i> (reorganization energies, electron, and hole mobilities, and charge transfer rates that govern carrier dynamics within devices); <i>interfacial properties</i> (energy alignment at donor–acceptor interfaces, contributing to efficient charge separation and minimizing recombination); and <i>chemical reactivity descriptors</i> (ionization potential, electron affinity, chemical hardness, and electrophilicity, which facilitate material screening for OSC applications). We also show how to compute OSCs’ power conversion efficiency (PCE) from DFT.</p><h3>Methods</h3><p>The review also discusses the importance of selecting appropriate exchange–correlation functionals and basis sets to ensure the accuracy of DFT predictions. By providing reliable computational insights, DFT accelerates the rational design of OSC materials, guides experimental efforts, and reduces resource demands. This work underscores DFT’s pivotal role in optimizing OSC performance and fostering the development of next-generation photovoltaic technologies.</p></div>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143396668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-12DOI: 10.1007/s00894-025-06308-9
Zhen Zhao, Hao Zhang, Xiaoyan Zhuang, Lijuan Yan, Guangyong Li, Jun Li, Hui Yan
Context
Lipid nanoparticles (LNPs) are a novel type of drug delivery carrier, which play a protective role in nucleic acid drug delivery. LNPs are composed of various organic materials and these compositions assume corresponding tasks. Among these components, ionizable lipids undergo localized accumulation of lipids after exposure to the acidic pH environment of endosomes due to electrostatic interactions between lipid nanoparticles and phospholipids in endosomal membranes, which contributes to membrane fusion-disruption, endosomal escape, and cargo release. However, these extrapolations lack intuitive evidence at the molecular level, so we perform computational simulations to provide a microscopic view of molecular and cellular biological events. In this work, we performed molecular dynamics (MD) simulations to study the microscopic mechanism of membrane disruption induced by the protonation of ionizable lipids. Models containing different concentrations of ionizable lipids were obtained by simulating the uptake process of ionizable lipids by the endosomal membrane. The simulated results showed that the protonated ionizable lipids accumulated on one side of the endosomal membrane. Through the analysis of intermolecular interactions, it was found that the accumulation was due to the strong association of the head groups of the protonated ionizable lipids with the membrane lipids. Whereas the unprotonated ionizable lipids were dispersed on both sides of the bilayer, which served to stabilize the nanoparticles. The accumulation of ionizable lipids caused a sustained effect on lipid order parameters and the thickness of the simulated bilayer, which may be responsible for endosomal membrane rupture.
Methods
In this study, we employed MD simulations and used the GROMOS 54A7 united-atom force field to investigate the passive diffusion process of ionizable lipids. MD simulations were performed using the GROMACS 2019 software, focusing on the changes in the energy and molecular distribution of the system during the uptake process of ionizable lipids. Characteristics such as SDC, thickness, and energy of the system configuration at the end of the process are also analyzed. These configurations of the simulations were visualized using VMD. The GridMAT-MD package was adopted to analyze the thickness of the membrane. The other characters such as density distribution profiles and energies were analyzed using the tools within the GROMACS package.
{"title":"In silico insights into the membrane disruption induced by the protonation of ionizable lipids","authors":"Zhen Zhao, Hao Zhang, Xiaoyan Zhuang, Lijuan Yan, Guangyong Li, Jun Li, Hui Yan","doi":"10.1007/s00894-025-06308-9","DOIUrl":"10.1007/s00894-025-06308-9","url":null,"abstract":"<div><h3>Context</h3><p>Lipid nanoparticles (LNPs) are a novel type of drug delivery carrier, which play a protective role in nucleic acid drug delivery. LNPs are composed of various organic materials and these compositions assume corresponding tasks. Among these components, ionizable lipids undergo localized accumulation of lipids after exposure to the acidic pH environment of endosomes due to electrostatic interactions between lipid nanoparticles and phospholipids in endosomal membranes, which contributes to membrane fusion-disruption, endosomal escape, and cargo release. However, these extrapolations lack intuitive evidence at the molecular level, so we perform computational simulations to provide a microscopic view of molecular and cellular biological events. In this work, we performed molecular dynamics (MD) simulations to study the microscopic mechanism of membrane disruption induced by the protonation of ionizable lipids. Models containing different concentrations of ionizable lipids were obtained by simulating the uptake process of ionizable lipids by the endosomal membrane. The simulated results showed that the protonated ionizable lipids accumulated on one side of the endosomal membrane. Through the analysis of intermolecular interactions, it was found that the accumulation was due to the strong association of the head groups of the protonated ionizable lipids with the membrane lipids. Whereas the unprotonated ionizable lipids were dispersed on both sides of the bilayer, which served to stabilize the nanoparticles. The accumulation of ionizable lipids caused a sustained effect on lipid order parameters and the thickness of the simulated bilayer, which may be responsible for endosomal membrane rupture.</p><h3>Methods</h3><p>In this study, we employed MD simulations and used the GROMOS 54A7 united-atom force field to investigate the passive diffusion process of ionizable lipids. MD simulations were performed using the GROMACS 2019 software, focusing on the changes in the energy and molecular distribution of the system during the uptake process of ionizable lipids. Characteristics such as SDC, thickness, and energy of the system configuration at the end of the process are also analyzed. These configurations of the simulations were visualized using VMD. The GridMAT-MD package was adopted to analyze the thickness of the membrane. The other characters such as density distribution profiles and energies were analyzed using the tools within the GROMACS package.</p></div>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143396653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-10DOI: 10.1007/s00894-025-06305-y
L. Santiago-Silva, H. Cruz-Martínez, H. Rojas-Chávez, L. López-Sosa, P. Calaminici
Context
Transition metal nanoparticles have gained great importance due to their promising applications in various fields such as energy, electronics, medicine, and agriculture. For these applications, materials with outstanding properties are currently required. Therefore, different strategies have been established to improve the properties of pure nanoparticles such as alloying, doping, and formation of composites. Among these strategies, doping is gaining great importance because it has been demonstrated that doped nanoparticles have better properties than pure nanoparticles. Therefore, it is essential to know the role of doping on the structures and properties of clusters with more than 16 atoms. Consequently, in this study, we propose a theoretical study of structures and properties focusing on pure Pd19, Cu-doped Pd18 (Pd18Cu), and Cu2-doped Pd17 (Pd17Cu2) nanoclusters and thus elucidate the role of Cu atoms on the structures and properties of larger doped Pd nanoclusters than those already presented in the literature. We have selected a nanocluster with 19 atoms since the most stable structure of this system is characterized by defined shapes such as octahedron or double-icosahedron.
Methods
Ground state structures and properties of Pd19, Pd18Cu, and Pd17Cu2 nanoclusters were studied using the auxiliary density functional theory (ADFT), as implemented in the deMon2k code. For obtaining the ground state structures of Pd19, Pd18Cu, and Pd17Cu2 nanoclusters, several dozen initial structures were taken along Born–Oppenheimer molecular dynamics (BOMD) trajectories and subsequently optimized without symmetry restrictions. The optimizations were performed with the revised PBE functional in combination with TZVP-GGA for the Cu atoms and using an 18-electron QECP|SD basis set for the Pd atoms. Different energetic and electronic properties were calculated for the most stable structures of Pd19, Pd18Cu, and Pd17Cu2 nanoclusters. Interestingly, when the Pd nanocluster is doped with two Cu atoms (Pd17Cu2), there is a structural transition, because the most stable structures for Pd19 and Pd18Cu are icosahedral. While the Pd17Cu nanocluster is characterized for a double-icosahedral-base structure. The binding energy per atom increases when the Cu concentration in the nanoclusters increases. According to the HOMO–LUMO gap, the chemical reactivity of the nanoclusters tends to increase as the Cu content in the nanoclusters increases.
{"title":"Structural transformation in Pd nanoclusters induced by Cu doping: an ADFT study","authors":"L. Santiago-Silva, H. Cruz-Martínez, H. Rojas-Chávez, L. López-Sosa, P. Calaminici","doi":"10.1007/s00894-025-06305-y","DOIUrl":"10.1007/s00894-025-06305-y","url":null,"abstract":"<div><h3>Context</h3><p>Transition metal nanoparticles have gained great importance due to their promising applications in various fields such as energy, electronics, medicine, and agriculture. For these applications, materials with outstanding properties are currently required. Therefore, different strategies have been established to improve the properties of pure nanoparticles such as alloying, doping, and formation of composites. Among these strategies, doping is gaining great importance because it has been demonstrated that doped nanoparticles have better properties than pure nanoparticles. Therefore, it is essential to know the role of doping on the structures and properties of clusters with more than 16 atoms. Consequently, in this study, we propose a theoretical study of structures and properties focusing on pure Pd<sub>19</sub>, Cu-doped Pd<sub>18</sub> (Pd<sub>18</sub>Cu), and Cu<sub>2</sub>-doped Pd<sub>17</sub> (Pd<sub>17</sub>Cu<sub>2</sub>) nanoclusters and thus elucidate the role of Cu atoms on the structures and properties of larger doped Pd nanoclusters than those already presented in the literature. We have selected a nanocluster with 19 atoms since the most stable structure of this system is characterized by defined shapes such as octahedron or double-icosahedron.</p><h3>Methods</h3><p>Ground state structures and properties of Pd<sub>19</sub>, Pd<sub>18</sub>Cu, and Pd<sub>17</sub>Cu<sub>2</sub> nanoclusters were studied using the auxiliary density functional theory (ADFT), as implemented in the deMon2k code. For obtaining the ground state structures of Pd<sub>19</sub>, Pd<sub>18</sub>Cu, and Pd<sub>17</sub>Cu<sub>2</sub> nanoclusters, several dozen initial structures were taken along Born–Oppenheimer molecular dynamics (BOMD) trajectories and subsequently optimized without symmetry restrictions. The optimizations were performed with the revised PBE functional in combination with TZVP-GGA for the Cu atoms and using an 18-electron QECP|SD basis set for the Pd atoms. Different energetic and electronic properties were calculated for the most stable structures of Pd<sub>19</sub>, Pd<sub>18</sub>Cu, and Pd<sub>17</sub>Cu<sub>2</sub> nanoclusters. Interestingly, when the Pd nanocluster is doped with two Cu atoms (Pd<sub>17</sub>Cu<sub>2</sub>), there is a structural transition, because the most stable structures for Pd<sub>19</sub> and Pd<sub>18</sub>Cu are icosahedral. While the Pd<sub>17</sub>Cu nanocluster is characterized for a double-icosahedral-base structure. The binding energy per atom increases when the Cu concentration in the nanoclusters increases. According to the HOMO–LUMO gap, the chemical reactivity of the nanoclusters tends to increase as the Cu content in the nanoclusters increases.</p></div>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s00894-025-06305-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-10DOI: 10.1007/s00894-025-06306-x
Maxim R. Ryzhikov, Svetlana G. Kozlova
Context
Defects have a noticeable influence on many properties of two-dimensional materials. The controlled formation of defects can be used for fine-tuning the electronic and chemical properties of transition metal dichalcogenide monolayers. The formation of a new type of displacement defect on the molybdenum disulfide (MoS2) monolayer surface has been studied using density functional theory. In the defect structure, two sulfur atoms form a disulfide bridge between the Mo atoms. The sulfur-sulfur bond is confirmed by interatomic distances, atomic charges, and Electron Localization Function analysis.
Methods
The PBEsol density functional in the BAND2017 and VASP software packages was used for structural relaxation and NEB pathway calculations for the MoS2 monolayers. The Slater-type orbital basis set TZP and PAW pseudopotential were used in the BAND2017 and VASP 6.2.0 codes, respectively. Additionally, single-point calculations with SCAN and HSE06 density functionals were performed. QTAIM charges and ELF distributions were calculated using the BAND2017 package.
{"title":"Theoretical prediction of disulfide defects (S22−) in molybdenum disulfide monolayers","authors":"Maxim R. Ryzhikov, Svetlana G. Kozlova","doi":"10.1007/s00894-025-06306-x","DOIUrl":"10.1007/s00894-025-06306-x","url":null,"abstract":"<div><h3>Context</h3><p>Defects have a noticeable influence on many properties of two-dimensional materials. The controlled formation of defects can be used for fine-tuning the electronic and chemical properties of transition metal dichalcogenide monolayers. The formation of a new type of displacement defect on the molybdenum disulfide (MoS<sub>2</sub>) monolayer surface has been studied using density functional theory. In the defect structure, two sulfur atoms form a disulfide bridge between the Mo atoms. The sulfur-sulfur bond is confirmed by interatomic distances, atomic charges, and Electron Localization Function analysis.</p><h3>Methods</h3><p>The PBEsol density functional in the BAND2017 and VASP software packages was used for structural relaxation and NEB pathway calculations for the MoS<sub>2</sub> monolayers. The Slater-type orbital basis set TZP and PAW pseudopotential were used in the BAND2017 and VASP 6.2.0 codes, respectively. Additionally, single-point calculations with SCAN and HSE06 density functionals were performed. QTAIM charges and ELF distributions were calculated using the BAND2017 package.</p></div>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S100 calcium-binding protein A9 (S100A9) is easily assembled into amyloid aggregates in solution. These amyloid aggregates cause retinal toxicity and act as an attachment core for Aβ fibrillar plaques that contribute to Alzheimer’s disease progression. The overexpression of S100A9 is also noticed in various malignancies. Therefore, the S100A9 amyloid formation inhibition is of significant interest. In comparison with small-molecule drugs, short peptides demonstrate higher specificity, potency, and biosafety. Hence, it could be beneficial to identify potential peptides to inhibit or disrupt S100A9 amyloid aggregation. Typical peptide design and identification via experimental means requires extensive preparation procedures and is limited to random selection of peptides. Virtual screening therefore offers an unbiased, higher throughput, and economically efficient approach in peptide drug development. Here, we reported in silico pentapeptide design against S100A9 and studied the interaction of pentapeptide with S100A9 that leads to the binding of the peptide with S100A9.
Method
Docking simulation resulted in three top binding free energy tripeptides (WWF, WPW, and YWF) with comparable affinity towards a known S100A9 inhibitor (polyphenol oleuropein aglycone; OleA). Subsequently, pentapeptides that consist of the three core tripeptides were selected from a pre-constructed pentapeptide library for further evaluation with docking simulation. Based on best docked binding free energy, two pentapeptides (WWPWH and WPWYW) were selected and subjected to 500 ns molecular dynamics (MD) simulation to study the important features that lead to the binding with S100A9. MMGBSA binding free energy calculation estimated − 30.38, − 24.58, and − 30.31 kcal/mol for WWPWH, WPWYW, and OleA, respectively. The main driving force for pentapeptide-S100A9 recognition was contributed by the electrostatic interaction. The results demonstrate that at in silico level, this workflow is able to design potential pentapeptides that are comparable with OleA and might be the lead molecule for future use to disaggregate S100A9 fibrils.
{"title":"In silico pentapeptide design for the inhibition between S100 calcium-binding A9 (S100A9) proteins","authors":"Jintao Pan, Chong Lee Ng, Theam Soon Lim, Yee Siew Choong","doi":"10.1007/s00894-025-06298-8","DOIUrl":"10.1007/s00894-025-06298-8","url":null,"abstract":"<div><h3>Context</h3><p>S100 calcium-binding protein A9 (S100A9) is easily assembled into amyloid aggregates in solution. These amyloid aggregates cause retinal toxicity and act as an attachment core for Aβ fibrillar plaques that contribute to Alzheimer’s disease progression. The overexpression of S100A9 is also noticed in various malignancies. Therefore, the S100A9 amyloid formation inhibition is of significant interest. In comparison with small-molecule drugs, short peptides demonstrate higher specificity, potency, and biosafety. Hence, it could be beneficial to identify potential peptides to inhibit or disrupt S100A9 amyloid aggregation. Typical peptide design and identification via experimental means requires extensive preparation procedures and is limited to random selection of peptides. Virtual screening therefore offers an unbiased, higher throughput, and economically efficient approach in peptide drug development. Here, we reported <i>in silico</i> pentapeptide design against S100A9 and studied the interaction of pentapeptide with S100A9 that leads to the binding of the peptide with S100A9.</p><h3>Method</h3><p>Docking simulation resulted in three top binding free energy tripeptides (WWF, WPW, and YWF) with comparable affinity towards a known S100A9 inhibitor (polyphenol oleuropein aglycone; OleA). Subsequently, pentapeptides that consist of the three core tripeptides were selected from a pre-constructed pentapeptide library for further evaluation with docking simulation. Based on best docked binding free energy, two pentapeptides (WWPWH and WPWYW) were selected and subjected to 500 ns molecular dynamics (MD) simulation to study the important features that lead to the binding with S100A9. MMGBSA binding free energy calculation estimated − 30.38, − 24.58, and − 30.31 kcal/mol for WWPWH, WPWYW, and OleA, respectively. The main driving force for pentapeptide-S100A9 recognition was contributed by the electrostatic interaction. The results demonstrate that at <i>in silico</i> level, this workflow is able to design potential pentapeptides that are comparable with OleA and might be the lead molecule for future use to disaggregate S100A9 fibrils.</p></div>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143361785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-08DOI: 10.1007/s00894-025-06303-0
Akinwunmi O. Adeoye, Kevin A. Lobb
Context
Cysteine and aspartic proteases are enzyme families that play crucial roles in the life cycle of Plasmodium, the parasite responsible for malaria. These proteases are involved in vital biological processes, such as hemoglobin degradation within the host’s red blood cells, protein turnover, and regulation of parasite development. Inhibiting these proteases with small molecule drugs can block the parasite’s growth and survival. Chemically, these enzymes have specific active sites where inhibitors can bind, preventing the breakdown of key proteins, making them attractive targets for the design of novel antimalarial compounds. Understanding the structure and catalytic mechanisms of these proteases is critical for developing selective and potent inhibitors. The degradation of hemoglobin occurs in the parasite’s digestive vacuole, and disruption of this process by targeting these proteases can inhibit parasite development, leading to the death of the parasite. Hence, these proteases are critical for maintaining the parasite’s metabolic functions, and inhibiting them can disrupt the parasite’s life cycle. Malaria remains a major global health problem, particularly in tropical and subtropical regions, where resistance to existing antimalarial drugs, such as chloroquine and artemisinin-based therapies, is an escalating issue. The emergence of drug-resistant Plasmodium strains highlights the urgent need for new therapeutic strategies. Targeting cysteine and aspartic proteases offers a novel approach to antimalarial drug development, as these enzymes are crucial for parasite survival and have not been widely exploited in current therapies. By inhibiting these proteases, researchers aim to develop new antimalarial treatments that could overcome resistance mechanisms and provide more effective options for malaria control and eradication.
Methods
The application of computational methods such as molecular docking, dynamics simulations, and quantum mechanical calculations, combined with powerful molecular modeling tools, provides a comprehensive framework for discovering and optimizing inhibitors targeting Plasmodium cysteine and aspartic proteases. These methods facilitate the rational design of novel antimalarial drugs, offering a pathway to overcome drug resistance and improve therapeutic outcomes.
{"title":"Malaria parasite cysteine and aspartic proteases as key drug targets for antimalarial therapy","authors":"Akinwunmi O. Adeoye, Kevin A. Lobb","doi":"10.1007/s00894-025-06303-0","DOIUrl":"10.1007/s00894-025-06303-0","url":null,"abstract":"<div><h3>Context</h3><p>Cysteine and aspartic proteases are enzyme families that play crucial roles in the life cycle of <i>Plasmodium</i>, the parasite responsible for malaria. These proteases are involved in vital biological processes, such as hemoglobin degradation within the host’s red blood cells, protein turnover, and regulation of parasite development. Inhibiting these proteases with small molecule drugs can block the parasite’s growth and survival. Chemically, these enzymes have specific active sites where inhibitors can bind, preventing the breakdown of key proteins, making them attractive targets for the design of novel antimalarial compounds. Understanding the structure and catalytic mechanisms of these proteases is critical for developing selective and potent inhibitors. The degradation of hemoglobin occurs in the parasite’s digestive vacuole, and disruption of this process by targeting these proteases can inhibit parasite development, leading to the death of the parasite. Hence, these proteases are critical for maintaining the parasite’s metabolic functions, and inhibiting them can disrupt the parasite’s life cycle. Malaria remains a major global health problem, particularly in tropical and subtropical regions, where resistance to existing antimalarial drugs, such as chloroquine and artemisinin-based therapies, is an escalating issue. The emergence of drug-resistant <i>Plasmodium</i> strains highlights the urgent need for new therapeutic strategies. Targeting cysteine and aspartic proteases offers a novel approach to antimalarial drug development, as these enzymes are crucial for parasite survival and have not been widely exploited in current therapies. By inhibiting these proteases, researchers aim to develop new antimalarial treatments that could overcome resistance mechanisms and provide more effective options for malaria control and eradication.</p><h3>Methods</h3><p>The application of computational methods such as molecular docking, dynamics simulations, and quantum mechanical calculations, combined with powerful molecular modeling tools, provides a comprehensive framework for discovering and optimizing inhibitors targeting <i>Plasmodium</i> cysteine and aspartic proteases. These methods facilitate the rational design of novel antimalarial drugs, offering a pathway to overcome drug resistance and improve therapeutic outcomes.</p></div>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143361784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号