Computational Insights Research Articles

Computational antigenic insights into the novel NADC-34-like Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) isolate YC-2020

In this computational study, we advanced the understanding of the antigenic properties of the NADC-34-like isolate of the Porcine Reproductive and Respiratory Syndrome Virus (PRRSV), named YC-2020, relevant in veterinary pathology. We utilized sequence comparison analyses of the M and N proteins, comparing them with those of NADC34, identifying substantial amino acid homology that allowed us to highlight conserved epitopes and crucial variants. Through the application of Clustal Omega for multiple sequence alignment and platforms like Vaxijen and AllerTOP for predicting antigenic and allergenic potential, our analyses revealed important insights into the conservation and variation of epitopes essential for the development of effective diagnostic tools and vaccines. Our findings, aligned with initial experimental studies, underscore the importance of these epitopes in the development of targeted immunodiagnostic platforms and significantly contribute to the management and control of PRRSV. However, further studies are required to validate the computational predictions of antigenicity for this new viral isolate. This approach underscores the potential of computational models to enable ongoing monitoring and control of PRRSV evolution in swine. While this study provides valuable insights into the antigenic properties of the novel PRRSV isolate YC-2020 through computational analysis, it is important to acknowledge the limitations inherent to in silico predictions, specifically, the absence of laboratory validation.

Computational Insights into Phase Equilibria between Wide-Gap Semiconductors and Contact Materials

Computational Insights into Phase Equilibria between Wide-Gap Semiconductors and Contact Materials

Computational insights into the conformational transition of STING: Mechanistic, energetic considerations, and the influence of crucial mutations

STING (stimulator of interferon genes) is a crucial protein in the innate immune system's response to viral and bacterial infections. In this study, we investigated the mechanistic and energetic mechanism of the conformational transition process of STING activated by cGAMP binding. We found that the STING connector region undergoes an energetically unfavorable rotation during this process, which is compensated by the favorable interaction between cGAMP and the STING ligand binding domain. We further studied several disease-causing mutations and found that the V155 M mutation facilitates a smoother transition in the STING connector region. However, the V147L mutation exhibits unfavorable conformational transition energy, suggesting it may hinder STING activation pathway that relies on connector region rotation. Despite being labeled as hyperactive, the widespread prevalence of V147L/V147I mutations across species implies a neutral character, indicating complexity in its role. Overall, our analysis deepens the understanding of STING activation within the connector region, and targeting this region with compounds may provide an alternative approach to interfering with STING's function.

Antioxidant Properties and Aldose Reductase Inhibitory Potency of Viscum album L. Extracts: Experimental and Computational Insights

Antioxidant Properties and Aldose Reductase Inhibitory Potency of Viscum album L. Extracts: Experimental and Computational Insights

A Computational Insight on the Effect of Doping of Transition Metals and Group V Elements on the Electronic Properties of Phosphorene

A Computational Insight on the Effect of Doping of Transition Metals and Group V Elements on the Electronic Properties of Phosphorene

Computational insights into the electronic structure of functionalized monolayer hBN supercapacitor electrodes

In this study, we examined a collection of functionalized hBN monolayers’ electronic structure and quantum capacitance. Different ad-atom adsorption techniques have been used to functionalize the hBN monolayer. Density functional theory calculations are performed to precisely determine the electrical structure of an ad-atom doped hBN monolayer with a range of doping concentrations. The quantum capacitance of every functionalized system was then calculated. Above 500 μF/cm2, a noticeable quantum capacitance has been seen. Our calculations demonstrate that ad-atom doping at hollow position of hBN honeycomb lattice greatly increases the quantum capacitance of hBN monolayer. The microscopic cause of this system’s increased quantum capacitance has been investigated. Our DFT-based calculation shows that the system has a very large quantum capacitance due to the creation of new electronic states in the vicinity of the band edge and the Fermi level shift caused by the ad-atom adsorption.

Composition Engineering on the Structure and Transport Properties of CaO–SiO2–P2O5 System: A Computational Insight

Composition Engineering on the Structure and Transport Properties of CaO–SiO2–P2O5 System: A Computational Insight

A comprehensive study of imidazolium hydrogen maleate (IMHM) single crystal: computational and experimental insights for nonlinear optical applications

A comprehensive study of imidazolium hydrogen maleate (IMHM) single crystal: computational and experimental insights for nonlinear optical applications

Computational insights into the thermal performance enhancement of solar air heater channel through metal foam integration

Computational insights into the thermal performance enhancement of solar air heater channel through metal foam integration

Diving deep into the superior lubrication efficiency: A dynamic approach incorporating covalent organic polymer as strengthening booster in paraffin oil through a holistic blend of experimental and computational approaches

This research addresses the paramount importance of enhancing surface protection and minimizing friction in mechanical systems through the novel design of covalent organic polymer additive (COPA). COPA-1 and COPA-2 were intricately designed to enhance surface protection and minimize wear. Tribological analysis revealed that the addition of an optimized concentration of COPA-1 (25 ppm) to base oil significantly reduced friction (∼60.49% decrease) and wear (∼79.23% decrease) while increasing load-bearing capacity to 588 N. Rheological analysis confirmed excellent shear stability and desirable viscosity behavior. Furthermore, computational tools like density functional theory and molecular dynamics simulations provided valuable insights into the adsorption mechanisms and tribological performance. This integration of experimental and computational insights highlights the transformative potential of COPA in revolutionizing lubrication technology.

Unveiling the Computational Insights into Na‐Decorated Hydrogen‐Substituted Graphdiyne for Efficient Tracing and Trapping of Nitrogen and its Oxides

Addressing air pollution is a critical concern, particularly in the context of tracing and trapping nitrogen and its oxides (N2, N2O, NO, NO2) emitted from fuel combustion. In this context, this study delves into the potential of recently discovered Hydrogen-substituted Graphdiyne (HsGDY) and to enhance its adsorption capabilities by incorporating sodium (Na) metal atom computationally. Herein, the strategic sites for Na atom decoration on HsGDY is identified and the most stable site R1 with Eads = −0.820 eV is chosen for subsequent NOx adsorption studies. Through DFT calculations, we assess the adsorptive capacity of NOx gases onto both HsGDY and Na-decorated HsGDY (NaHsGDY) slabs. In particular NO2 gas molecule with Eads = −2.537 eV emphasizes greater adsorption over NaHsGDY slab. Analysis of electronic properties reveals significant reduction in the energy gap (Eg) of the NaHsGDY, indicating heightened reactivity toward NOx gases thereby resulting in substantial increase in the slab’s conductivity. Additionally, charge density difference and Löwdin charge analyses provides consistent evidence supporting enhancement in charge transfer during NOx gases adsorption after Na decoration. The NaHsGDY slab demonstrates high selectivity, sensitivity, and superior performance than HsGDY slab, positioning it as a promising candidate for targeted NOx gas molecules detection.

Comprehensive computational insights on the conformations, electronic properties and binding mechanism of mescaline: A hallucinogenic molecule

In the series of computational investigations of hallucinogenic compounds particularly in unraveling their conformational aspects, mescaline is taken up in this report after having studied psilocybin and psilocin. Six conformers were identified from the relaxed scan of the dihedral angles of which two were taken up for studying their chemical properties. The two low energy conformers differed by about 0.5 kcal.mol-1 at B3LYP/cc-pVTZ and 1.5 kcal.mol-1 at CCSD/cc-PVDZ levels of theory, respectively and structurally the two conformers differ by the orientation of the alkyl amine group vis-à-vis the benzene ring via the N–H---π interaction. Natural Bond Orbital calculations unveiled the existence of intra-molecular π → π*, n → π* charge transfers, and some hyperconjugative interactions that significantly enhance the stability of mescaline. Reduced Density Gradient calculations unraveled the occurrence of strong intramolecular N–H---π interaction in the most stable conformer of mescaline. The calculated geometrical parameters and predicted structure of the most stable conformer of mescaline agree significantly well with the earlier reported conformers from X-ray studies of mescaline. The computed λmax in the UV–visible spectrum, peak positions in the proton NMR spectrum, and vibrational modes exhibit excellent agreement with the previously reported experimental findings. Moreover, we utilized molecular docking and molecular dynamics simulations to elucidate the binding mode and molecular mechanism of mescaline in comparison to other hallucinogenic molecules. Our findings revealed that mescaline displayed a favorable binding energy and induced essential conformational changes, indicating a potential common mechanism of action shared with psilocybin, another hallucinogenic compound.

Dissipative Particle Dynamics Study on the Phase Region of Spatial Gradient Materials Produced by Photoinduced Isomerization

AbstractSpatial gradient materials occupy an important research position in the field of functional materials with their unique porous structure. Gradient changes in pore size and density distribution have received extensive attention in the fields of biomimetic and smart materials. The gradient transition law is mathematically related to the driving force of isomerization reaction and component phase separation. In this study, a dissipative particle dynamics simulation is used to introduce photoisomerization reactions into the system. Lambert's law is used to construct a reaction model for the variation of light intensity with irradiation depth, and a gradient structure with a spatial transition law is obtained. The effects of the extinction coefficient ε, the initial reaction probability Pr0, and the interactions α(A,B) between the isomerized molecules as well as the viscosity on the formation of the gradient structure are investigated in detail. Furthermore, the mathematical proportionality between the size of the phase region and interfacial energy of the two phases is elucidated. This study provides preliminary computational insights into the factors affecting the photoinduced phase separation process of polymeric gradient materials. It may help to develop effective strategies to improve the phase separation and properties of polymer gradient materials in subsequent studies.

Computational insights into diverse binding modes of the allosteric modulator and their regulation on dopamine D1 receptor

Allosteric drugs hold the promise of addressing many challenges in the current drug development of GPCRs. However, the molecular mechanism underlying their allosteric modulations remain largely elusive. The dopamine D1 receptor (DRD1), a member of Class A GPCRs, is critical for treating psychiatric disorders, and LY3154207 serves as its promising positive allosteric modulator (PAM). In the work, we utilized extensive Gaussian-accelerated molecular dynamics simulations (a total of 41μs) for the first time probe the diverse binding modes of the allosteric modulator and their regulation effects, based on the DRD1 and LY3154207 as representative. Our simulations identify four binding modes of LY3154207 (one boat mode, two metastable vertical modes and a novel cleft-anchored mode), in which the boat mode is the most stable while there three modes are similar in the stability. However, it is interesting to observed that the most stable boat mode inversely exhibits the weakest positive allosteric effect on influencing the orthosteric ligand binding and maintaining the activity of the transducer binding site. It should result from its induced weaker correlation between the allosteric site and the orthosteric site, and between the orthosteric site and the transducer binding site than the other three binding modes, as well as its weakened interaction between a crucial activation-related residue (S2025.46) and the orthosteric ligand (dopamine). Overall, the work offers atomic-level information to advance our understanding of the complex allosteric regulation on GPCRs, which is beneficial to the allosteric modulator design and development.

Predicting Food Distribution with Underlying Factors for a Hunger Relief Organization

ABSTRACT Hunger relief organizations often estimate food demand using food distribution data. Leveraging Visual Analytics (VA) and historical data, we examine how underlying factors like unemployment, poverty rate, and median household income affect forecasts for aid recipients’ food demand. Our study reveals that incorporating these factors enhances forecast accuracy. Visual Analytics empowers decision-makers to integrate field knowledge with computational insights, enabling more informed decisions. This innovative approach presents a valuable tool for charitable organizations to strategically improve forecasting precision in the dynamic landscape of hunger relief.

The Absorption Mechanisms of CO2, H2S and CH4 Molecules in [EMIM][SCN] and [EMIM][DCA] Ionic Liquids: A Computational Insight

This study investigates the absorption mechanisms of carbon dioxide (CO2), hydrogen sulfide (H2S), and methane (CH4) molecules in two imidazolium-based ionic liquids, namely 1-ethyl-3-methylimidazolium thiocyanate ([EMIM][SCN]) and 1-ethyl-3-methylimidazolium dicyanamide ([EMIM][DCA]). We employed molecular dynamics (MD) simulations applying umbrella sampling technique to calculate free energy profiles (FEPs) for gas molecules in the ILs. The results reveal CO2's pronounced affinity for the interface over the bulk in both ionic liquids (IL), whereas H2S exhibits facile penetration into both regions. CH4 shows limited penetration into the IL bulk, remaining predominantly near the interface. We further explore the influence of ILs' anionic structures on gas accumulation sites by performing normal MD simulations. For instance, density profiles also confirm CO2's higher density in [EMIM][DCA] compared to [EMIM][SCN], reflecting the influence of anionic composition on CO2 solubility. These insights offer valuable knowledge for designing efficient ILs for gas capture and separation applications.

Experimental and computational insights into the mechanism of destabilization of poly(acrylic acid)-capped silver nanoparticles induced by weak conjugate bases

Herein we report a systematic study of the effects of H2PO4− and ClO4− on the stability of poly(acrylic acid)-capped silver nanoparticles (PAA-AgNPs). Spectroscopic titration revealed that a smaller amount of ClO4− is required to detach PAA, and a blue-shift in surface plasmon resonance (SPR) was observed relative to H2PO4−, owing to its electron accepting nature which leads to a weaking of the PAA-AgNP donor bond. Experimental observations were supported by DFT calculations, which revealed that complexation of AgNPs with ionized PAA, H2PO4– and ClO4− is mediated by the electron affinity of the AgNP and the conjugated bases. Electron donation by the weak acids leads to the weakening of the PAA-AgNP donor bond, whereby ClO4− contributes more to the destabilization of the PAA capped AgNPs due to its greater electron affinity. Additionally, H2PO4− can form hydrogen bonds with PAA, which promotes the formation of aggregates. Moreover, DFT calculations have shown that the structure of the model Ag14 cluster is significantly distorted in the presence of H2PO4−, more so than in the case of ClO4−. The findings are supported by the experimental quantification of residual PAA by differential scanning calorimetry and solid-state total organic carbon analysis (SSM-TOC), and powder X-ray diffraction (XRD).

Phytotherapeutic potential of compounds identified from fractionated extracts of Morus alba L., as an inhibitor of interleukin-6 in the treatment of rheumatoid arthritis: computational approach

The presence of HLA-DRB1 alleles that encode critical points associated with environmental interactions is associated with increased risk of rheumatoid arthritis caused by anti-citrullinated protein antibodies. Therefore, interleukin-6 (IL-6), a multifunctional cytokine that controls both local and systemic acute inflammatory responses through its ability to induce a phase response, plays a serious role. Its overexpression leads to pathological challenges such as rheumatoid arthritis and menopausal osteoporosis. However, targeting the IL-6 receptor and its region could be the major step in controlling the overexpression of this cytokine for therapeutic importance. Therefore, our research explored the computational insight needed to investigate the anti-RFA potential of phytochemicals from fractionated extracts of Morus alba L. against receptors, which have been implicated as druggable targets for the treatment of rheumatoid arthritis. In this study, fifty-nine (59) previously isolated and characterized phytochemicals from M. alba L. were identified from the literature and retrieved from the PubChem database. In silico screening was used to assess the mode of action of these phytochemicals from M. alba L. against receptors that may serve as therapeutic targets for rheumatoid arthritis. Molecular docking studies, toxicity prediction, drug visualization and molecular dynamics simulation (MD) of the ligands together with the receptor-identified target were carried out using the Schrodinger Molecular Drug Discovery Suite. The findings indicated that a selected group of ligands displayed significant binding strength to specific amino acid residues, revealing an important link between the building blocks of proteins (amino acids) and ligands at the inhibitor binding site through traditional chemical interactions, such as interactions between hydrophobic and hydrogen bonds. The binding affinities of the receptors were carefully checked via comparison with those of the approved ligands, and the results suggested structural and functional changes in the lead compounds. Therefore, the bioactive component from M. alba L. could be a lead foot interleukin-6 (IL-6) inhibitor and could be a promising lead compound for the treatment of rheumatoid arthritis and related challenges. Communicated by Ramaswamy H. Sarma

Computational insights in cell physiology

Physiological processes are governed by intricate networks of transcriptional and post-translational regulations. Inter-cellular interactions and signaling pathways further modulate the response of the cells to environmental conditions. Understanding the dynamics of these systems in healthy conditions and their alterations in pathologic situations requires a “systems” approach. Computational models allow to formalize and to simulate the dynamics of complex networks. Here, we briefly illustrate, through a few selected examples, how modeling helps to answer non-trivial questions regarding rhythmic phenomena, signaling and decision-making in cellular systems. These examples relate to cell differentiation, metabolic regulation, chronopharmacology and calcium dynamics.

Integrated insights into the structure, spectroscopy, and reactivity of a novel Brucinium Tetraphenylborate: A comprehensive computational and experimental study

The current study examines the crystal development and structure of a recently synthesized 2,3-dimethoxystrychnidin-10-one (brucine) tetraphenylborate, using both experimental and theoretical examinations. Brucinium tetraphenylborate crystal (1) was successfully synthesized and characterized using Single Crystal X-ray Diffraction. The crystal lattice is intricately defined by prevailing N/C-H···O hydrogen bonds and O/C-H···π interactions, establishing a cohesive molecular network. To elucidate intermolecular interactions within the crystal packing, Hirshfeld surface analysis and 2D fingerprint plots are employed. Validation of experimental findings is conducted through rigorous Density Functional Theory (DFT) calculations employing the B3LYP and CAM-B3LYP functionals, in conjunction with the 6–311+G* basis set. The reactivity profile of the title molecule is systematically explored through the analysis of frontier molecular orbitals (FMO), HOMO-LUMO energies, molecular electrostatic potential (MEP), and global chemical reactivity descriptors. Notably, computational insights reveal that the energy gap (Eg) and other chemical reactivity descriptors are intricately associated with both tetraphenylborate and brucine moieties. This emphasizes their pivotal roles in the overall activity and antioxidant capacity of the molecule. This research contributes to the understanding of the intricate molecular dynamics, shedding light on key factors influencing the compound's reactivity and potential antioxidant properties.