Normal Mode Analysis Research Articles

Gravity effect in a piezo-thermoelastic diffusive medium with dual-phase-lag model

The model of generalized thermoelasticity, with the dual-phase-lag theory (DPL), is applied to study the influence of gravity on a piezo-thermoelastic diffusive medium. Normal mode analysis is used to obtain the exact expressions for different physical quantities. The derived expressions are computed numerically and the results are presented in graphical form. Comparisons are made with the results predicted by the Lord–Shulman theory (LS) and the DPL model in the presence and absence of gravity.

Influence of memory-dependent derivative on generalized thermoelastic rotating porous solid via three-phase-lag model

This paper is concerned with the influence of memory-dependent heat transport law on rotating thermoelastic medium with voids via three-phase-lag. The entire pervious medium is rotating with a invariant angular haste, where the bounding airplane is subordinated to a thermal shock and is free of tractions. By employing the normal mode analysis, the exact expressions for the displacement components, stresses, temperature distribution and change in volume fraction field have been depicted graphically in the presence and the absence of gyration and memory-dependent outgrowth. The effect of the voiding is also bandied in the literature review.

Revisiting the Ramachandran plot based on statistical analysis of static and dynamic characteristics of protein structures

Ramachandran plots, which describe protein structures by plotting the dihedral angle pairs of the backbone on a two-dimensional plane, have played an important role in structural biology over the past few decades. However, despite continued discovery of new protein structures to date, the Ramachandran plot is still constructed by only a small number of data points, and further it cannot reflect the steric information of proteins. Here, we investigated the secondary structure of proteins in terms of static and dynamic characteristics. As for static feature, the Ramachandran plot was revisited for the dataset consisting of 9,148 non-redundant high-resolution protein structures released in the protein data bank until April 1, 2022. By calculating amino acid propensities, it was found that the proportion of secondary structures with respect to residue depth is directly related to their hydrophobicity. As for dynamic feature, normal mode analysis (NMA) based on an elastic network model (ENM) was carried out for the dataset using our KOSMOS web server (http://bioengineering.skku.ac.kr/kosmos/). All ENM-based NMA results were stored in the KOSMOS database, allowing researchers to use them in various ways. In this process, it was commonly found that high B-factors appeared at the edge of the alpha helix region, which was elucidated by introducing residue depth. In addition, by investigating the change in dihedral angle, it was possible to quantitatively survey the contribution of structural change of protein on the Ramachandran plot. In conclusion, our statistical analysis of protein characteristics will provide insight into a range of protein structural studies.

Comparative Surface Electrostatics and Normal Mode Analysis of High and Low Pathogenic H7N7 Avian Influenza Viruses.

Influenza A viruses are rarely symptomatic in wild birds, while representing a higher threat to poultry and mammals, where they can cause a variety of symptoms, including death. H5 and H7 subtypes of influenza viruses are of particular interest because of their pathogenic potential and reported capacity to spread from poultry to mammals, including humans. The identification of molecular fingerprints for pathogenicity can help surveillance and early warning systems, which are crucial to prevention and protection from such potentially pandemic agents. In the past decade, comparative analysis of the surface features of hemagglutinin, the main protein antigen in influenza viruses, identified electrostatic fingerprints in the evolution and spreading of H5 and H9 subtypes. Electrostatic variation among viruses from avian or mammalian hosts was also associated with host jump. Recent findings of fingerprints associated with low and highly pathogenic H5N1 viruses, obtained by means of comparative electrostatics and normal modes analysis, prompted us to check whether such fingerprints can also be found in the H7 subtype. Indeed, evidence presented in this work showed that also in H7N7, hemagglutinin proteins from low and highly pathogenic strains present differences in surface electrostatics, while no meaningful variation was found in normal modes.

Immunoinformatic-Based Multi-Epitope Vaccine Design for Co-Infection of Mycobacterium tuberculosis and SARS-CoV-2.

(1) Background: Many co-infections of Mycobacterium tuberculosis (MTB) and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have emerged since the occurrence of the SARS-CoV-2 pandemic. This study aims to design an effective preventive multi-epitope vaccine against the co-infection of MTB and SARS-CoV-2. (2) Methods: The three selected proteins (spike protein, diacylglycerol acyltransferase, and low molecular weight T-cell antigen TB8.4) were predicted using bioinformatics, and 16 epitopes with the highest ranks (10 helper T lymphocyte epitopes, 2 CD8+ T lymphocytes epitopes, and 4 B-cell epitopes) were selected and assembled into the candidate vaccine referred to as S7D5L4. The toxicity, sensitization, stability, solubility, antigenicity, and immunogenicity of the S7D5L4 vaccine were evaluated using bioinformatics tools. Subsequently, toll-like receptor 4 docking simulation and discontinuous B-cell epitope prediction were performed. Immune simulation and codon optimization were carried out using immunoinformatics and molecular biology tools. (3) Results: The S7D5L4 vaccine showed good physical properties, such as solubility, stability, non-sensitization, and non-toxicity. This vaccine had excellent antigenicity and immunogenicity and could successfully simulate immune responses in silico. Furthermore, the normal mode analysis of the S7D5L4 vaccine and toll-like receptor 4 docking simulation demonstrated that the vaccine had docking potential and a stable reaction. (4) Conclusions: The S7D5L4 vaccine designed to fight against the co-infection of MTB and SARS-CoV-2 may be safe and effective. The protective efficacy of this promising vaccine should be further verified using in vitro and in vivo experiments.

INFLUENCE OF LOCAL THERMAL NON-EQUILIBRIUM ON THE STABILITY OF NANOFLUID FLOW IN AN INCLINED CHANNEL FILLED WITH POROUS MEDIUM

The effect of local thermal nonequilibrium on the stability of nanofluid flow in an inclined channel filled with a porous medium is numerically investigated. The Buongiorno model for nanofluid and Darcy-Brinkman model for flow in a porous medium are utilized, along with a three-field model for temperature, with each field representing the fluid, particle, and solid-matrix phases individually. The Chebyshev spectral collocation approach is used to determine the solution of the eigenvalue problem, which is obtained for perturbed states using a normal mode analysis. The impacts of various local thermal nonequilibrium parameters, the critical Rayleigh number, and associated wavenumber are displayed through graphs. It is worth noting that the LTNE parameters have a major impact on convective instability. Also, the dynamics of the flow field, behavior of temperature, and volume fraction are presented through streamlines, isotherms, and isonanoconcentration at the critical level.

INSTABILITY INVESTIGATION OF THERMO-BIOCONVECTION OF OXYTACTIC MICROORGANISM IN JEFFREY NANOLIQUID WITH EFFECTS OF INTERNAL HEAT SOURCE

The intent of this article is to investigate the influence of internal heat source on the stability of a suspension containing oxytactic microorganisms in a shallow horizontal porous fluid layer saturated by Jeffrey nanoliquid. The Jeffrey-Buongiorno model governs the nanofluid bioconvection flow. Normal mode analysis is utilized, and the principle of exchange of stability is invoked due to the absence of opposing agencies. The stability criteria is defined in terms of critical thermal Rayleigh number as a function of various flow governing parameters by using the weighted residual Galerkin method. It is perceived that the increment of uniform heat supply and the presence of oxytactic microorganism cells as well as the nanoparticles enhances heat transfer and constitutes an unstable system that hastens bioconvection. The nanoparticle Lewis number is found to have a dual impact on the system stability that relies on the nanoparticle Rayleigh number and exhibits destabilizing nature for top-heavy nanoparticle concentration. It is also observed that the Jeffrey parameter produces nonoscillatory instability in the system.

THE EFFECT OF LOCAL THERMAL NON-EQUILIBRIUM AND MAGNETIC FIELD ON THE STABILITY IN A VERTICAL CHANNEL FILLED WITH NANOFLUID

In this investigation, the influence of local thermal non-equilibrium (LTNE) on the onset of convection in a channel occupied with nanofluid was examined. The flow took place in the presence of a transverse magnetic field. The Buongiorno and two-field models (each independently signifying the fluid and particle phases) were used for the nanofluid and energy equation, respectively. A normal mode analysis was applied to obtain the eigenvalue problem for the disturbed state, which was solved using the Chebyshev spectral collocation technique. The effects of the governing parameters on the Rayleigh number and corresponding wavenumber are presented graphically. It was noticed that the concentration Rayleigh number, inter-phase heat transfer parameter, and modified diffusivity ratio had a destabilizing effect, while the modified thermal capacity ratio, thermal diffusivity ratio, Lewis number, and modified particle density increment had a stabilizing effect on the system.

LINEAR CONVECTIVE STABILITY IN AN INCLINED CHANNEL FILLED WITH A NANOFLUID-SATURATED POROUS MEDIUM

In this study, convective stability of nanofluid flow in an inclined porous channel is being numerically investigated. The effects of Brownian motion and thermophoresis are accounted for in the nanofluid model. In addition, the flow in the porous region governs Brinkman's equation. A normal mode analysis is used to get the eigenvalue problem for the perturbed state, which is then solved using the Chebyshev spectral collocation approach. The influence of various governing parameters, the critical Rayleigh number, and associated wavenumber are graphically displayed.

Design of a multi-epitope vaccine using HA and M1 proteins from influenza and S, E, and M proteins from SARS-CoV-2 by in silico tools

Among various infections, acute respiratory tract infections (ARTIs) have the highest incidence and mortality in the world. These infections are caused by various microorganisms such as the influenza and SARS-CoV-2 viruses. The potential effect of influenza alongside COVID-19 on mortality, morbidity, and health-service capacity is a main concern, although, recently, little is understood about the interaction between these two pathogenic respiratory viruses. Thus, the creation and development of effective vaccines are urgently needed to stop the spread of these diseases. In this study, we created a novel multi-epitope vaccine to protect against SARS-CoV-2 and influenza infections. For usage in vaccine construction, the HA and M1 proteins from the influenza virus and the S, E, and M proteins from the SARS-CoV-2 virus were examined. Using various bioinformatics techniques, the discovery of B and T cell epitopes, energy minimization, prediction of Interferon-gamma response, allergenicity, and toxicity were carried out. The most effective peptides were chosen via molecular docking. To create a multi-epitope vaccine, the chosen epitopes were mixed with the appropriate linkers and adjuvant. The I-TASSER server created the 3D model of the vaccine candidate. Optimization and evaluation of this model were investigated by Ramachandran maps and the Swiss-pdb viewer server. The obtained results showed that the designed vaccine is non-allergenic, and non-toxic with high stability and immunogenicity. The remarkable stability of the final free vaccines and in complex with TLR3, TLR4, TLR5, and TLR8 was confirmed by experiments using normal mode analysis. High amounts of immunoglobulins, T-cell responses, and INF-γ secretions were strikingly visible in the immune simulation. Overall, the new multi-epitope vaccine is expected to be a suitable vaccine against influenza and SARS-CoV-2 infections.

Physicochemical and toxicological studies of some commonly used triazine-based herbicides; In-silico approach

Pesticides play a significant role in modern agriculture and public health by protecting crops, preventing the spread of diseases, and ensuring food safety. However, the use of pesticides also raises concerns due to their potential negative consequences on human health and the ecosystem. This study has concentrated on commonly used triazine-based herbicides (atraton, atrazine, prometon, secbumeton, terbuthylazine, and trietazine) due to their unfavorable side effects, which include endocrine disruption, teratogenicity, embryogenicity, carcinogenicity, and hypoplasia of the adrenal cortex. Our investigation encompasses a thorough examination of the physicochemical, spectral, biological, and toxicological properties of these triazine-based herbicides. Density functional theory (DFT) and time-dependent DFT along with the B3LYP/6-311+G (d, p) basis set were used to enumerate the geometry, chemical, and spectral properties. To evaluate the chemical reactivity of triazine compounds, the HOMO-LUMO gap is calculated. FT-IR and UV spectroscopy have been performed to identify functional groups, determine bond lengths, and investigate molecular conformations of triazine derivatives. In addition, binding affinities and modes against human estrogen-related and cancer-causing receptor proteins (PDB IDs: 4MNF and 2E2R, respectively) have been observed utilizing molecular docking and non-bonding interactions. We selected both proteins that are associated with abnormal cell growth and malignancy, particularly breast cancer and melanoma. Normal mode analysis (NMA) was performed to get the deformability and interactions of protein and amino acid residues, respectively. Pharmacokinetics and biological parameters were accomplished to anticipate their toxicological properties. Terbuthylazine and trietazine have the highest Gibbs free energies, and atrazine has the highest binding affinity for both receptor proteins. All triazine derivatives exhibit nephrotoxicity, carcinogenicity, hematotoxicity, hepatotoxicity, and CYP2C9 inhibitory properties. Therefore, the goal of our inquiry was to gain a deeper comprehension of the risks associated with exposure to triazine-based herbicides, which would be useful for the subsequent investigation. In addition, our research will raise public awareness of the negative impacts of triazine-based herbicides.

Transverse thermal instability of partially ionized radiative plasma with impact of neutral collisions and finite electron inertia effect in ISM

The impact of neutral friction, finite electron inertia and radiative heat-loss function on the thermal instability of viscous, partially-ionized plasma has been explored integrating the impacts of finite electrical resistivity and thermal conductivity. Normal mode analysis scheme is used to derive universal dispersion relation by means of the related linearized perturbation equations of the difficulty and a tailored thermal situation of instability is explored. It is finding that the thermal condition of instability is modified owing the occurrence of radiative heat-loss function, thermal conductivity, finite electron inertia and neutral particle. For transverse mode of propagation, we discover that the condition of thermal instability depends on the finite electron inertia, magnetic field strength, radiative heat-loss function, thermal conductivity, neutral particle and finite electrical resistivity, but independent viscosity of two-components. From the graphs, we explored that the temperature dependent heat-loss function, thermal conductivity, neutral collision frequency and viscosity of two-components demonstrates stabilizing effect, while finite electron inertia and finite electrical resistivity demonstrates destabilizing effect. Our results help’s to understand the process of molecular cloud formation in ISM.

Chemical reaction, Dufour and Soret effects on the stability of magnetohydrodynamic blood flow conveying magnetic nanoparticle in presence of thermal radiation: A biomedical application

Nowadays ferrofluids (magnetic nanofluids) are at the center of many researches because of their major biomedical applications such as drug delivery and cancer treatment. The effects of chemical reaction, temperature gradient induced mass transfer and concentration gradient induced heat transfer on the stability of ferrofluid flow are of great importance. This paper deals with a stability analysis of a ferrofluid composed of blood as base fluid and magnetic nanoparticles. The study integrates the effects of chemical reactions, the effects of mass transfer (Soret effect), the effects of heat transfer (Dufour effect) and the effects of the Buoyancy force. The flow is exposed to a magnetic field and thermal radiation. A system of eigenvalue equations governing the evolution of disturbances is derived by assuming a normal mode analysis. This system of equations is then solved numerically by the method of collocation. It appears from this study that the addition of nanoparticles to the blood increases its inertia, which dampens the amplitude of the disturbances and stabilizes the flow. The Casson parameter affects the stability of the flow by increasing the amplitude of the disturbances, which reflects its destabilizing effect. It appears from this study that taking into account the non-Newtonian nature of blood is very important when modeling the dynamics of the system because it shows more important and very different results than when blood is treated as a Newtonian fluid. The chemical reaction between the fluid and the nanoparticles leads to the redistribution of disturbances within the flow, which amplifies the instabilities and reflects the destabilizing character of the chemical reaction. On the other hand, temperature gradient induced mass transfer effects and concentration gradient induced heat transfer effects play an essential role on the stability of the flow because they attenuate the amplitude of the disturbances in the flow. The Darcy number exhibits a stabilizing effect on the flow. It appears from this analysis that the porosity of the medium increases the contact surface between the fluid and the nanoparticles. Buoyancy forces, thermal radiation parameter and wave number contribute to the stability of the flow. The magnetic field through the Lorentz force decreases the kinetic energy of the flow, which dissipates the disturbances and thus reflects the stabilizing character of the magnetic field. It should be noted that heat and mass transfer on magnetohydrodynamic flows through porous media taking into consideration the effect of chemical reaction appears in many natural and artificial transport processes in several branches of science and engineering applications. This phenomenon plays an important role in the chemical industry, power and cooling industry for drying, chemical vapor deposition on surfaces, cooling of nuclear reactors and petroleum industry. The effects of thermal radiation, mass and heat transfer are used in many situations in biomedical engineering and aerospace engineering.

Coarse-Grained Models for Vault Normal Model Analysis.

Recent experiments have shown that the molecular complex of vault has large conformational changes at its shoulder and cap regions in solution. From the comparison of two configuration structures, it has been found that the shoulder region can twist and move outward, while the cap region will rotate and push upward correspondingly. To further understand these experimental results, in this paper, we study the vault dynamics for the first time. Since vault has an extremely large-sized structure with around 63,336 Cα atoms, traditional normal mode method with the Cα coarse-grained representation will fall short. We employ a newly invented multiscale virtual particle-based anisotropic network model (MVP-ANM). To reduce the complexity, the 39-folder vault structure is coarse-grained to about 6000 virtual particles, which significantly reduces the computational cost while still maintaining the basic structure information. Among the 14 low frequency eigenmodes from Mode 7 to Mode 20, two eigenmodes, i.e., Mode 9 and Mode 20, are found to be directly associated with the experimental observations. In Mode 9, shoulder region undergoes a significant expansion while the cap part is lifted upward. In Mode 20, a clear rotation of both shoulder and cap regions is well observed. Our results are consistent with the experimental observations. More importantly, these low frequency eigenmodes indicate that the vault waist, shoulder and lower cap regions are the most likely regions for the opening of the vault particle. And the opening mechanism is highly likely to be rotation and expansion at these regions. As far as we know, this is the first work to provide the normal mode analysis for the vault complex.

The First Snake Venom KTS/Disintegrins-Integrin Interactions Using Bioinformatics Approaches.

Snake venom contains a number of active molecules that have been shown to possess high anti-tumor activities; disintegrins are an excellent example among these. Their ability to interact and bind with integrins suggests that they could be very valuable molecules for the development of new cancer therapeutic approaches. However, in the absence of a clear Lysine-Threonine-Serine (KTS) Disintegrins Integrin interaction model, the exact compound features behind it are still unknown. In this study, we investigated the structural characteristics of three KTS-disintegrins and the interaction mechanisms with the α1β1 integrin receptor using in silico bioinformatics approaches. Normal mode analysis showed that the flexibility of the KTSR motif and the C-terminal region play a key role and influence the KTS-Disintegrin-integrin interaction. Protein-protein docking also suggested that the interaction involving the KTSR motif is highly dependent on the residue following K21, S23 and R24. These findings contribute to a better understanding of the KTS-Disintegrin-Integrin structural differences and their interactions with α1β1 receptors, which could improve the selection process of the best active molecules for antitumor therapies.

Normal modes of Proca fields in AdS spacetime

A normal mode analysis for Proca fields in the anti-de Sitter (AdS) spacetime is given. It is found that the equations for the Proca field can be decoupled analytically. This is performed by changing the basis of the vector spherical harmonics decomposition. The normal modes and the normal mode frequencies of the Proca equation in the AdS spacetime are then analytically determined. It is also shown that the Maxwell field can be recovered by taking the massless limit of the Proca field with care so that the nonphysical gauge modes are eliminated.

Modeling of a homogeneous isotropic half space in the context of multi-phase lag coupled thermoelasticity

A two-dimensional multi-phase lag model in the context of generalized thermoelasticity is established for an isotropic half-space medium. A vector-matrix differential equation is obtained from the governing equations using normal mode analysis. The eigenvalue approach is applied to obtain the solutions. The temperature-dependent displacements, stresses, strains are calculated numerically and represented graphically to show the accuracy of the solution under mechanical and thermal loads.

Scytonemin redox status in a filamentous cyanobacterium visualized by an excitation-laser-line-scanning spontaneous Raman scattering spectral microscope

Some cyanobacteria produce a UVA-absorbing pigment, scytonemin, at extracellular sheaths. Although scytonemin-containing dark sheaths are recognizable through optical microscopes and its redox changes have been known for decades, there has been no report to obtain images of both oxidized and reduced scytonemins at subcellular resolution. Here, we show that a spontaneous Raman scattering spectral microscopy based on an excitation-laser-line-scanning method unveil 3D subcellular distributions of both the oxidized and reduced scytonemins in a filamentous cyanobacterium. The redox changes of scytonemin were supported by comparison in the Raman spectra between the cyanobacterial cells, solid-state scytonemin and quantum chemical normal mode analysis. Distributions of carotenoids, phycobilins, and the two redox forms of scytonemin were simultaneously visualized with an excitation wavelength at 1064 nm that is virtually free from the optical screening by the dark sheaths. The redox differentiation of scytonemin will advance our understanding of the redox homeostasis and secretion mechanisms of individual cyanobacteria as well as microscopic chemical environments in various microbial communities. The line-scanning Raman microscopy based on the 1064 nm excitation is thus a promising tool for exploring hitherto unreported Raman spectral features and distribution of nonfluorescent molecules embedded below nontransparent layers for visible light, while avoiding interference by autofluorescence.

New formulation of the Navier–Stokes equations for liquid flows

Abstract For isothermal liquid flows, the condition of incompressibility provides a useful simplification for describing their mechanical properties. Nevertheless, it overlooks acoustic effects, and it provides the unpleasant shortcoming of infinite propagation speed of velocity perturbations, no matter the type of constitutive equation for the shear stresses is adopted. In this paper, we provide a derivation of a new formulation of the Navier–Stokes equations for liquid flows that overcomes the above issues. The pressure looses its ancillary status of mere gauge variable (or equivalently Lagrange multiplier of the incompressibility condition) enforcing the solenoidal nature of the velocity field, and attains the proper physical meaning of hydrodynamic field variable characterized by its own spatiotemporal evolution. From the experimental evidence of sound attenuation, related to the occurrence of a non-vanishing bulk viscosity, the evolution equation for pressure in out-of-equilibrium conditions is derived without introducing any adjustable parameters. The connection between compressibility and memory effects in the propagation of internal stresses is established. Normal mode analysis and some preliminary simulations are also discussed.

Investigation of The Potential Inhibitor Effects Of Lycorine On Sars-Cov-2 Main Protease (Mpro) Using Molecular Dynamics Simulations and MMPBSA

The main protease (Mpro or 3CLpro) plays important roles in viral replication and is one of attractive targets for drug development for SARS-CoV-2. In this study, we investigated the potential inhibitory effect of lycorine molecule as a ligand on SARS-CoV-2 using computational approaches. For this purpose, we conducted molecular docking and molecular dynamics simulations MM-PB(GB)SA analyses. The findings showed that the lycorine ligand was successfully docked with catalytic dyad (Cys145 and His41) of SARS-CoV-2 Mpro with binding affinity changing between -6.71 and -7.03 kcal mol-1. MMPB(GB)SA calculations resulted according to GB (Generalized Born) approach in a Gibbs free energy changing between -24.925-+01152 kcal/mol between lycorine and SARS-CoV-2 which is promising. PB (Poisson Boltzmann) approach gave less favorable energy (-2.610±0.2611 kcal mol-1). Thus, Entropy calculations from the normal mode analysis (ΔS) were performed and it supported GB approach and conducted -23.100±6.4635 kcal mol-1. These results showed lycorine has a druggable potential but the drug effect of lycorine on COVID-19 is limited and experimental studies should be done with pharmacokinetic modifications that increase the drug effect of lycorine.