Interaction Potential Energy Research Articles

Prospecting native and analogous peptides with anti-SARS-CoV-2 potential derived from the trypsin inhibitor purified from tamarind seeds

The study aimed to prospect in silico native and analogous peptides with anti-SARS-CoV-2 potential derived from the trypsin inhibitor purified from tamarind seeds (TTIp). From the most stable theoretical model of TTIp (TTIp 56/287), in silico cleavage was performed for the theoretical identification of native peptides and generation of analogous peptides. The anti-SARS-CoV-2 potential was investigated through molecular dynamics (MD) simulation between the peptides and binding sites of transmembrane serine protease 2 (TMPRSS2), responsible for the entry of SARS-CoV-2 into the host cell. Five native and analogous peptides were obtained and validated through chemical and physical parameters. The best interaction potential energy (IPE) occurred between TMPRSS2 and one of the native peptides obtained by cleavage with trypsin and its analogous peptide. Thus, both peptides showed many hydrophobic residues, a common physical–chemical property among the peptides that inhibit the entry of enveloped viruses, such as SARS-CoV-2, present in specific drugs to treat COVID-19.

Total longitudinal potential energy of interaction between parallel charged rods of finite size

We present a formula for the total potential energy of interaction between two parallel charged prismatic rods of finite size as a function of longitudinal inter-rod displacement (TLPE), obtained by calculating the repulsive electrostatic potential energy (using the nonlinear Poisson-Boltzmann equation) and the attractive van der Waals (VDW) potential energy between the rods in skewed configurations. The full profile of the TLPE curves is like an inverted bell, whose (top) width is twice the rod length, and depth is the same as that of the secondary minimum of the Derjaguin-Landau-Verwey-Overbeek (DLVO) potential for the rods.Using the TLPE function, we estimated root mean square of longitudinal displacements of fluctuating rods of 250 × 50 × 50 nm3 and a scaled surface potential of 5 for lateral inter-rod separations, d = 20 and 25 nm, e.g., in 5-rod systems, which showed non-negligible values of 24–87 nm.

Quantum and Semiclassical Dynamics of Nonadiabatic Electronic Excitation of C(3P) to C1D) by Hyperthermal Collisions with N2.

The dynamics and kinetics of nonadiabatic excitation of C(3P) to C(1D) induced by hyperthermal collisions with N2 molecules are investigated using a quantum mechanical and two semiclassical nonadiabatic methods. The full-dimensional interaction potential energy surfaces and spin-orbit coupling, which facilitates the spin-forbidden process, are represented by a recently constructed diabatic potential energy matrix. The multistate quantum dynamics for selected partial waves found small transition probabilities due to the weak spin-orbit coupling. The spin-flip transition is the most favored near the threshold due to effective curve crossing. Strong oscillations are also found in the probabilities, which are attributable to resonances supported by the deep well in the singlet-state potential. Vibrational state-specified rate coefficients are reported from J-shifted quantum dynamics calculations, and they follow the Arrhenius form. Vibrational excitation in the N2 collision partner is found to increase the excitation rate at low temperatures, but the trend is reversed at high temperatures. The two semiclassical methods qualitatively reproduce the quantum rate coefficients.

Micro-mechanical insights into the stress transmission in strongly aggregating colloidal gel.

Predicting the mechanical response of soft gel materials under external deformation is of paramount importance in many areas, such as foods, pharmaceuticals, solid-liquid separations, cosmetics, aerogels, and drug delivery. Most of the understanding of the elasticity of gel materials is based on the concept of fractal scaling with very few microscopic insights. Previous experimental observations strongly suggest that the gel material loses the fractal correlations upon deformation and the range of packing fraction up to which the fractal scaling can be applied is very limited. In addition, correctly implementing the fractal modeling requires identifying the elastic backbone, which is a formidable task. So far, there is no clear understanding of the gel's elasticity at high packing fractions or the correct length scale that governs its mechanical response. In this work, we undertake extensive numerical simulations to elucidate the different aspects of stress transmission in gel materials. We observe the existence of two percolating networks of compressive and tensile normal forces close to the gel point. We also find that the probability distribution for the compressive and tensile parts normalized by their respective mean shows a universal behavior irrespective of various values of interaction potential and thermal energy and different particle size distributions. Interestingly, there are also a large number of contacts with zero normal force, and, consequently, a peak in the normal force distribution is observed at fn ≈ 0 even at higher pressures. We also identify the critical internal state parameters, such as the mean normal force, force anisotropies, and the average coordination number, and propose simple constitutive relations that relate different components of stress to internal state parameters. The agreement between our model prediction and the simulation observation is excellent. It is shown that the anisotropy in the force networks gives rise to the normal stress difference in soft gel materials. Our results strongly demonstrate that the mechanical response of the gel system is governed mainly by the particle length scale phenomena, with a complex interplay between the compressive and tensile forces at the particle contact.

N-glycosylation reinforces interaction of immune checkpoint TIM-3 with a small molecule ligand

N-glycosylation of eukaryotic proteins plays roles in protein folding, trafficking, and signal transduction. The biological influence of the process is well understood, whereas the pharmacological impact of protein N-glycosylation is not well under discerned. The role of N-glycosylation on drug binding to protein has been rarely studied. We have modeled the influence of a bi-antennary N-glycan introduced at position N78 on the immune checkpoint TIM-3 (T cell immunoglobulin domain and mucin domain-containing molecule 3) on the interaction with a selective drug antagonist. The bulky N-glycan introduced at the consensus sequence Asn-Val-Thr has no influence on drug binding when the glycan adopts an extended conformation. But in a folded conformation, the glycan can interact directly with the triazoloquinazolinone derivative so as to further stabilize the drug-TIM-3 complex. The non-fucosylated glycan at position N78 markedly consolidates the drug interaction, via an additional H-bond interaction with the α3-mannose residue. It provides a gain of empirical potential energy of interaction (ΔE) of about 30 %. The presence of a more rigid fucosylated N-glycan is a little less favorable, with a gain of ΔE of about 20 %. The folded N-glycan appears to protect the ligand bound to the protein cavity, with the tricyclic core of the heterocyclic molecule sandwiched between two indole rings of tryptophan residues. Similar results were obtained when using a biantennary disialyl N-glycan with a bisecting GlcNAc residue and a tetra-antennary N-glycan. The molecular models illustrate the drug-stabilizing capacity of a bulky N-glycan positioned at a validated glycosylation site (N78 corresponding to N100 for the full-length protein). The modeling approach is useful to delineate further the role of the N-glycan of the immune checkpoint TIM-3 in interaction with small molecule ligands, and to guide the design of more potent compounds. The approach is transposable to other proteins to better comprehend the influence of N-glycans on drug-receptor interactions.

Modeling of the Potential Energy of Interaction of Two Atoms by Solving a System of Nonlinear Equations

Modeling of the Potential Energy of Interaction of Two Atoms by Solving a System of Nonlinear Equations

Metallic water: Transient state under ultrafast electronic excitation.

The modern means of controlled irradiation by femtosecond lasers or swift heavy ion beams can transiently produce such energy densities in samples that reach collective electronic excitation levels of the warm dense matter state, where the potential energy of interaction of the particles is comparable to their kinetic energies (temperatures of a few eV). Such massive electronic excitation severely alters the interatomic potentials, producing unusual nonequilibrium states of matter and different chemistry. We employ density functional theory and tight binding molecular dynamics formalisms to study the response of bulk water to ultrafast excitation of its electrons. After a certain threshold electronic temperature, the water becomes electronically conducting via the collapse of its bandgap. At high doses, it is accompanied by nonthermal acceleration of ions to a temperature of a few thousand Kelvins within sub-100fs timescales. We identify the interplay of this nonthermal mechanism with the electron-ion coupling, enhancing the electron-to-ions energy transfer. Various chemically active fragments are formed from the disintegrating water molecules, depending on the deposited dose.

Modeling of the Potential Energy of Interaction of Two Atoms by Solving a System of Nonlinear Equations

Modeling of the Potential Energy of Interaction of Two Atoms by Solving a System of Nonlinear Equations

Multiphysics Modeling of Low-Intensity Pulsed Ultrasound Induced Chemotherapeutic Drug Release from the Surface of Gold Nanoparticles.

Currently, no numerical model for low-intensity pulsed ultrasound (LIPUS)-triggered anticancer drug release from gold nanoparticle (GNP) drug carriers exists in the literature. In this work, LIPUS-induced doxorubicin (DOX) release from GNPs was achieved in an ex vivo tissue model. Transmission electronic microscopy (TEM) imaging was performed before and after LIPUS exposure, and significant aggregation of the GNPs was observed upon DOX release. Subsequently, GNP surface potential was determined before and after LIPUS-induced DOX release, using a Zetasizer. A numerical model was then created to predict GNP aggregation, and the subsequent DOX release, via combining a thermal field simulation by solving the bioheat transfer equation (in COMSOL) and the Derjaguin, Landau, Verwey, and Overbeek (DLVO) total interaction potential (in MATLAB). The DLVO model was applied to the colloidal DOX-loaded GNPs by summing the attractive van der Waals and electrostatic repulsion interaction potentials for any given GNP pair. DLVO total interaction potential was found before and after LIPUS exposure, and an energy barrier for aggregation was determined. The DLVO interaction potential peak amplitude was found to drop from 1.36 kBT to 0.24 kBT after LIPUS exposure, translating to an 82.4% decrease in peak amplitude value. It was concluded that the interaction potential energy threshold for GNP aggregation (and, as a result, DOX release) was equal to 0.24 kBT.

Cold dense quark matter for the Alcubierre drive model

The Alcubierre warp drive is a controversial theory by Miguel Alcubierre. Some arguments claim that it may not be physically possible. However, based on previous studies, this work suggests an extremely dense quark matter with a low-temperature limit of up to zero that can satisfy the requirements of the Alcubierre warp drive model considering the color interaction potential energy. The energy-momentum tensor and velocity of the warp drive model supported by the quark matter are also described.

Предельная толщина стенок пор, формирующихся в процессах анодного травления сильнолегированных полупроводников

With a decrease in the thickness of the walls separating the space of pores in porous semiconductors, the potential energy of interaction between an electron and a donor (or a hole and an acceptor) can become greater than the kinetic energy of a free charge carrier. As a consequence, such interlayers lose their conductivity and transit into the dielectric state (Mott phase transition). With regard to the conditions of electrochemical pore formation, this means that as the pore channels approach each other during anodic etching to a distance at which the current flow through the wall that separates them stops, the potential of its surface ceases to be determined by the external electric bias and the electrochemical process, that leads to a further decrease in the thickness of such a wall, stops. Expressions are obtained for the limiting thickness of the walls of pores formed in degenerate semiconductors of n- and p-type conductivity. In contrast to the well-known model that relates the loss of conductivity by pore walls to the combination of space charge layers, the proposed model allows a consistent explanation for the experimental data for both n- and p-type silicon with doping levels above 10^18 cm^-3.

Limiting thickness of pore walls formed in processes of anode etching of heavily doped semiconductors

With a decrease in the thickness of the walls separating the space of pores in porous semiconductors, the potential energy of interaction between an electron and a donor (or a hole and an acceptor) can become greater than the kinetic energy of a free charge carrier. As a consequence, such interlayers lose their conductivity and transit into the dielectric state (Mott phase transition). With regard to the conditions of electrochemical pore formation, this means that as the pore channels approach each other during anodic etching to a distance at which the current flow through the wall that separates them stops, the potential of its surface ceases to be determined by the external electric bias and the electrochemical process, that leads to a further decrease in the thickness of such a wall, stops. Expressions are obtained for the limiting thickness of the walls of pores formed in degenerate semiconductors of n- and p-type conductivity. In contrast to the well-known model that relates the loss of conductivity by pore walls to the combination of space charge layers, the proposed model allows a consistent explanation for the experimental data for both n- and p-type silicon with doping levels above 1018 cm-3. Keywords: thickness limitation, pore formation, silicon, donor, acceptor.

Cold collisions of hot molecules.

In this Perspective, we review our recent work on rotationally inelastic collisions of highly vibrationally excited NO molecules prepared in single rotational and parity levels at v = 10 using stimulated emission pumping (SEP). This state preparation is employed in a recently developed crossed molecular beam apparatus where two nearly copropagating molecular beams achieve an intersection angle of 4° at the interaction region. This near-copropagating beam geometry of the molecular beams permits very wide tuning of the collision energy, from far above room temperature down to 2 K where we test the theoretical treatment of the attractive part of the potentials and the difference potential for the first time. We have obtained differential cross sections for state-to-state collisions of NO (v = 10) with Ar and Ne in both spin-orbit manifolds using velocity map imaging. Overall good agreement of the experimental results was seen with quantum mechanical close-coupling calculations done on both coupled-cluster and multi-reference configuration interaction potential energy surfaces. Probing cold collisions of NO carrying ∼2 eV of vibrational excitation allows us to test state-of-the-art theory in this extreme nonequilibrium regime.

Brownian dynamics simulation of electrical properties of KcsA potassium ion channel

As one of the regulators of cationic concentration in cells, potassium channels play an important role in the depolarization and repolarization of nerve cell. KcsA (K<sup>+</sup> conduction and selectivity architecture) channel is simple and has the commonness of potassium ion channel, which is often used as a template for potassium channel research. In this paper, Brownian dynamics (BD) method is used to simulate the electrical characteristics of the actual KcsA potassium channel systematically. The potential mean force (PMF) of ions in the channel under electrostatic field, the current-voltage characteristic curve of symmetric solution and asymmetric solution, the ion concentration distribution curve in the axial direction of the channel, and the conduction-concentration curve are obtained. The results show that the selectivity filter region of KcsA potassium channel blocks the passage of Cl<sup>–</sup> basically, showing a special selection characteristic of the passage of K<sup>+</sup>, that its current-voltage curve presents a basically linear distribution, and that the conductivity-concentration curve presents a trend of first increasing and then flattening. The basic characteristic is consistent with the experimental phenomenon. In addition, the influence of the THz field on the channel K<sup>+</sup> current is also simulated and analyzed. Compared with applying only the same amplitude electrostatic field, the selected terahertz field of 0.6 THz, 1.2 THz, and 5 THz can reduce the PMF by affecting the interaction potential energy between ion pairs, thereby increasing the K<sup>+</sup> current. The research in this paper not only deepens the understanding of the regularity of KcsA potassium ion channels, but also provides a new idea for studying other types of ion channels and the influence of terahertz field on the characteristics of ion channels.

Skyrmion–skyrmion interaction induced by itinerant electrons in a ferromagnetic strip

Magnetic skyrmions are promising spin textures for building next-generation magnetic memories and spintronic devices. Nevertheless, one of the major challenges in realizing skyrmion-based devices is the stabilization of ordered arrays of these spin textures in different geometries. Here we numerically study the skyrmion–skyrmion interaction potential that arises due to the dynamics of itinerant electrons coupled to the magnetic texture in a ferromagnetic background with racetrack geometry. We consider different topological textures (ferromagnetic (FM) and antiferromagnetic (AFM)), namely: skyrmions, antiskyrmions and biskyrmions. We show that at low electron filling, for sufficiently short separation, the skyrmions strongly couple each other yielding a bound-state bound by electronic dynamics. However, when the filling is increased, the interaction potential energy presents local minima at specific values of the skyrmion–skyrmion distance. Each of these local minima corresponds to energetically stable positions of skyrmions which are ‘protected’ by well-defined energy barriers. By inspecting the local charge density, we find that in the case of AFM skyrmions, the local antiferromagnetic nature prevents electronic penetration into the core, allowing the AFM skyrmions to be seen as infinite potential barriers for electrons.

Magnetic-field-induced Wigner crystallization of charged interlayer excitons in van der Waals heterostructures

Ever since its inception, coherent excited states of semiconductors have been the focus of semiconductor materials research to evolve into a vibrant field of low-dimensional solid-state physics. The field is gaining new momentum these days due to emerging transdimensional semiconductors such as van der Waals bound layers of transition metal dichalcogenides (TMDs) of controlled thickness. Here, we develop the theory of magnetic-field-induced Wigner crystallization for charged interlayer excitons (CIE) discovered recently in TMD heterobilayers. We derive the ratio of the potential interaction energy to the kinetic energy for the many-particle CIE system in the perpendicular magnetostatic field of an arbitrary strength and predict the crystallization effect in the strong field regime. We show that magnetic-field-induced Wigner crystallization and melting of CIEs can be observed in magneto-photoluminescence experiments with TMD bilayers of systematically varied electron-hole doping concentrations. Our results advance the capabilities of this new generation of transdimensional quantum materials.

Learning physics-consistent particle interactions.

Interacting particle systems play a key role in science and engineering. Access to the governing particle interaction law is fundamental for a complete understanding of such systems. However, the inherent system complexity keeps the particle interaction hidden in many cases. Machine learning methods have the potential to learn the behavior of interacting particle systems by combining experiments with data analysis methods. However, most existing algorithms focus on learning the kinetics at the particle level. Learning pairwise interaction, e.g., pairwise force or pairwise potential energy, remains an open challenge. Here, we propose an algorithm that adapts the Graph Networks framework, which contains an edge part to learn the pairwise interaction and a node part to model the dynamics at particle level. Different from existing approaches that use neural networks in both parts, we design a deterministic operator in the node part that allows to precisely infer the pairwise interactions that are consistent with underlying physical laws by only being trained to predict the particle acceleration. We test the proposed methodology on multiple datasets and demonstrate that it achieves superior performance in inferring correctly the pairwise interactions while also being consistent with the underlying physics on all the datasets. While the previously proposed approaches are able to be applied as simulators, they fail to infer physically consistent particle interactions that satisfy Newton's laws. Moreover, the proposed physics-induced graph network for particle interaction also outperforms the other baseline models in terms of generalization ability to larger systems and robustness to significant levels of noise. The developed methodology can support a better understanding and discovery of the underlying particle interaction laws, and hence, guide the design of materials with targeted properties.

Prospecting in silico antibacterial activity of a peptide from trypsin inhibitor isolated from tamarind seed

Bacterial infections have become a global concern, stimulating the growing demand for natural and biologically safe therapeutic agents with antibacterial action. This study was evaluated the genotoxicity of the trypsin inhibitor isolated from tamarind seeds (TTI) and the antibacterial effect of TTI theoric model, number 56, and conformation number 287 (TTIp 56/287) and derived peptides in silico. TTI (0.3 and 0.6 mg.mL−1) did not cause genotoxicity in cells (p > 0.05). In silico, a greater interaction of TTIp 56/287 with the Gram-positive membrane (GP) was observed, with an interaction potential energy (IPE) of −1094.97 kcal.mol−1. In the TTIp 56/287-GP interaction, the Arginine, Threonine (Thr), and Lysine residues presented lower IPE. In molecular dynamics (MD), Peptidotrychyme59 (TVSQTPIDIPIGLPVR) showed an IPE of −518.08 kcal.mol−1 with the membrane of GP bacteria, and the Thr and Arginine residues showed the greater IPE. The results highlight new perspectives on TTI and its derived peptides antibacterial activity.

Interaction of deformable solid and hollow particles with rough surface morphology in colloidal systems

Hypothesis and backgroundA majority of natural particles have deformable and rough surfaces. Past research indicated a lack of information for a numerical model to simulate the potential non-contact interaction between two deformable particles with uneven surfaces. The simulation of deformable particles is critical to better understanding the interaction of deformable particles in colloidal systems. We hypothesized that numerical models could simulate the deformation process of solid and hollow particles, and the constructed models could predict the impact of deformation on the interaction of rough-surfaced solid or hollow deformable particles. Numerical modelingThis work modeled the deformable solid and hollow particles with rough surface morphologies following a fractal geometry theory. Their non-contact interaction was simulated following the three-stages deformation model. Also, the impacts of surface tension, particle size, and surface roughness on the interaction of the particles were investigated. FindingsIt was observed that the total potential energy of deformable solid and hollow particles followed a similar pattern under different conditions. The difference in the energy profile between solid and hollow particles is that the hollow particles generate a deeper primary minimum, and the energy barrier disappears, indicating that the hollow particles have better attachment affinity. The results show that the increased particle size will strengthen the deformability of deformable solid and hollow particles and their potential interaction, and particle size will be the most influential parameter in affecting the deformability of particles. When the particle size increased from 10 nm to 1000 nm, the deformation region of solid particles was enlarged from 5 nm to 90 nm. Nevertheless, increased surface tension would weaken the deformability of deformable solid and hollow particles, which would significantly reduce particle aggregation. The increase in the fractal dimension would reduce solid and hollow particles' deformability but increase the potential interaction energy. The controversial results could be found by increasing fractal roughness, which would improve the deformability of particles and reduce the interaction energy. The results of this study could be applied for foreseeing the deformation and interaction of deformable particles with potential applications in suspension systems, such as biological cell suspensions.

Electrostatic layer-by-layer deposition of diamond nanoparticles onto substrate surfaces

Diamond nanoparticles (DNPs) are expected as splendid coating materials to give, e.g. corrosion resistance, anti-bacterial properties, and antireflection function. In this paper, we demonstrate a technique of electrostatic layer-by-layer deposition of DNPs onto substrate surfaces using DNP colloidal suspensions with different signs of zeta potentials alternately. The formed DNP layers are investigated in terms of film thickness, surface roughness, and homogeneity. Plus, those morphologies of DNP layers are theoretically correlated with the colloidal properties of DNP suspensions based on the electrostatic interaction potential energy between colloidal DNPs and substrate surfaces. Consequently, it turns out that the demonstrated technique enables formation of DNP thin layers with desired thickness, particle density, and surface roughness on substrate surfaces by controlling the ionic strength of colloidal DNPs.