Virtual Technique Research Articles

Deep Learning with Geometry-Enhanced Molecular Representation for Augmentation of Large-Scale Docking-Based Virtual Screening.

Structure-based virtual screening has been a crucial tool in drug discovery for decades. However, as the chemical space expands, the existing structure-based virtual screening techniques based on molecular docking and scoring struggle to handle billion-entry ultralarge libraries due to the high computational cost. To address this challenge, people have resorted to machine learning techniques to enhance structure-based virtual screening for efficiently exploring the vast chemical space. In those cases, compounds are usually treated as sequential strings or two-dimensional topology graphs, limiting their ability to incorporate three-dimensional structural information for downstream tasks. We herein propose a novel deep learning protocol, GEM-Screen, which utilizes the geometry-enhanced molecular representation of the compounds docking to a specific target and is trained on docking scores of a small fraction of a library through an active learning strategy to approximate the docking outcome for yet nontraining entries. This protocol is applied to virtual screening campaigns against the AmpC and D4 targets, demonstrating that GEM-Screen enriches more than 90% of the hit scaffolds for AmpC in the top 4% of model predictions and more than 80% of the hit scaffolds for D4 in the same top-ranking size of library. GEM-Screen can be used in conjunction with traditional docking programs for docking of only the top-ranked compounds to avoid the exhaustive docking of the whole library, thus allowing for discovering top-scoring compounds from billion-entry libraries in a rapid yet accurate fashion.

MT-VTON: Multilevel Transformation-Based Virtual Try-On for Enhancing Realism of Clothing

Virtual 3D fashion fitting, commonly referred to as 2D virtual try-on, has garnered significant attention due to its potential to revolutionize the way consumers interact with fashion items online. This paper presents a novel approach to virtual try-on utilizing a deep learning framework built upon the concept of appearance flow. Our proposed method improves the existing state-of-the-art techniques by seamlessly integrating natural cloth folds, shadows, and intricate textures, such as letters and comic characters, into the synthesized virtual try-on images. Building upon the advancements of previous research, our approach introduces a multi-faceted transformation strategy that operates at both the pixel and image patch levels. Our method’s effectiveness is demonstrated through extensive experiments and comparisons with existing virtual try-on techniques. The results showcase a substantial improvement in the synthesis of virtual try-on images with natural-looking cloth folds, realistic shadows, and intricate textures.

Minimal cut of strongly connected directed random graphs studied in virtual machine deployment

Abstract This paper first presents the basic concepts of random graph theory, including undirected, directed, and generalized random graphs. A random homomorphic number mapping is introduced to solve the cut distance problem of directed random graphs, and a minimum cut distance is proposed. Next, a virtual machine deployment strategy (VMDS) based on the minimum cut algorithm is proposed to construct VM clusters based on similarity and to cut VM clusters based on the minimum cut of directed random graphs. According to the results, the MAE (1.3875) and MSE (2.7783) of both the conventional AR algorithm and ES algorithm are the lowest. Compared to the MAE (1.7381) and MSE (3.7840) of the VMDS algorithm, both significantly decrease. The research results presented in this paper are useful for applying virtual machine deployment techniques in cloud computing.

Inhibitor screening for volume-sensitive LRRC8A chloride channel

Leucine-rich repeat-containing protein 8 A (LRRC8A) protein is a critical member of volume-regulated anion channels. It plays a critical roles in the regulation of cellular volume and involves in the development of diseases like osteoarthritis. Screening of lead compounds to modulate its function may provide potential therapeutics of related diseases. Here, we employ virtual screening techniques and molecular dynamics (MD) simulation to screen potential inhibitors against LRRC8A. LRRC8A was regarded as the drug target to investigate potential compounds from the ZINC15 database via molecular docking. The final compound was selected among the top 10 Autodock Vina score (–8.8 Kcal/mol) with the ZINC ID ZINC000018195627 after druggability prediction. The docked complex from the virtual screening was subjected to MD simulation to analyze the stability of the LRRC8A protein–ligand complex, with parameters including root mean square deviation, root mean square fluctuation and radius of gyration. Molecular Mechanics/Poisson–Boltzmann Surface Area (MM/PBSA) method was further employed to predict the binding free energies from MD simulation trajectory. Our study provides insightful analysis for the potential compound to modulate LRRC8A and lay the foundation of therapeutics development against osteoarthritis. Communicated by Ramaswamy H. Sarma

Does walking/running experience shape the sagittal mental time line?

A growing body of evidence suggested that time could be separately represented either on the lateral or sagittal axis. And the lateral mental time line has an origin associated with sensorimotor experience, e.g., reading/writing. However, it is still not clear whether the sagittal mental time line also originates from sensorimotor experience, e.g., walking/running. To address this question, we examined how the movement experience affected the space–time mapping on the lateral and sagittal axes using the virtual reality technique in two experiments. The results showed that the virtual movement experience had significant effects on the space–time mapping on the lateral axis (Experiment 1), but not on the sagittal axis (Experiment 2). This finding supported that the space–time mapping on the lateral axis does originate from sensorimotor experience, while the space–time mapping on the sagittal axis more likely originates from spatial metaphors in languages or other cultural experiences.

Optimal settings for different tooth types in the virtual bracket removal technique.

To determine the optimal settings for reconstructing the buccal surfaces of different tooth types using the virtual bracket removal (VBR) technique. Ten postbonded digital dentitions (with their original prebonded dentitions) were enrolled. The VBR protocol was carried out under five settings from three commonly used computer-aided design (CAD) systems: OrthoAnalyzer (O); Meshmixer (M); and curvature (G2), tangent (G1), and flat (G0) from Geomagic Studio. The root mean squares (RMSs) between the reconstructed and prebonded dentitions were calculated for each tooth and compared with the clinically acceptable limit (CAL) of 0.10 mm. The overall prevalences of RMSs below the CAL were 66.80%, 70.08%, 62.30%, 94.83%, and 56.15% under O, M, G2, G1, and G0, respectively. For the upper dentition, the mean RMSs were significantly lower than the CAL for all tooth types under G1 and upper incisors and canines under M and G2. For the lower dentition, the mean RMSs were significantly lower than the CAL for all tooth types under G1 and lower incisors and canines under M, G2, and G0 (all P < .05). Additionally, the mean RMSs of all teeth under G1 were significantly lower than those under the other settings (all P < .001). The optimal settings varied among different tooth types. G1 performed best for most tooth types compared to the other four settings.

Detection of Various Traditional Chinese Medicinal Metabolites as Angiotensin-Converting Enzyme Inhibitors: Molecular Docking, Activity Testing, and Surface Plasmon Resonance Approaches.

Angiotensin-converting enzyme 1 (ACE1) is a peptide involved in fluid and blood pressure management. It regulates blood pressure by converting angiotensin I to angiotensin II, which has vasoconstrictive effects. Previous studies have shown that certain compounds of natural origin can inhibit the activity of angiotensin-converting enzymes and exert blood pressure-regulating effects. Surface Plasmon Resonance (SPR) biosensor technology is the industry standard method for observing biomolecule interactions. In our study, we used molecular simulation methods to investigate the docking energies of various herbal metabolites with ACE1 proteins, tested the real-time binding affinities between various herbal metabolites and sACE1 by SPR, and analyzed the relationship between real-time binding affinity and docking energy. In addition, to further explore the connection between inhibitor activity and real-time binding affinity, several herbal metabolites' in vitro inhibitory activities were tested using an ACE1 activity test kit. The molecular docking simulation technique's results and the real-time affinity tested by the SPR technique were found to be negatively correlated, and the virtual docking technique still has some drawbacks as a tool for forecasting proteins' affinities to the metabolites of Chinese herbal metabolites. There may be a positive correlation between the enzyme inhibitory activity and the real-time affinity detected by the SPR technique, and the results from the SPR technique may provide convincing evidence to prove the interaction between herbal metabolites and ACE1 target proteins.

Optimization design of all-angle negative refraction phononic crystals at a specified frequency

All-angle negative refraction (AANR) is an effective way to achieve negative refraction in phononic crystals (PnCs). It is difficult to achieve AANR using a traditional heuristic design. In this work, we propose a novel topology optimization framework for optimizing the material distribution of air/solid PnCs to achieve AANR at a specified frequency. The optimization goal is to minimize the curvature at a specific point of the equal-frequency contours (EFCs), and the Kriging-based material-field series expansion (KG-MFSE) algorithm is adopted to solve the complicated optimization problem. To ensure the connectivity of the air domain inside the unit cell, the virtual temperature technique is employed, and the filtering and threshold projection are used to control the minimum length scale of the air domain. Numerical examples show that the proposed optimization framework is effective for the material design of AANR PnCs, and several optimized design samples were fabricated with additive manufacturing. The corresponding negative refraction is verified through numerical simulation and experiment.

Design, analysis and testing of thermoplastic welded stiffened panels to investigate skin-stringer separation in post-buckling

Thermoplastic composite three-stringer panels with omega stiffeners and conduction welded joints are designed, analysed and tested until final failure to investigate the performance of the welded joint in post-buckling. The three-stringer panels are designed to be structurally representative of the fuselage demonstrator of the Clean Sky 2 project STUNNING. A simplified model of the fuselage keel section is analysed by finite element analysis, using the virtual crack closure technique to model skin-stringer separation of the welded joint. The post-buckling and skin-stringer separation behaviour of the fuselage section is then adopted as the reference for the design of the three-stringer panels. Two panels are then tested. The test setup utilises digital image correlation to measure the deformation of the panels, and a high-speed camera to capture the final failure mode. The panels failed in post-buckling due to the separation of the middle stringer, with unstable separation growth followed by separation of the outer stringers and then stringer fracture. The numerical analysis of the panels, with geometrical imperfections included, is able to predict the structural behaviour accurately, with only minor differences in buckling shape and separation behaviour.

A novel low cybersickness dynamic rotation gain enhancer based on spatial position and orientation in virtual environments

AbstractHardware and software resources nowadays make possible new Virtual Reality (VR) interaction methods. Numerous challenges have been involved over the years, and one of the most interesting is locomotion in virtual environments. In particular, Real Walking (RW) is one of the most effective Virtual Locomotion Techniques (VLT). It causes only reduced cybersickness, but it also requires proportional real walkable space to the virtual one, often requiring wide areas. In this context, optimization techniques have been proposed in the literature, e.g., reorientation or relocation. In this work, a novel method for improving reorientation in a virtual environment, exploiting a dynamic Rotation Gain Multiplication Factor (RGMF) based on the competence of the user in VR systems usage is proposed. The results highlight the effectiveness of the system and show the specific target of users that mainly appreciated it.

A distributed fault estimation method for a class of nonlinear Markov jump systems

This paper investigates the distributed fault estimation problem of a class of nonlinear Markov jump systems. The main goal is to design a distributed observer network to estimate system states and actuator fault simultaneously. For the two cases of completely known and general uncertain transition rates, we first use a virtual intermediate observer technique to remove the observer matching condition, which upgrades the flexibility in the process of design. Next, by using the information of some special neighboring nodes and adopting observability decomposition approach, a novel distributed observer network allowed to be with unobservable nodes is constructed. Then, the mentioned goal is achieved based on the observer network. The proposed method can compensate missing information of unobservable nodes, which solves the estimation problem in the case of partial information loss. Finally, an example is provided to demonstrate the effectiveness of the proposed method.

Virtual source total focusing method for crack detection in complex curved structure

Accurate non-destructive testing and evaluation of cracks is important for the quality assurance and life-cycle management of key components in aerospace and energy industries. This paper presents a novel imaging method for cracks detection in complex curved structure , combining virtual source technique, multi-mode total focusing method and phase coherence imaging method. The virtual source on the sample surface is employed as the emitter and receiver for the ultrasonic array imaging. In this way, the calculation complexity of imaging algorithm due to beam path search can be reduced, and the detection sensitivity in the region of interest can be improved. In addition, the phase coherence factor is used to suppress the background noise and imaging artifacts, which significantly improves the quality of ultrasonic array imaging. A complex curved sample with variable thickness and non-developable surface was used to examine the effectiveness of the virtual source total focusing method. The signal-to-noise ratio of the crack defect is increased by more than 25 dB using the novel method compared with that of the conventional total focusing method, and the quantitative evaluation error of defect is less than 2.67%.

Virtual data integration for a clinical decision support systems

&lt;span lang="EN-US"&gt;Clinical decision support (CDS) supplies clinicians and their patients, and relevant staff with meaningful and timely information intelligently integrated or visualized to enhance health and the health sector. Data is the backbone of decision support systems, especially (clinical) ones. Data integration (either virtual or physical manner) is a powerful technique to manipulate a vast amount of heterogeneous data and prepare it as input for the decision-making process. The difficulties in manipulating data that have a physical data integration technique motivated the decision support developers to tend to data virtualization as a data integration technique. In this paper, a clinical decision support system was developed using the virtual data integration technique. The developed system was evaluated in terms of usability and its capability of providing clinical decision support. The evaluation findings indicate that the proposed system is highly usable and has a positive impact on supporting the clinical decision-making process.&lt;/span&gt;

In-silico molecular prediction of de-novo pteridophytic ligands targeting fungal Sec-14p: A CADD based analysis

Applications of Computer-Aided Drug Design (CADD) tools in the healthcare system are a developing area of research. Implementation of in-silico, structure-based virtual screening techniques in drug discovery to identify potential agonists or inhibitors based upon the binding affinity towards corresponding target proteins is a widely used technique in drug discovery. This advanced technique is used in this study to identify potential candidates from Himalayan pteridophytes possessing antifungal potentials through inhibition of Sec14p, a phosphatidylinositol/phosphatidylcholine transfer protein from Saccharomyces cerevisiae that is complexed with Picolinamide. 3D conformations for the chemical structures of identified phytoconstituents were prepared through Chem Draw 16.0 program for prediction of activity (way2drug), mechanism (PyRx), physicochemical & pharmacokinetics (SWISS-ADME) and toxicological (PROTOX-2) probabilities through in-silico approaches for all selected 180 ligands. BIOVIA discovery studio visualizer was used to generate a 3D and 2D image of the most active 19 among the 180 identified ligands. Comparative studies proposed some highly potential effective and safe compounds from Himalayan pteridophytes that could interfere with fungal cell growth.

РОЗВИТОК ТВОРЧИХ ЗДІБНОСТЕЙ МАЙБУТНІХ УЧИТЕЛІВ ТРУДОВОГО НАВЧАННЯ ТА ТЕХНОЛОГІЙ ЧЕРЕЗ ВИКОРИСТАННЯ НЕТРАДИЦІЙНИХ МЕТОДІВ ВІЗУАЛІЗАЦІЇ В ТЕХНОЛОГІЧНІЙ ОСВІТІ

This article is devoted to the study of the impact of non-traditional visualization methods on the development of creative abilities of future teachers of labor education and technology in the context of technological education. The study examines current trends in the field of technological education and emphasizes the importance of developing the creative potential of students for the effectiveness of their future pedagogical activities. The article analyzes the theoretical aspects of creative thinking and visualization, reveals their relationship and role in the pedagogical process. The key psychological mechanisms that support the development of creative abilities and creative thinking in students are singled out. The article presents a wide range of non-traditional visualization methods that can be successfully implemented in technological education. In particular, she examines in detail the use of graphic organizers and mind maps, interactive multimedia and the latest technologies such as virtual and augmented reality. Non-traditional drawing techniques and paper-making are studied separately as creative means to stimulate creativity and imagination in students. Based on real examples of successful implementation of non-traditional visualization methods, case studies are presented that demonstrate the positive impact of such an approach on the development of creative abilities of future teachers of labor education and technology. The article also draws attention to the challenges and obstacles faced by educators when implementing non-traditional methods. It provides recommendations for successful implementation and effective overcoming of these obstacles, in particular, focusing on the need for cooperation between teachers and technical specialists, adaptation of educational programs and support of creative initiatives of students. It was determined that the use of such methods as virtual reality, augmented reality, multimedia presentations, graphic illustrations, creative projects and experimental drawing techniques makes the educational process interesting, exciting and stimulates students to actively express themselves. Keywords: creative abilities, future teachers of labor training and technologies, visualization, non-traditional methods, interactive multimedia tools, virtual reality, drawing, paper-making, technological education.

A multitier virtual screening of antagonists targeting PD-1/PD-L1 interface for the management of triple-negativebreastcancer.

Immunotherapies are promising therapeutic options for the management of triple-negative breast cancer because of its high mutation rate and genomic instability. Of note, the blockade of the immune checkpoint protein PD-1 and its ligand PD-L1 has been proven to be an efficient and potent strategy to combat triple-negative breast cancer.To date, various anti-PD-1/anti-PD-L1 antibodies have been approved. However, the intrinsic constraints of these therapeutic antibodies significantly limit their application, making small molecules a potentially significant option for PD-1/PD-L1 inhibition. In light of this, the current study aims to use a high-throughput virtual screening technique to identify potential repurposed candidates as PD-L1 inhibitors. Thus, the present study explored binding efficiency of 2509 FDA-approved compounds retrieved from the drug bank database against PD-L1 protein. The binding affinity of the compounds was determined using the glide XP docking programme. Furthermore, prime-MM/GBSA, DFT calculations, and RF score were used to precisely re-score the binding free energy of the docked complexes. In addition, the ADME and toxicity profiles for the lead compounds were also examined to address PK/PD characteristics. Altogether, the screening process identified three molecules, namely DB01238, DB06016 and DB01167 as potential therapeutics for the PD-L1 protein. To conclude, a molecular dynamic simulation of 100ns was run to characterise the stability and inhibitory action of the three lead compounds. The results from the simulation study confirm the robust structural and thermodynamic stability of DB01238 than other investigated molecules.Thus, our findings hypothesize that DB01238 could serve as potential PD-L1 inhibitor in the near future for triple-negative breast cancer patients.

Virtual chemical analysis and machine learning-based prediction of polyethylene terephthalate nanoplastics toxicity on aquatic organisms as influenced by particle size and properties

This study focuses on the chemical analysis and prediction of Polyethylene Terephthalate (PET) toxicity, considering the influence of particle size and properties. The effect PET of different sizes (1, 4, 9, 16 and 25 nm coded NP1 to NP5) on aquatic organisms such as Terpedo californica (electric ray fish) and Danio rerio (zebrafish) as model species was evaluated by virtual chemical techniques and machine learning methodology based on Multilayer Perceptrons Artificial Neural Networks (MLP ANN) and Support Vector Machine. The PET NPs was built and characterized in silico and then docked on the acetylcholinesterase (TcAChE) and cytochrome P450 (Zf CYP450) of the organisms, respectively. The results showed that the binding affinities of the NPs increased steadily from – 7.1 kcal mol-1 to – 9.9 kcal mol-1 for NP1 to NP4 and experienced a drop at NP5 (– 8.9 kcal mol-1) for TcAChE. The Zf CYP450 also had a similar pattern ranging from -5.2 kcal mol-1 to -8.1 kcal mol-1. The MLP ANN showed an accuracy of 85.9 % and 77.3 %. In comparison, SVM showed a better PET NPs toxicity prediction with an accuracy of 99.5 % and 99.4% based on the inherent properties of TcAChE and Zf CYP450, respectively.

Free Vibration and Dynamic Analysis on Free-Constrained Layer of Graphene Based on Composite Conical Shell via Jacobi–Ritz Method

Excessive vibration has always been a serious problem for conical shell structures, while the application of the graphene-based free-constrained layer (GFCL) based on carbon fiber-reinforced composite (CFRC) structure is a novel way to improve structural performance. An analytical model for vibration and dynamic characteristics of the GFCL-CFRC conical shell resting on the Winkler–Pasternak elastic foundation with arbitrary boundary conditions is constructed, and four types of GFCL porosity distribution and GFCL dispersion pattern are considered in this model. The multi-segment technique and virtual spring technique are utilized to simulate arbitrary boundary conditions. Then, the first-order shear deformation theory (FSDT) and Hamilton’s principle are employed to obtain the motion equation of the GFCL-CFRC conical shell, and the motion equation of the GFCL-CFRC conical shell is solved by the Ritz method. In conclusion, the dispersion mode of GFCL, thickness ratio of GFCL, and fiber angle have influence on the dynamic performance. With a reasonable design, the dynamic performance of the GFCL-CFRC conical shell can be further improved.

Mode I fracture toughness determination and environmental durability evaluation of adhesive bonds by wedge test

This paper presents a study of a method for determining the fracture toughness of adhesive bonds under Mode I loading using the wedge test. The slope of adhesively bonded specimen arms at loading points was used to provide an effective crack length for the wedge test specimen. A simple expression was derived based on beam theory for the Mode I energy release rate. Finite element analyses were conducted on wedge specimens with a range of material and geometrical properties. Good agreement was found between the energy release rates from the beam theory-based expression and the virtual crack closure technique (VCCT). A comparison of various energy release rate expressions showed that the present expression was more accurate than the other expressions available in the literature. The results of this study suggest that the environmental durability of adhesive bonds with composite adherends as well as metallic adherends can be assessed in terms of their fracture toughness using the present method. Experiments under hot and humid conditions were performed on wedge specimens with adherends made of carbon fiber reinforced polymer (CFRP) composite laminate and titanium alloy, and the fracture toughness results were obtained.

Cyclic elastoplasticity and XFEM based fatigue life assessment of out-of-plane gusset welded joints

Conventional design methods for high-cycle fatigue failure of engineering components often assume a linear-elastic material behaviour. The different driving forces of crack initiation and propagation fail to be considered, resulting in less accurate predictions of fatigue life. To address this issue, the present study proposes a novel method to predict the fatigue life of out-of-plane gusset welded joints based on cyclic elastoplasticity and extended finite element method (XFEM). Incorporating the welding residual stress simulated by thermal–mechanical analysis, the cyclic stress–strain response of out-of-plane gusset welded joints was assessed by Fatigue SS (FSS) constitutive model. The crack initiation life was therefore predicted by the local strain approach considering the mean stress correction. Based on the converged cyclic stress–strain response, the crack propagation behaviour and life were predicted by XFEM in combination with Virtual Crack Closure Technique (VCCT). The influence of mean stress, mixed-mode crack and residual stress on crack initiation and propagation life was also investigated. The results show that the proposed method can predict the fatigue life of out-of-plane gusset welded joints under the pure tension loading with high accuracy against experimental results.