Structure Model Research Articles

Exploring the evolutionary and pathogenic role of Acinetobacter baumannii biofilm-associated protein (Bap) through in silico structural modeling.

Acinetobacter species encode for extracellularly secreted Biofilm-associated protein (Bap), a multi-domain protein with variable molecular weights reaching several hundred kilodaltons. Bap is crucial for the development of multi-dimensional structures of mature biofilms. In our investigation, we analyzed 7338 sequences of A. baumannii from the NCBI database and found that Bap or Bap-like protein (BLP) was present in 6422 (87.52%) isolates. Further classification revealed that 12.12% carried Type-1 Bap, 68.44% had Type-2, 6.91% had Type-3, 0.05% had Type-6 or SDF-Type, and 12.51% lacked Bap or BLP. The majority of isolates with Type-1, Type-2, and Type-3 Bap belonged to ST1, ST2, and ST25, respectively. Phylogenetic analysis suggested that Type-1 Bap is the most ancient, while Type-3 and SDF-Type have evolved recently. Studying the interaction of predicted Bap structures with human CEACAM-1 and PIgR showed that Bap with its BIg13 and BIg6 domains interact with the N-terminal domain of CEACAM-1, involving Arg43 and Glu40, involved in CEACAM-1 dimerization. Also, we found that recently evolved Type-3 and SDF-Type Bap showed greater interaction with CEACAM-1 and PIgR. It can be asserted that the evolution of Bap has conferred enhanced virulence characteristics to A. baumannii with increased interaction with CEACAM-1 and PIgR. Using in silico approaches, this study explores the evolutionary, physicochemical, and structural features of A. baumannii Bap and unravels its crucial role in mediating interaction with human CEACAM-1 and PIgR through detailed structure modelling. These findings advance our understanding of A. baumannii Bap and highlight its role in pathogenesis.

High-dimensionality structure in English-language personality type-nouns.

Past applications of the lexical approach to type-noun personality structures have yielded different results compared with those generated for adjectival personality structures, since then new methods have arisen for identifying robust higher-dimensionality structure in data. This research aims to identify an optimal taxonomy of English language type-nouns. Current study reanalyzed 372 type-nouns from a previous study emphasizing robustness across methodological variations (original vs. ipsatized data, oblique vs. orthogonal rotations, convergence between male and female target ratings) to determine a replicable but more comprehensive model of personality type-noun structure. A 13-factor original-data oblimin-rotated solution was determined to be the most robust model, except for a one-factor model that was far less comprehensive and informative; an original-data 32-factor oblimin-rotated solution was also fairly robust. Although each of the Big Five adjectival markers indicated a large correlation with one or more type-noun factors; nearly half of the 13 type-noun factors lacked such large correlations with the Big Five. A high-dimensionality approach thus indicated that type-nouns capture substantial content beyond the Big Five. A comparison with the character-types described by an ancient philosopher (Theophrastus) signified that some granular type-noun dimensions may have stability across multiple millennia.

Electromagnetic Characterization of Permanent Magnet Eddy Current Structures Based on Backplane Distance Adjustment

To address the problem of problematic spray design inside mining anchor-digging equipment, a switching seal using a permanent magnet eddy current drive is initially presented here. The layer model of the permanent magnet eddy current structure is established, the subdomain analysis model is introduced, the permanent magnet eddy current structure is divided into six regions along the axial direction, and the boundary equations are established at the interfaces of each region. The vector magnetic potential equations in each region are deduced, along with the electromagnetic torque and axial force equations. The computational results are compared and analyzed with the results of finite element simulation, verifying the accuracy of the theoretical model. The design of experiments is used to verify the feasibility of the switching seal using the permanent magnet eddy current structure.

First principles modelling of the ion binding capacity of finger millet

Finger millet, a cereal grain widely consumed in India and Africa, has gained more attention in recent years due to its high dietary fibre (arabinoxylan) and trace mineral content, and its climate resilience. The aim of this study was to understand the interactions between potassium (K+), calcium (Ca2+) and zinc (Zn2+) ions and the arabinoxylan structure and determine its ion-binding capacity. Three variations of a proposed model of the arabinoxylan structure were constructed and first principles Density Functional Theory calculations were carried out to determine the cation-binding capacity of the arabinoxylan complexes. Zn2+-arabinoxylan complexes were highly unstable and thermodynamically unfavourable in all three models. Ca2+ and K+ ions, however, form thermodynamically stable complexes, particularly involving two glucuronic acid residues as a binding pocket. Glucuronic acid residues are found to play a key role in stabilising the cation-arabinoxylan complex, and steric effects are more important to the stability than charge density. Our results highlight the most important structural features of the millet fibre regarding ion-storage capacity, and provide valuable preliminary data for confirmatory experimental studies and for the planning of clinical trials where the bioavailability of bound ions following digestion may be tested.

β Cephei Pulsators in Eclipsing Binaries Observed with TESS

The combined strength of asteroseismology and empirical stellar basic parameter determinations for in-depth asteroseismic analysis of massive pulsators in eclipsing binaries shows great potential for treating the challenging and mysterious discrepancies between observations and models of stellar structure and the evolution of massive stars. This paper compiles a comprehensive list of massive pulsators in eclipsing binary systems observed with TESS. The TESS light curves and discrete Fourier transforms of a sample of 8055 stars of spectral type B0–B3 were examined for eclipses and stellar pulsations, and the ephemerides of the resulting subsample of massive pulsators in eclipsing binaries were computed. This subsample was also crossmatched with existing catalogs of massive pulsators. Until now, fewer than 30 β Cephei pulsators in eclipsing binaries have been reported in the literature. Here we announce a total of 78 pulsators of the β Cephei type in eclipsing binaries, 59 of which are new discoveries. Forty-three are recognized as definite, and 35 are candidate pulsators. Our sample of pulsating massive stars in eclipsing binaries allows for future asteroseismic modeling to better understand the internal mixing profile and to resolve the mass discrepancy in massive stars. We have already started follow-up work on some of the most interesting candidates.

The impact of radiative levitation on mode excitation of main-sequence B-type pulsators

Numerical computations of stellar oscillations for models representative of B-type stars predict fewer modes to be excited than observations reveal from modern space-based photometric data. One shortcoming of state-of-the-art evolution models of B-type stars that may cause a lack of excited modes is the absence of microscopic diffusion in most such models. We investigate whether the inclusion of microscopic diffusion in stellar models of B-type stars, notably radiative levitation experienced by isotopes, leads to extra mode driving by the opacity mechanism compared to the case of models that do not include microscopic diffusion. We consider the case of slowly to moderately rotating stars and use non-rotating equilibrium models, while we account for (uniform) rotation in the computations of the pulsation frequencies. We calculate 1D stellar structure and evolution models with and without microscopic diffusion and examine the effect of radiative levitation on mode excitation, for both low-radial order pressure and gravity modes and for high-radial order gravity modes. As is common practice in asteroseismology, rotation is included in the pulsation computations according to the mode's frequency regime. For modes having frequencies below twice the rotation frequency, that is, modes in the sub-inertial regime, we adopt the traditional approximation of rotation. For modes in the super-inertial regime with frequency above twice the rotation frequency, rotation is treated perturbatively up to first order in the rotation. We consider macroscopic envelope mixing induced by internal gravity waves to compute the modes and study its effect on the surface abundances. We find systematically more modes to be excited for the stellar models including microscopic diffusion compared to those without it, in agreement with observational findings of pulsating B-type dwarfs. Furthermore, the models with microscopic diffusion predict that excited modes occur earlier on in the evolution compared to modes without it. In order to maintain realistic surface abundances during the main sequence, we include macroscopic envelope mixing by internal gravity waves. Along with microscopic diffusion, such macroscopic envelope mixing ensures both more excited modes and surface abundances consistent with spectroscopic studies of B-type stars. While radiative levitation has so far largely been neglected in stellar evolution computations of B-type stars for computational convenience, it impacts mode excitation predictions for stellar models of such stars. We conclude that the process of radiative levitation is able to reduce the discrepancy between predicted and observed excited pulsation modes in B-type stars.

Identification of novel single nucleotide variants in the drug resistance mechanism of Mycobacterium tuberculosis isolates by whole-genome analysis

BackgroundTuberculosis (TB) represents a major global health challenge. Drug resistance in Mycobacterium tuberculosis (MTB) poses a substantial obstacle to effective TB treatment. Identifying genomic mutations in MTB isolates holds promise for unraveling the underlying mechanisms of drug resistance in this bacterium.MethodsIn this study, we investigated the roles of single nucleotide variants (SNVs) in MTB isolates resistant to four antibiotics (moxifloxacin, ofloxacin, amikacin, and capreomycin) through whole-genome analysis. We identified the drug-resistance-associated SNVs by comparing the genomes of MTB isolates with reference genomes using the MuMmer4 tool.ResultsWe observed a strikingly high proportion (94.2%) of MTB isolates resistant to ofloxacin, underscoring the current prevalence of drug resistance in MTB. An average of 3529 SNVs were detected in a single ofloxacin-resistant isolate, indicating a mutation rate of approximately 0.08% under the selective pressure of ofloxacin exposure. We identified a set of 60 SNVs associated with extensively drug-resistant tuberculosis (XDR-TB), among which 42 SNVs were non-synonymous mutations located in the coding regions of nine key genes (ctpI, desA3, mce1R, moeB1, ndhA, PE_PGRS4, PPE18, rpsA, secF). Protein structure modeling revealed that SNVs of three genes (PE_PGRS4, desA3, secF) are close to the critical catalytic active sites in the three-dimensional structure of the coding proteins.ConclusionThis comprehensive study elucidates novel resistance mechanisms in MTB against antibiotics, paving the way for future design and development of anti-tuberculosis drugs.

Investigation of Bandgap Properties of a Piezoelectric Phononic Crystal Plate Based on the PDE Module in COMSOL

Investigation of Bandgap Properties of a Piezoelectric Phononic Crystal Plate Based on the PDE Module in COMSOL

Fine Shear-Wave Velocity Structures of Subsurface beneath the Guangdong–Hong Kong–Macao Greater Bay Area with Dense Seismic Array and SPAC Method

Abstract We apply the spatial autocorrelation (SPAC) method to construct the 3D subsurface shear-wave velocity structure model using the short-period dense seismic array (containing 725 nodal geophones) located at the Guangdong–Hong Kong–Macao Greater Bay area (GBA). We first divided the dense array into numerous subarrays, with each subarray consisting of nine nodal geophones, and obtained 562 subarrays that can provide 1D VS profiles of the same quantity. Then, the SPAC method and genetic algorithm are utilized to extract the dispersion curve of the Rayleigh wave from the raw microtremor data and invert VS structure, respectively. Finally, a 3D VS structure model from the surface to 3.3 km depth is derived by combining all 1D VS structures. Relatively low-velocity anomalies above 700 m are considered unconsolidated shallow sediments as well as relatively high-velocity anomalies beneath 1100 m are attributed to consolidated granite bedrock. Meanwhile, low-velocity anomalies that are identified through the vertical VS profile at a depth of about 900–3000 m can be contributed to the fractured zone, and striped low-velocity anomalies in the horizontal VS maps reveal the location of the deeply buried faults in the study area. The results also mean that the SPAC method combined with the records of short-period dense seismic array can be effectively applied to image subsurface structures in high-populated urban area. The development of this noise-resistance and environment-friendly geophysical technique provides a reliable and effective way to explore the complicated subsurface geological structures, which is of great significance to urban engineering construction and earthquake disaster reduction work in densely populated urban agglomerations.

Cost-effective topology optimization of masonry structure reinforcements by a linear static analysis-based GA framework

AbstractThe paper presents a novel optimization framework aimed at the minimization of seismic retrofitting-related costs for existing unreinforced masonry building structures. The framework provides topology optimization of reinforcements (reinforced plasters) to implement in masonry walls for the accomplishment of seismic safety checks under the reference seismic load combinations. Optimization is carried out by a genetic algorithm (GA) developed in MATLAB®, which controls a 3D finite element equivalent frame model of the masonry structure developed in OpenSees. The GA routine iterates the reinforcement configurations employing specific genetic operators. The feasibility of each candidate retrofitting solution is assessed by performing in-plane shear and flexural safety checks of masonry walls. The framework is finally tested with a case study masonry structure supposed to be made of average-quality or poor-quality masonry. Results will show that the proposed framework can effectively provide the minimization of seismic retrofitting costs for existing masonry structures, giving as output the optimal configuration of the reinforcements within the structural layout.

The physical and evolutionary energy landscapes of devolved protein sequences corresponding to pseudogenes

Protein evolution is guided by structural, functional, and dynamical constraints ensuring organismal viability. Pseudogenes are genomic sequences identified in many eukaryotes that lack translational activity due to sequence degradation and thus over time have undergone "devolution." Previously pseudogenized genes sometimes regain their protein-coding function, suggesting they may still encode robust folding energy landscapes despite multiple mutations. We study both the physical folding landscapes of protein sequences corresponding to human pseudogenes using the Associative Memory, Water Mediated, Structure and Energy Model, and the evolutionary energy landscapes obtained using direct coupling analysis (DCA) on their parent protein families. We found that generally mutations that have occurred in pseudogene sequences have disrupted their native global network of stabilizing residue interactions, making it harder for them to fold if they were translated. In some cases, however, energetic frustration has apparently decreased when the functional constraints were removed. We analyzed this unexpected situation for Cyclophilin A, Profilin-1, and Small Ubiquitin-like Modifier 2 Protein. Our analysis reveals that when such mutations in the pseudogene ultimately stabilize folding, at the same time, they likely alter the pseudogenes' former biological activity, as estimated by DCA. We localize most of these stabilizing mutations generally to normally frustrated regions required for binding to other partners.

Analyzing polycyclic aromatic hydrocarbons using topological indices and QSPR analysis to reveal molecular complexity

Polycyclic aromatic hydrocarbons (PAHs) have distinctive chemical structures and are well known for their wide range of uses and environmental relevance. This work explores the impact of these structural characteristics on eccentricity-based topological indices offering information about the arrangement of atoms within the molecules. This study uses quantitative structure-property relationship (QSPR) analysis to construct prediction models for understanding and forecasting specific PAHs including Dibenzo[e,l]Pyrene, Heptacence, Heptaphene, Naphthacene, Naphthalene, Naphto[1,2a]pyrene, Naphtho[2,3a]pyrene, perylene, Perylene, Picene, Phenanthrene, Pyrene, Tetraphene, Tribenzo[b,n,pqr]perylene, Tribenzo[a,fg,op]tetracene and Triphenylene. Furthermore, regression analysis applies to clarify the quantitative correlations between the factors under study and improves the interpretability of the data produced. The combined use of these diverse approaches advances a thorough comprehension of the mutual influence of chemical structure, topological indices and predictive modeling about PAHs.

The 6-kilodalton peptide 1 in plant viruses of the family Potyviridae is a viroporin

Potyviridae, the largest family of plant RNA viruses, includes many important pathogens that significantly reduce the yields of many crops worldwide. In this study, we report that the 6-kilodalton peptide 1 (6K1), one of the least characterized potyviral proteins, is an endoplasmic reticulum-localized protein. AI-assisted structure modeling and biochemical assays suggest that 6K1 forms pentamers with a central hydrophobic tunnel, can increase the cell membrane permeability of Escherichia coli and Nicotiana benthamiana, and can conduct potassium in Saccharomyces cerevisiae. An infectivity assay showed that viral proliferation is inhibited by mutations that affect 6K1 multimerization. Moreover, the 6K1 or its homologous 7K proteins from other viruses of the Potyviridae family also have the ability to increase cell membrane permeability and transmembrane potassium conductance. Taken together, these data reveal that 6K1 and its homologous 7K proteins function as viroporins in viral infected cells.

A Survey of Deep Learning Methods for Estimating the Accuracy of Protein Quaternary Structure Models

The quality prediction of quaternary structure models of a protein complex, in the absence of its true structure, is known as the Estimation of Model Accuracy (EMA). EMA is useful for ranking predicted protein complex structures and using them appropriately in biomedical research, such as protein–protein interaction studies, protein design, and drug discovery. With the advent of more accurate protein complex (multimer) prediction tools, such as AlphaFold2-Multimer and ESMFold, the estimation of the accuracy of protein complex structures has attracted increasing attention. Many deep learning methods have been developed to tackle this problem; however, there is a noticeable absence of a comprehensive overview of these methods to facilitate future development. Addressing this gap, we present a review of deep learning EMA methods for protein complex structures developed in the past several years, analyzing their methodologies, data and feature construction. We also provide a prospective summary of some potential new developments for further improving the accuracy of the EMA methods.

SimRNAweb v2.0: a web server for RNA folding simulations and 3D structure modeling, with optional restraints and enhanced analysis of folding trajectories.

Research on ribonucleic acid (RNA) structures and functions benefits from easy-to-use tools for computational prediction and analyses of RNA three-dimensional (3D) structure. The SimRNAweb server version 2.0 offers an enhanced, user-friendly platform for RNA 3D structure prediction and analysis of RNA folding trajectories based on the SimRNA method. SimRNA employs a coarse-grained model, Monte Carlo sampling and statistical potentials to explore RNA conformational space, optionally guided by spatial restraints. Recognized for its accuracy in RNA 3D structure prediction in RNA-Puzzles and CASP competitions, SimRNA is particularly useful for incorporating restraints based on experimental data. The new server version introduces performance optimizations and extends user control over simulations and the processing of results. It allows the application of various hard and soft restraints, accommodating alternative structures involving canonical and noncanonical base pairs and unpaired residues, while also integrating data from chemical probing methods. Enhanced features include an improved analysis of folding trajectories, offering advanced clustering options and multiple analyses of the generated trajectories. These updates provide comprehensive tools for detailed RNA structure analysis. SimRNAweb v2.0 significantly broadens the scope of RNA modeling, emphasizing flexibility and user-defined parameter control. The web server is available at https://genesilico.pl/SimRNAweb.

Research on disease diagnosis based on teacher-student network and Raman spectroscopy.

Diabetic nephropathy is a serious complication of diabetes, and primary Sjögren's syndrome is a disease that poses a major threat to women's health. Therefore, studying these two diseases is of practical significance. In the field of spectral analysis, although common Raman spectral feature selection models can effectively extract features, they have the problem of changing the characteristics of the original data. The teacher-student network combined with Raman spectroscopy can perform feature selection while retaining the original features, and transfer the performance of the complex deep neural network structure to another lightweight network structure model. This study selects five flow learning models as the teacher network, builds a neural network as the student network, uses multi-layer perceptron for classification, and selects the optimal features based on the evaluation indicators accuracy, precision, recall, and F1-score. After five-fold cross-validation, the research results show that in the diagnosis of diabetic nephropathy, the optimal accuracy rate can reach 98.3%, which is 14.02% higher than the existing research; in the diagnosis of primary Sjögren's syndrome, the optimal accuracy rate can be reached 100%, which is 10.48% higher than the existing research. This study proved the feasibility of Raman spectroscopy combined with teacher-student network in the field of disease diagnosis by producing good experimental results in the diagnosis of diabetic nephropathy and primary Sjögren's syndrome.

OPTIMIZATION OF THE PEROVSKITE SOLAR CELL STRUCTURE

An experimental perovskite solar cell (PSC) with the structure Au/Spiro-MeOTAD/CH3NH3PbI3/PEDOT:PSS/ITO was fabricated. The measurements of main photovoltaic characteristics were provided. The current-voltage dependences (I-V curves) were measured conducted in the voltage range from -1V to 1V. During the measurements, the corresponding values were calculated of the short-circuit current density(Jsc) and open-circuit voltage(Uoc) were obtained as 1.23 mA/cm² and 0.19 V, respectively. Subsequently, an analytical model corresponding to this structure was formulated. For modeling the parameters of the perovskite solar cell, the Comsol Multiphysics environment was used, this environment is based on the finite element method. The relevant computations were provided to obtain the corresponding values of the short-circuit current density and open-circuit voltage as 3.29 mA/cm² and 0.2 V, respectively, with the maximum theoretically calculated power of this structure being 0.11 W. The experimental outcomes were juxtaposed with the predictions of the analytical computations, and the modeling results were empirically validated. An analytically accomplished model of the same structure was built by adding an electron transport layer (ETL). An organic material BCP (Bathocuproine) was used as an supplementary ETL layer. During the optimization of the PSC, the main datums were mathematically counted. Such values as the short-circuit current density of 10.17 mA/cm², open-circuit voltage of 1.2 V, and the maximum power value of Au/BCP/Spiro-MeOTAD/CH3NH3PbI3/PEDOT:PSS/ITO structure, which is 3.21 W were rated. A comparison of the volt-ampere characteristics of perovskite cells in dark and light modes was conducted for primary and optimized structures. The main parameters, obtained during the modeling of the experimental sample and subsequent model optimization, were compared. Specifically one of the key parameters of solar cell heterostructures the fill factor was evaluated and found to have increased from 16.52% to 25.00%, respectively. The light-sensitive behavior of the perovskite cell were visibly enhanced.

Using interpretative structure model and analytical network process for optimum site selection of airport locations in Delta Egypt

Abstract Airports are among the constructions that must meet international standards and specifications established by the International Civil Aviation Organization (ICAO). Some of these parameters and criteria include topography, environmental, and operating circumstances. Navigation operations are also affected by terrain and human barriers, while noise, infrastructure, and weather factors affect the environment around airports. This article investigates using the interpretative structure model (ISM) and analytical network process (ANP) together as a new technique to select and determine the optimum site selection for constructing new international airports in the Nile Delta, Egypt. The criteria used (16 international criteria) are selected depending on the standards of the ICAO, field surveys, and previous studies. Nile Delta, Egypt, is chosen as a case study because it suffers from the lack of international airports and has a population of approximately 23 million. Therefore, new international airports must be established to serve this region, boost tourism, improve transportation, and stimulate commercial traffic. The results using the suggested new technique are compared with the traditional used methods for site selection, such as fuzzy-analytic hierarchy process. Landsat 8 images are used in this research. A quality test using the area under the curve and the receiver operating characteristic curve was applied to evaluate the new technique for site selection of international airports, depending on calculating the highest suitability index for each proposed site. From the quality tests, it is deduced that the suggested method (ISM–ANP) for airport site selection is more accurate than any other traditional method. ArcGIS 10.5 software is used to draw the final digital maps containing the proposed resulted sites. As a result, three new locations for the construction of international airports were found and selected throughout the research region (Delta Nile, Egypt) based on the used mathematical models. Therefore, the proposed novel method for determining the locations of international airports is thought to be effective and feasible, and it can be used to determine the locations of any development projects in general, particularly in developing countries, which benefits the decision-makers in making the right decisions.

Evaluation of adults' acumen exerted from cerebral stress with quantified anthropometric indices using bioelectrical impedance analysis

This work considers cerebral stress-struck adults to assess their ‘acumen’ with four quantified anthropometric indices like cell membrane capacitance (CM), total body impedance (TBI), total body fat (TBF), and total body water (TBW). Primarily, a bio-impedance model of the epithelial tissue structure of human body has been presented and anatomized considering mental stress driven hormonal changes happen inside human body to propose several preambles. Secondly, an intelligence quotient (IQ) test designed to create ‘racing’ thoughts has been conducted right before measuring indices using bioelectrical impedance spectroscopy (BIS) method. Finally, juxtaposed investigations to vindicate the correlation between bio-impedance model-implied preambles and the variance of the four quantified indices were made by comparing them to the IQ test outcomes. This article reports, an effectively innervated nervous system having homeostasis endocrine human anatomy with CM, TBI, TBF, and TBW, in the range of 1.0–2.1 nF, 470–550 Ω, 7.9–20%, and 56.8–80%, respectively for the subjects whose acumen is classified as “Class-A", while “Class-B" subjects are also presented with other distinct quantified indices. The outcomes of this work are expected to be a paradigm in the digital judgment of adults' psychological engagement to any tasks.

METHOD FOR CALCULATING THE BEARING CAPACITY OF A SCREW PILE WITH A SPIRAL BLADE BY THE SOIL

Purpose. The purpose of the scientific article is to study and substantiate the principle methodology for calculating the bearing capacity of a screw pile with a spiral blade on the basis of field tests of a prototype pile using existing methods of theoretical calculation of similar piles. Determination of the bearing capacity of a pile with a spiral blade by the soil according to the first limit state. Also, the goal is to determine certain regularities in the modeling of pile structure. Methodology. A metal elements pile is used as a test sample. Determination of the theoretical bearing capacity of the pile in the vertical direction is conducted using formulas and calculation data from Appendix H.5 (DBN B.2.1-10-2009, 2011). The basic solution is that the load-bearing capacity of the pile is achieved due to the adhesion of each individual blade to the soil, which in total reflects the final value of the load-bearing capacity of the pile. Findings. Six experimental piles were installed and tested with static axial compressive and pullout loads. The estimated compressive, pullout and horizontal loads allowed for test piles, turned in to the design mark and tested without soaking subsoils, were determined. In this work, on the basis of experiments, the possibility of using the calculation data existing in the regulatory documentation as a justified theoretical calculation of pile-based foundations in the design of buildings and structures in general with the use of piles with a spiral blade is proven. Originality. A refined mathematical dependence for determining the bearing capacity of a screw pile with a spiral blade by the soil is proposed and the possibility of its use is confirmed experimentally. Practical value. The proposed method makes it possible to substantiate and use screw piles with a spiral blade for pile foundations.