Computer-aided Design Methodology Research Articles

Repurposing FDA-Approved Agents to Develop a Prototype Helicobacter pylori Shikimate Kinase (HPSK) Inhibitor: A Computational Approach Using Virtual Screening, MM-GBSA Calculations, MD Simulations, and DFT Analysis

Background/Objectives: Helicobacter pylori infects approximately half of the global population, causing chronic gastritis, peptic ulcers, and gastric cancer, a leading cause of cancer mortality. While current therapies face challenges from rising antibiotic resistance, particularly to clarithromycin, alongside treatment complexity and costs, the World Health Organization has prioritized the development of new antibiotics to combat this high-risk pathogen. In this study, we employed computer-aided drug design (CADD) methodologies, including molecular docking, Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) analysis, molecular dynamics (MD) simulations, and Density Functional Theory (DFT) calculations, to explore the potential repurposing of FDA-approved agents as inhibitors of Helicobacter pylori shikimate kinase (HpSK). Methods: Using the Glide module, the HTVS method was initially applied to screen 1615 FDA-approved agents followed by extra-precision (XP) docking for the obtained 111 hits. The obtained XP scores were used to confine the results to those hits with a score above the reference ligand, shikimate, score. This yielded 31 final hits with an XP score above −5.867. MM-GBSA calculations were performed on these top candidates and the reference ligand to refine the analysis and compounds’ prioritization. Results: The 31 compounds displayed binding free energy (ΔGbind) values ranging from 3.61 to −55.92 kcal/mol, with shikimate exhibiting a ΔGbind of −34.24 kcal/mol and 10 hits having a lower ΔGbind value. Out of these ten, three drugs—Dolutegravir, Cangrelor, and Isavuconazonium—were selected for further analysis based on their drug-like properties. Robust and stable binding profiles for both Isavuconazonium and Cangrelor were verified via molecular dynamics simulation. Additionally, Density Functional Theory (DFT) analysis was conducted, and the Highest Occupied Molecular Orbitals (HOMOs), Lowest Unoccupied Molecular Orbitals (LUMOs), and the energy gap (HLG) between them were calculated. All three drug candidates displayed lower HLG values than shikimate, suggesting higher reactivity and more efficient electronic transitions than the reference ligand. Conclusions: These findings suggest that the identified drugs, although not optimal for direct repurposing, would serve as promising leads against Helicobacter pylori shikimate kinase. These drugs could be valuable leads for experimental assessment and further optimization, particularly with no prototype yet identified. In terms of potential for clinical repurposing, the results point to diflunisal as a promising candidate for further testing.

Revealing 5-(3,5-difluorobenzyl)-1H-indazole as the active pharmacophore of ALK/ROS1 dual inhibitors through theoretical calculations and biological activity evaluations

Anaplastic lymphoma kinase (ALK) and tyrosine protein kinase (ROS1) are recognized as driver genes in lung cancer, with dual inhibition of both targets offering a promising approach to enhance therapeutic outcomes in non-small cell lung cancer (NSCLC). Although numerous ALK/ROS1 inhibitors have received FDA approval, detailed research into the essential active structural motifs within these inhibitors remains limited. Addressing this gap, the current study employed computer-aided drug design (CADD) methodologies, incorporating bioisosteric and conformational similarity principles to design and synthesize 31 dual-target 2-morpholinobenzamide derivatives. These derivatives each include the 5-(3,5-difluorobenzyl)-1H-indazole, 4-benzylmorpholine, and thiophene moieties. Based on docking binding energies, we proposed that 5-(3,5-difluorobenzyl)-1H-indazole may represent a key pharmacophore for ALK/ROS1 activity. Subsequent kinase and cellular assays validated this hypothesis, with compound X4 exhibiting optimal inhibitory activity against both ALK and ROS1 kinases and lung cancer cell lines, achieving IC50 values of 0.512 µM (ALK), 0.766 µM (ROS1), and 0.034 ± 0.002 µM (H2228). In vitro antitumor assays demonstrated dose-dependent induction of apoptosis in H2228 cells by X4. Western blot (WB) analysis further confirmed that X4 effectively suppresses the expression of p-ALK and p-ERK. Importantly, X4 exhibited high specificity in targeting ALK and ROS1 across a range of kinases. In an H2228 xenograft model, X4 achieved a tumor inhibition rate of 54.71 %, underscoring its considerable potential in ALK/ROS1 inhibition.

Molecular hybridization assisted multi-technique approach for designing USP21 inhibitors to halt catalytic triad-mediated nucleophilic attack and suppress pancreatic ductal adenocarcinoma progression: A molecular dynamics study

AimsPancreatic cancer, the 12th-most common cancer, globally, is highly challenging to treat due to its complex epigenetic, metabolic, and genomic characteristics. In pancreatic ductal adenocarcinoma, USP21 acts as an oncogene by stabilizing the long isoform of Transcription Factor 7, thereby activating the Wnt signaling pathway. This study aims to inhibit activation of this pathway through computer-aided drug discovery. Accordingly, four libraries of compounds were designed to target the USP21's catalytic domain (Cys221, His518, Asp534), responsible for its deubiquitinating activity. Main methodsUtilizing an array of computer-aided drug design methodologies, such as molecular docking, virtual screening, principal component analysis, molecular dynamics simulation, and dynamic cross-correlation matrix, the structural and functional characteristics of the USP21-inhibitor complex were examined. Following the evaluation of the binding affinities, 20 potential ligands were selected, and the best ligand was subjected to additional molecular dynamics simulation study. Key findingsThe results indicated that the ligand-bound USP21 exhibited reduced structural fluctuations compared to the unbound form, as evident from RMSD, RMSF, Rg, and SASA graphs. ADMET analysis of the top ligand showed promising pharmacokinetic and pharmacodynamic profiles, good bioavailability, and low toxicity. The stable conformations of the proposed drug when bound to their target cavities indicate a robust binding affinity of −9.3 kcal/mol. The drug exhibits an elevated pKi value of 6.82, a noteworthy pIC50 value of 5.972, and a pKd value of 6.023 proving its high affinity and inhibitory potential towards the target. SignificanceIn-vitro testing of the top compound (MOLHYB-0436) could lead to its use as a potential treatment for pancreatic cancer.

Формирование методики автоматизированного проектирования аэрогидродинамических компоновок экранопланов на основе численного моделирования

На сегодняшний день известно множество компьютерных программ, предназначенных для оптимального проектирования судов различных типов, которые в совокупности с CAD-пакетами (CAD – computer aided design, позволяют разработать компьютерную модель обводов и спецификации основных элементов судна для ее последующего использования в разработке конструкторской документации. В настоящей работе исследуются возможности применения современных компьютерных технологий в формировании методики автоматизированного проектирования аэрогидродинамической компоновки экраноплана, удовлетворяющей требованиям продольной статической устойчивости. Приводятся результаты решения задачи оптимального проектирования компоновки крыла и оперения экраноплана на основе численного моделирования аэрогидродинамики. Предложен алгоритм проектирования аэрогидродинамической компоновки экраноплана на основе численного моделирования. Today, there are many computer programs designed for optimal design of ships of various types, which, together with CAD packages (CAD - computer aided design, allow you to develop a computer model of the contours and specifications of the main elements of the vessel for its subsequent use in the development of design documentation. In this paper, the possibilities of using modern computer technologies in the formation of a computer-aided design methodology for the aerohydrodynamic layout of an ekranoplane that meets the requirements of longitudinal static stability are investigated. The results of solving the problem of optimal design of the wing and tail assembly of an ekranoplane based on numerical modeling of aero-hydrodynamics are presented. An algorithm for designing the aerohydrodynamic layout of an ekranoplane based on numerical modeling is proposed.

Proposal of pharmacophore model for HIV reverse transcriptase inhibitors: Combined mutational effect analysis, molecular dynamics, molecular docking and pharmacophore modeling study.

Antiretroviral therapy (ART) efficacy is jeopardized by the emergence of drug resistance mutations in HIV, compromising treatment effectiveness. This study aims to propose novel analogs of Effavirenz (EFV) as potential direct inhibitors of HIV reverse transcriptase, employing computer-aided drug design methodologies. Three key approaches were applied: a mutational profile study, molecular dynamics simulations, and pharmacophore development. The impact of mutations on the stability, flexibility, function, and affinity of target proteins, especially those associated with NRTI, was assessed. Molecular dynamics analysis identified G190E as a mutation significantly altering protein properties, potentially leading to therapeutic failure. Comparative analysis revealed that among six first-line antiretroviral drugs, EFV exhibited notably low affinity with viral reverse transcriptase, further reduced by the G190E mutation. Subsequently, a search for EFV-similar inhibitors yielded 12 promising molecules based on their affinity, forming the basis for generating a pharmacophore model. Mutational analysis pinpointed G190E as a crucial mutation impacting protein properties, potentially undermining therapeutic efficacy. EFV demonstrated diminished affinity with viral reverse transcriptase, exacerbated by the G190E mutation. The search for EFV analogs identified 12 high-affinity molecules, culminating in a pharmacophore model elucidating key structural features crucial for potent inhibition. This study underscores the significance of EFV analogs as potential inhibitors of HIV reverse transcriptase. The findings highlight the impact of mutations on drug efficacy, particularly the detrimental effect of G190E. The generated pharmacophore model serves as a pivotal reference for future drug development efforts targeting HIV, providing essential structural insights for the design of potent inhibitors based on EFV analogs identified in vitro.

Past, Present, and Future Perspectives on Computer-Aided Drug Design Methodologies.

The application of computational approaches in drug discovery has been consolidated in the last decades. These families of techniques are usually grouped under the common name of "computer-aided drug design" (CADD), and they now constitute one of the pillars in the pharmaceutical discovery pipelines in many academic and industrial environments. Their implementation has been demonstrated to tremendously improve the speed of the early discovery steps, allowing for the proficient and rational choice of proper compounds for a desired therapeutic need among the extreme vastness of the drug-like chemical space. Moreover, the application of CADD approaches allows the rationalization of biochemical and interactive processes of pharmaceutical interest at the molecular level. Because of this, computational tools are now extensively used also in the field of rational 3D design and optimization of chemical entities starting from the structural information of the targets, which can be experimentally resolved or can also be obtained with other computer-based techniques. In this work, we revised the state-of-the-art computer-aided drug design methods, focusing on their application in different scenarios of pharmaceutical and biological interest, not only highlighting their great potential and their benefits, but also discussing their actual limitations and eventual weaknesses. This work can be considered a brief overview of computational methods for drug discovery.

Updates on drug designing approach through computational strategies: a review.

The drug discovery and development (DDD) process in pursuit of novel drug candidates is a challenging procedure requiring lots of time and resources. Therefore, computer-aided drug design (CADD) methodologies are used extensively to promote proficiency in drug development in a systematic and time-effective manner. The point in reference is SARS-CoV-2 which has emerged as a global pandemic. In the absence of any confirmed drug moiety to treat the infection, the science fraternity adopted hit and trial methods to come up with a lead drug compound. This article is an overview of the virtual methodologies, which assist in finding novel hits and help in the progression of drug development in a short period with a specific medicinal solution.

In silico approach towards polyphenols as targeting glucosamine-6-phosphate synthase for Candida albicans

Candida albicans is one of the most common species of fungus with life-threatening systemic infections and a high mortality rate. The outer cell wall layer of C. albicans is packed with mannoproteins and glycosylated polysaccharide moieties that play an essential role in the interaction with host cells and tissues. The glucosamine-6-phosphate synthase enzyme produces N-acetylglucosamine, which is a crucial chemical component of the cell wall of Candida albicans. Collectively, these components are essential to maintain the cell shape and for infection. So, its disruption can have serious effects on cell growth and morphology, resulting in cell death. Hence, it is considered a good antifungal target. In this study, we have performed an in silico approach to analyze the inhibitory potential of some polyphenols obtained from plants. Those can be considered important in targeting against the enzyme glucosamine-6-phosphate synthase (PDB-2VF5). The results of the study revealed that the binding affinity of complexes theaflavin and 3-o-malonylglucoside have significant docking scores and binding free energy followed by significant ADMET parameters that predict the drug-likeness property and toxicity of polyphenols as potential ligands. A molecular dynamic simulation was used to test the validity of the docking scores, and it showed that the complex remained stable during the period of the simulation, which ranged from 0 to 100 ns. Theaflavins and 3-o-malonylglucoside may be effective against Candida albicans using a computer-aided drug design methodology that will further enable researchers for future in vitro and in vivo studies, according to our in silico study. Communicated by Ramaswamy H. Sarma

Multi-Section Chassis for Extreme Terrain

One of the options for the layout of the adaptive chassis of a wheeled vehicle is a multi-section system in which the sections are connected by means of hinges. The article considers an approach to building a methodology for computer-aided design of a family of mobile wheeled chassis of various weight categories and economic purposes. The principles of unification of the design of original units and the choice of supplied components are proposed. The main directions of the application of technology and the use of advanced machines are analyzed. Industry technologies are indicated that allow to reduce the cost of serial production of products.

Epicatechin analogues may hinder human parainfluenza virus infection by inhibition of hemagglutinin neuraminidase protein and prevention of cellular entry.

Human parainfluenza viruses (HPIVs) are ( -)ssRNA viruses belonging to Paramyoviridaie family. They are one of the leading causes of mortality in infants and young children and can cause ailments like croup, bronchitis, and pneumonia. Currently, no antiviral medications or vaccines are available to effectively treat parainfluenza. This necessitates the search for a novel and effective treatment. Computer-aided drug design (CADD) methodology can be utilized to discover target-based inhibitors with high accuracy in less time. A library of 45 phytocompounds with immunomodulatory properties was prepared. Thereafter, molecular docking studies were conducted to characterize the binding behavior of ligand in the binding pocket of HPIV3 HN protein. The physicochemical properties for screened compounds were computed, and the top hits from docking studies were further analyzed and validated using molecular dynamics simulation studies using the Desmond module of Schrodinger Suite 2021-1, followed by MM/GBSA analysis. The compounds CID:72276 (1) and CID:107905 (2) emerged as lead compounds of our in silico investigation. Further in vitro studies will be required to prove the efficacy of lead compounds as inhibitors and to determine the exact mechanism of their inhibition. Computational studies predict three natural flavonoids to inhibit the HN protein of HPIV3.

Effect of heavy inert ion strikes on cell density-dependent profile variation and distortion during the etching process for high-aspect ratio features

Vertical scaling technique faces a physical limitation in 3D NAND device fabrication, even assuming superior etching technology. Another promising scaling technique to increase the storage density is lateral scaling, which increases the number of holes between slit and slit from four to nine and above. However, unpredictable small critical dimension, feature-to-feature variation, and distortion occur. To elucidate the profile deteriorations induced by the lateral scaling, we analyzed the effect of the angular etching yield dependency of the incident ion fluxes into a given feature using the multiscale technology computer-aided design methodology. As one of the inherent features of the gas, incident angle θmax in which the sputtering yield achieves its maximum value is a crucial factor for analyzing and modeling etching profiles. Moreover, the impact of the heavy inert ion strikes on the unpreferred etching profiles was investigated. In this study, the synergy of lower energy ions, larger fluxes, and larger θmax of heavy inert ions decrease the feature-to-feature variation, reducing hard mask distortion without the etch rate reduction.

Docking-Based Virtual Screening Enables Prioritizing Protein Kinase Inhibitors With In Vitro Phenotypic Activity Against Schistosoma mansoni.

Schistosomiasis is a parasitic neglected disease with praziquantel (PZQ) utilized as the main drug for treatment, despite its low effectiveness against early stages of the worm. To aid in the search for new drugs to tackle schistosomiasis, computer-aided drug design has been proved a helpful tool to enhance the search and initial identification of schistosomicidal compounds, allowing fast and cost-efficient progress in drug discovery. The combination of high-throughput in silico data followed by in vitro phenotypic screening assays allows the assessment of a vast library of compounds with the potential to inhibit a single or even several biological targets in a more time- and cost-saving manner. Here, we describe the molecular docking for in silico screening of predicted homology models of five protein kinases (JNK, p38, ERK1, ERK2, and FES) of Schistosoma mansoni against approximately 85,000 molecules from the Managed Chemical Compounds Collection (MCCC) of the University of Nottingham (UK). We selected 169 molecules predicted to bind to SmERK1, SmERK2, SmFES, SmJNK, and/or Smp38 for in vitro screening assays using schistosomula and adult worms. In total, 89 (52.6%) molecules were considered active in at least one of the assays. This approach shows a much higher efficiency when compared to using only traditional high-throughput in vitro screening assays, where initial positive hits are retrieved from testing thousands of molecules. Additionally, when we focused on compound promiscuity over selectivity, we were able to efficiently detect active compounds that are predicted to target all kinases at the same time. This approach reinforces the concept of polypharmacology aiming for “one drug-multiple targets”. Moreover, at least 17 active compounds presented satisfactory drug-like properties score when compared to PZQ, which allows for optimization before further in vivo screening assays. In conclusion, our data support the use of computer-aided drug design methodologies in conjunction with high-throughput screening approach.

TCAD augmented generative adversarial network for hot-spot detection and mask-layout optimization in a large area HARC etching process

Cost-effective vertical etching of plug holes and word lines is crucial in enhancing 3D NAND device manufacturability. Even though multiscale technology computer-aided design (TCAD) methodology is suitable for effectively predicting etching processes and optimizing recipes, it is highly time-consuming. This article demonstrates that our deep learning platform called TCAD-augmented Generative Adversarial Network can reduce the computational load by 2 600 000 times. In addition, because well-calibrated TCAD data based on physical and chemical mutual reactions are used to train the platform, the etching profile can be predicted with the same accuracy as TCAD-only even when the actual experimental data are scarce. This platform opens up new applications, such as hot spot detection and mask layout optimization, in a chip-level area of 3D NAND fabrication.

Quality assurance of surface layer during ball-bar hardening treatment under conditions of modern digital production

The article presents studies of the quality of the surface layer during treatment with a multi-contact vibration impact tool — a ball-rod hardener, which will significantly facilitate the work of the technologist in technological design in the conditions of modern digital production. The main process parameters affecting the formation of the sur face layer quality were identified. Studies of the process were carried out in order to obtain dependencies for calculating the roughness of the surface, the depth of the strengthened layer, the degree of plastic deformation, residual stresses, processing time and their experimental confirmation. he discrepancy between the results of theoretical and experimental studies does not exceed 20 %, which indicates their high convergence. Technological recommendations are given for designing the technological process of processing with a ball-rod hardener in the conditions of digital production. A methodology for computer-aided design of technological processes using the Microsoft Visual Studio software development environment in the C# programming language has been developed and presented. A software module of the computer-aided design system of technological processes of ball-rod hardener processing has been developed.

Synthesis of miniaturized wideband four‐way filtering power divider consisting of unequal‐width three‐coupled‐lines

A miniaturized wideband four-way filtering power divider (FPD) is presented in this article. It is composed of unequal-width three-coupled-lines (TCLs), stepped-impedance open-circuited stubs, and isolation resistors. By using two groups of the unequal-width TCLs and the stepped-impedance open-circuited stubs, size reduced four-way FPD with wideband filtering responses and out-of-band rejection is realized. Besides, good output ports matching and isolation are obtained by inserting two types of air-bridge resistors. In the theoretical analysis section, the impedance matrix of the unequal-width TCL is introduced, for the first time, and rigorous closed-form design equations for the proposed FPD are also derived. Moreover, the methodology for computer-aided design is given based on the design equations. For demonstration, a prototype operating at 1.5 GHz is designed, fabricated, and measured. The measured results validate the 80% bandwidth with more than 17 dB out-of-band rejection, more than 14 dB isolation and more than 15 dB return loss at all output ports. Compare with the reported four-way FPD with similar bandwidth, a size reduction of 74% is obtained.

Identification of benzamide inhibitors of histone deacetylase 1 from Babesia and Theileria species via high-throughput virtual screening and molecular dynamics simulations.

Theileria and Babesia species are eukaryotic protozoan parasites classified under the order Piroplasmida of the phylum Apicomplexa. Tick vectors transmit these microorganisms in tropical and subtropical regions to a wide range of animals, including ruminants, causing fatal and life-threatening diseases such as bovine babesiosis and theileriosis. Resistance to commercially available drugs requires the search for new drug candidates. Histone deacetylase (HDAC) has a potential to be utilized as a drug target; therefore, it may be considered as an effective alternative. Previous studies revealed that HDAC inhibitors, identified for human use, show promising anti-parasitic effects. We have herein focused on the class I HDAC enzyme, HDAC1, of the Babesia and Theileria species to discover potential benzamide inhibitors by following a streamlined workflow of computer-aided drug design methodology. Molecular docking and molecular dynamics simulations revealed that benzamide derivatives stably interacted with the HDAC1 active site in both parasites as hypothesized. Furthermore, specific residue insertions at the entry point of the active site cleft of parasitic HDAC1 could enable ways to design parasite-specific drugs without adversely affecting host enzymes.

Using computer modelling when creating a heat exchanger for a complex cycle small-size gas turbine plant

Using the complex methodology of computer-aided design, calculation, and production, an experimental plate heat exchanger for a small-size gas turbine plant of complex cycle was created. Using a computer parametric 3D model of the base heat exchangers element (plate) allows for the design, calculation, optimization, and technological preparation of production automatically.. Experimental studies of the heat exchanger for the complex cycle small-size gas turbine plant created according to the proposed methodology confirm its reliability and accuracy.

Automated design, calculation and production of plate heat exchangers for complex cycle gas turbine plants

The comprehensive methodology of computer-aided design and calculation of plate heat exchangers for complex cycle gas turbine plants has been developed. This method allows obtaining a heat exchanger that provides the best thermal and hydraulic characteristics within the specified limits with minimal participation of the designer. The algorithm for closely linking the design stage with the production technology, which makes it possible to obtain a set of 3D models of technological equipment necessary for the producing of a heat exchanger, has been developed. Experimental studies of the heat exchanger produced according to the proposed method showed a close convergence with the calculated data.

A model-based solvent selection and design framework for organic coating formulations

Selection of solvents and calculation of their composition in the final product, is a critical step in coating formulation design. This task can be facilitated by computer-aided methods if the necessary thermodynamic and group contribution property models along with chemical property data are available for the ingredients under consideration. However, these computer-aided procedures must be supplemented and verified by using experimental procedures. Hence, the computer-aided stage can be used to speed-up the solvent selection and design process, efficiently utilize experimental resources and serve as a guide for the formulation chemist.We present in this work an adaption of the generic Computer-Aided Product Design (CAPD) methodology for organic coating formulations. Herein, the paper discusses a model-based framework developed for the design of solvents for such coatings. The applicability of this framework is tested via a case study wherein, solvents for the dispersion of two specific organic pigments are required to be determined, when acrylic polymers are used as dispersing aids.

Integrated Process-Product Design based on COSMO-SAC model: Application to the Production of 2,2,4-Trimethyl-1,2-H-Dihydroquinoline (TMQ)

TMQ (2,2,4-trimethyl-1,2-H-dihydroquinoline) is a widely used and effective antioxidant in rubber production technologies. Its product is a kind of mixture which mainly consists of oligomers such as dimer, trimer and tetramer. The quality of TMQ is determined by the content of oligomers, especially dimer. This paper presents a systematic computer-aided molecular design (CAMD) methodology for designing optimal solvents for the synthesis of TMQ reaction system where the function of such solvents is to enhance the yield by optimal selectivity of reaction and extraction of TMQ products. In this work, we proposed an integrated process-product design framework of reaction and extraction solvent design for TMQ product. In this framework, a decomposition-based method is presented, which involves an integrated property estimation method combined group contribution methods with COSMO-SAC (COnductor-like Screen MOdel for Segment Activity Coefficient) and a process model of chemical and phase equilibrium. The results show that the designed solvents are able to improve the yield of dimer.