Computational Modeling Studies Research Articles

Halloysite Clay Nanotubes for Catalytic Conversion of Biomass: Synergy between Computational Modeling and Experimental Studies

Halloysite Clay Nanotubes for Catalytic Conversion of Biomass: Synergy between Computational Modeling and Experimental Studies

Computer Modeling Study of the Effects of Radio Frequency EM Radiation on Humans

Computer Modeling Study of the Effects of Radio Frequency EM Radiation on Humans

Influence of natural hyoid bone position and surgical repositioning on upper airway patency: A computational finite element modeling study.

A validated finite element model of the rabbit UA was advanced and used to simulate changes in BHP and SHR, alone and in combination. The hyoid was displaced in cranial, caudal, anterior, anterior-cranial and anterior-caudal directions from 1-4mm. Model outcomes included UA collapsibility, measured using closing pressure (Pclose), cross-sectional area (CSA) and soft tissue mechanics (displacement, stress and strain). Graded BHP increments increased Pclose for all directions, and up to 29-43% at 4mm (relative to the original BHP). Anterior-based SHR decreased Pclose (~-115% at 4mm) and increased ΔCSA (~+35% at 4mm). Cranial SHR decreased ΔPclose (-29%), minimally affecting CSA. Caudal SHR increased ΔPclose (+27%) and decreased ΔCSA (-7%). Anterior-cranial and anterior-caudal SHR produced the highest stresses and strains. SHR effects on UA outcomes were dependent on BHP, with more caudal BHPs leading to less effective surgeries. BHP (phenotype) and SHR both alter UA outcomes, with effects dependent on hyoid displacement direction and magnitude. BHP influences the effectiveness of SHR in reducing UA collapsibility. These findings provide further insights into the hyoid's role in UA patency and suggest that considering the hyoid's baseline position and surgical repositioning direction/increment may help improve hyoid surgeries for OSA treatment.

Xylose Acetals - a New Class of Sustainable Solvents and Their Application in Enzymatic Polycondensation.

The use of organic solvents in academic research and industry applications is facing increasing regulatory pressure due to environmental and health concerns. Consequently, there is a growing demand for sustainable solvents, particularly in the enzymatic synthesis and processing of polyesters. Biocatalysts offer a sustainable method for producing these materials; however, achieving high molecular weights often necessitates use of solvents. In this work, we introduce a new class of alternative aprotic solvents with medium polarity produced directly from agricultural waste biomass in up to 83 mol% yield (on xylan basis). The new solvents have a largely unmodified xylose core and acetal functionality, yet they show no peroxide formation and provide reduced flammability risk. We also demonstrate their successful application in enzymatic polycondensation reactions with Candida antarctica lipase B (CaLB). In particular, the solvent dibutylxylose (DBX) outperformed the hazardous solvent diphenyl ether and facilitated polycondensation of the lignin-derived diester pyridine-2,4-dicarboxylate, yielding polyesters with a Mn of >15 kDa. Computational modelling studies provided further insight into the molecular structure and dynamics of CaLB in the presence of new solvents. Lastly, up to 98 wt% of the new xylose acetals were successfully recovered and recycled, further contributing to the sustainability of the overall process.

A Computational Perspective into Binding Mechanism of a potent FAK Inhibitor as Anticancer Drug Candidate: Insights from Molecular Dynamics Simulations

Focal adhesion kinase (FAK) is an important non-receptor tyrosine kinase (nRTK) with crucial role in primary cell functions. Fundamental cellular processes, such as migration, adhesion, proliferation, and survival, are regulated by FAK. The tumorigenesis of FAK is very important since it is overexpressed in advanced cancers, causes malignant features and induces cancer metastasis. The available evidence proposes FAK as a promising target for cancer therapy. At the moment, there are no FAK inhibitors (FAKIs) in the market but several small molecule FAKIs have been developed and a few of them entered into clinical studies as anticancer agents. In spite of these achievements, development of selective and potent FAKIs may be partly hampered by the lack of crystallographic or structural data. This limitation could be resolved through proposing robust ligand–protein binding models to design new FAKIs. GSK2256098 is a small molecule ATP-competitive FAKI that undergoes clinical trials as a monotherapy or in combination with other medications against advanced solid tumors. GSK2256098 have been proven to be a selective and potent agent (IC[Formula: see text] 0.4 nM) with respect to other clinical candidates. With regard to appropriate characteristics, this molecule is particularly amenable for performing computational modeling studies. In this study, we try to propose an applicable binding model of GSK2256098 inside the FAK kinase domain. For this purpose, molecular docking, all-atom 200-ns molecular dynamics simulations and free-energy-calculation methods were applied as consecutive modeling techniques. Atomic insight and dynamic evolution of the system were used to attain a stable binding mode and infer chemical interactions of GSK2256098 inside the kinase domain of FAK. Although complementary investigations need to be conducted, obtained results may offer a structural basis for the development of potent and selective FAKIs.

Family Malvaceae: a potential source of secondary metabolites with chemopreventive and anticancer activities supported with in silico pharmacokinetic and pharmacodynamic profiles.

Cancer is the second most widespread cause of mortality following cardiovascular disorders, and it imposes a heavy global burden. Nowadays, herbal nutraceutical products with a plethora of bioactive metabolites represent a foundation stone for the development of promising chemopreventive and anticancer agents. Certain members of the family Malvaceae have traditionally been employed to relieve tumors. The literature concerning the chemopreventive and anticancer effects of the plant species along with the isolated cytotoxic phytometabolites was reviewed. Based on the findings, comprehensive computational modelling studies were performed to explore the pharmacokinetic and pharmacodynamic profiles of the reported cytotoxic metabolites to present basis for future plant-based anticancer drug discovery. All the available information about the anticancer research in family Malvaceae and its cytotoxic phytometabolites were retrieved from official sources. Extensive search was carried out using the keywords Malvaceae, cancer, cytotoxicity, mechanism and signalling pathway. Pharmacokinetic study was performed on the cytotoxic metabolites using SWISS ADME model. Acute oral toxicity expressed as median lethal dose (LD50) was predicted using Pro Tox 3.0 web tool. The compounds were docked using AutoDock Vina platform against epidermal growth factor receptor (EGFR kinase enzyme) obtained from the Protein Data Bank. Molecular dynamic simulations and MMGBSA calculations were performed using GROMACS 2024.2 and gmx_MMPBSA tool v1.5.2. One hundred forty-five articles were eligible in the study. Several tested compounds showed safe pharmacokinetic properties. Also, the molecular docking study showed that the bioactive metabolites possessed agreeable binding affinities to EGFR kinase enzyme. Tiliroside (25), boehmenan (30), boehmenan H (31), and isoquercetin (22) elicited the highest binding affinity toward the enzyme with a score of -10.4, -10.4, -10.2 and -10.1Kcal/mol compared to the reference drug erlotinib having a binding score equal to -9Kcal/mol. Additionally, compounds 25 and 31 elicited binding free energies equal to -42.17 and -42.68Kcal/mol, respectively, comparable to erlotinib. Overall, the current study presents helpful insights into the pharmacokinetic and pharmacodynamic properties of the reported cytotoxic metabolites belonging to family Malvaceae members. The molecular docking and dynamic simulations results intensify the roles of secondary metabolites from medicinal plants in fighting cancer.

In Vitro and In Vivo Biological Evaluation of Novel 1,4-Naphthoquinone Derivatives as Potential Anticancer Agents.

A novel library of naphthoquinone derivatives (3-5 aa) was synthesized and evaluated for their anticancer properties. Specifically, compounds 5 i, 5 l, 5 o, 5 q, 5 r, 5 s, 5 t, and 5 v demonstrated superior cytotoxic activity against the cancer cell lines that were studied. All the studied compounds exhibited a higher selectivity index (SI) and a favourable safety profile than the standard drug doxorubicin. Notably, compound 5 v displayed a greater cytotoxic effect on MCF-7 cells (IC50=1.2 μM, and 0.9 μM at 24 h and 48 h, respectively) compared to the standard drug doxorubicin (IC50=2.4 μM, and 2.1 μM at 24 h and 48 h, respectively). To further investigate the mechanism of cytotoxic effect, additional anticancer studies were conducted with 5 v in MCF-7 cells. The studies are including morphological changes, AO/EB (acridine orange/ethidium bromide) double staining, apoptosis analysis, cell colony assay, SDS-PAGE and Western blotting, cell cycle analysis, and detecting reactive oxygen species (ROS) assay. The findings showed that 5 v triggered cytotoxic effects in MCF-7 cells through the initiation of cell cycle arrest at the G1/S phase and necrosis. In vivo ecotoxicity studies indicated that 5 v had lower toxicity towards zebrafish larvae (LC50=50.15 μM) and had an insignificant impact on cardiac functions. In vivo xenotransplantation of MCF-7 cells in zebrafish larvae demonstrated a significant reduction in tumour volume in the xenograft. Approximately 95 % of the zebrafish larvae with 5 v xenografts survived after 10 days of the treatment. Finally, a computational modelling study was conducted on four protein receptors, namely ER, EFGR, BRCA1, and VEFGR2. The findings highlight the importance of the aminonaphthoquinone moiety, amide linkage, and propyl thio moiety in enhancing the anticancer properties. 5 v exhibited superior drug-likeness features and docking scores (-9.1, -7.1, -8.9, and -10.9 kcal/mol) compared to doxorubicin (-7.2, -6.1, -6.9, and -7.3 kcal/mol) against ER, EFGR, BRCA1, and VEGFR2 receptors, respectively. Therefore, the notable antitumor effects of naphthoquinone derivatives (3-5 aa) suggest that these molecular frameworks may play a role in the development of promising anticancer agents for cancer treatment.

A Methodology to Quantify the Effective Vertical Thickness of Prephonatory Vocal Fold Medial Surface

ObjectiveThe shape of the vocal fold medial surface, particularly its vertical thickness, has been shown in computational and physical modeling studies to be highly influential in regulating glottal closure during phonation. However, because of the difficulty to quantify the vertical thickness in real vocal folds, this influence has often been overlooked in clinical contexts. Therefore, the goal of this study is to present a method to calculate an effective vertical thickness of the medial surface that is predictive of the glottal closure pattern during phonation. MethodsAn effective vertical thickness of the medial surface is calculated as a weighted integral of the medial surface contour along the vertical dimension. The weight is one for the part of the medial surface within a fixed threshold distance from the most medial point, and decays exponentially otherwise. The influence of the threshold distance value on the effective thickness value is investigated. Additionally, the sensitivity of the calculated effective thickness to slight misidentification of the vertical glottal midline is also studied. The methodology is validated on the vocal fold medial surface data from a canine hemilarynx at different levels of thyroarytenoid muscle activation. ResultsFor most threshold distances, the thickness follows an expected sigmoid-like trend with respect to the thyroarytenoid muscle activation level. A threshold distance of 0.05 mm appears optimal as it produced thickness changes in a range comparable to previous computational and experimental studies. The methodology is relatively robust to slight misidentification of the vertical glottal midline. ConclusionsA methodology to estimate the effective vocal fold vertical thickness from medial surface contours is proposed. The methodology can be applied in future studies to correlate medial surface shape to relevant parameters characterizing vocal fold vibration as well as clinical evaluation of treatment effectiveness.

Comparison of Laminar and Turbulent K–Omega Shear Stress Transport Models Under Realistic Boundary Conditions Using Clinical Data for Arterial Stenosis

Abstract Early diagnosis of cardiovascular diseases (CVDs), including arterial stenosis, enables targeted treatments that reduce CVD mortality. It is vital to improve the accuracy of early diagnostic tools. Current computational studies of stenosis use mathematical models, such as laminar and k–omega shear stress transport (SST) models, available in ansys (Fluent and CFX), openfoam, and comsol software packages. Users can adjust boundary conditions, such as inlet velocity and outlet pressure using user-defined functions (UDFs) with different expressions and constant values. However, currently there is no rule over what to impose at these boundaries, and previous studies have used various assumptions, such as rigid artery wall, one-way fluid–structure interaction (FSI) or two-way FSI, and the blood's Newtonian or non-Newtonian material properties. This variety in construction has associated deviations of the models from the clinical data and lessens the value of the models as potential diagnostic or predictive tools for medical practitioners. In this study, we examine arterial stenosis models, with severities of 20%, 40%, and 50%, compared with the healthy artery analyzed in terms of strain energy to the artery wall. Additionally, we investigate elastic walls using one-way FSI, comparing with laminar and k–omega SST. These boundary conditions are based on clinical data. The results regarding the strain energy (mJ) behavior along the artery wall show that the k–omega SST model outperforms the laminar model for short arterial segments and under the Newtonian assumption with a no-slip boundary wall and turbulent flow.

The Use of Organoclays as Excipient for Metformin Delivery: Experimental and Computational Study

This work combines experimental and computational modeling studies for the preparation of a composite of metformin and an organoclay, examining the advantages of a Tunisian clay used for drug delivery applications. The clay mineral studied is a montmorillonite-like smectite (Sm-Na), and the organoclay derivative (HDTMA-Sm) was used as a drug carrier for metformin hydrochloride (MET). In order to assess the MET loading into the clays, these materials were characterized by means of cation exchange capacity assessment, specific surface area measurement, and with the techniques of X-ray diffraction (XRD), differential scanning calorimetry, X-ray fluorescence spectroscopy, and Fourier-transformed infrared spectroscopy. Computational molecular modeling studies showed the surface adsorption process, identifying the clay–drug interactions through hydrogen bonds, and assessing electrostatic interactions for the hybrid MET/Sm-Na and hydrophobic interactions and cation exchange for the hybrid MET/HDTMA-Sm. The results show that the clays (Sm-Na and HDTMA-Sm) are capable of adsorbing MET, reaching a maximum load of 12.42 and 21.97 %, respectively. The adsorption isotherms were fitted by the Freundlich model, indicating heterogeneous adsorption of the studied adsorbate–adsorbent system, and they followed pseudo-second-order kinetics. The calculations of ΔGº indicate the spontaneous and reversible nature of the adsorption. The calculation of ΔH° indicates physical adsorption for the purified clay (Sm-Na) and chemical adsorption for the modified clay (HDTMA-Sm). The release of intercalated MET was studied in media simulating gastric and intestinal fluids, revealing that the purified clay (Sm-Na) and the modified organoclay (HDTMA-Sm) can be used as carriers in controlled drug delivery in future clinical applications. The molecular modeling studies confirmed the experimental phenomena, showing that the main adsorption mechanism is the cation exchange process between proton and MET cations into the interlayer space.

Novel Approaches and Emerging Trends in Hydrotropic Solubilization Technology

Hydrotropic solubilization technology enhances the solubility and bioavailability of poorly water-soluble drugs, a major challenge in pharmaceutical research. This review discusses hydrotropic agents’ structures, the solubilization process, and factors affecting drug solubility. It explores optimizing agent concentrations, the role of computer modeling and QSAR studies, and hydrotropes’ impact on overcoming biological barriers and improving pharmacokinetics and pharmacodynamics. The review highlights hydrotropic compounds’ potential in advancing pharmaceutical formulations and clinical applications.

Understanding the variability of the proximal femoral canal: A computational modeling study.

Statistical shape modeling (SSM) offers the potential to describe the morphological differences in similar shapes using a compact number of variables. Its application in orthopedics is rapidly growing. In this study, an SSM of the intramedullary canal of the proximal femur was built, with the aim to better understanding the complexity of its shape which may, in turn, enhance the preoperative planning of total hip arthroplasty (THA). This includes the prediction of the prosthetic femoral version (PFV) which is known to be highly variable amongst patients who have undergone THA. The model was built on three dimensional (3D) models of 64 femoral canals which were generated from pelvic computed tomography images including the proximal femur in the field of view. Principal component analysis (PCA) was performed on the mean shape derived from the model and each segmented canal. Five prominent modes of variations representing approximately 84% of the total 3D variations in the population of shapes were found to capture variability in size, proximal torsion, intramedullary femoral anteversion, varus/valgus orientation, and distal femoral shaft twist/torsion, respectively. It was established that the intramedullary femoral canal is highly variable in its size, shape, and orientation between different subjects. PCA-driven SSM is beneficial for identifying patterns and extracting valuable features of the femoral canal.

The effect of fixed and functional remodelling on conduction velocity, wavefront propagation, and rotational activity formation in atrial fibrillation.

Pathophysiology of atrial fibrillation (AF) remains unclear. Interactions between scar and conduction velocity (CV) and their impact on wavefront propagation in sinus rhythm (SR) and rotational activity burden in AF were evaluated. Local activation times (LATs) and voltage data were obtained from patients undergoing ablation for persistent AF. Omnipolar voltage (OV) and bipolar voltage (BV) data were obtained during AF and SR at pacing intervals of 600 and 250 ms. Local activation times were used to determine CV dynamics and their relationship to the underlying voltage and pivot points in SR. Computational modelling studies were performed to evaluate the impact of CVs and fibrosis on rotational activity burden in AF. Data from 60 patients with a total of 2 768 400 LAT and voltage points were analysed (46 140 ± 5689 points/patient). Voltage determined CV dynamics. Enhanced CV heterogeneity sites were predominantly mapped to low-voltage zones (LVZs) (0.2-0.49 mV) (128/168, 76.2%) rather than LVZs (<0.2 mV) and frequently co-located to pivot points (151/168, 89.9%). Atrial fibrillation OV maps correlated better with SR BV 250 ms than 600 ms maps, thereby representing fixed and functional remodelling. Sinus rhythm maps at 250 ms compared with 600 ms harboured a greater number of pivot points. Increased CV slowing and functional remodelling on computational models resulted in a greater rotational activity burden. Conduction velocity dynamics are impacted by the degree of scar. Conduction velocity heterogeneity and functional remodelling impacts wavefront propagation in SR and rotational activity burden in AF. This study provides insight into the pathophysiology of AF and identifies potential novel ablation targets.

Monte Carlo simulation of spatial frequency domain imaging for breast tumors during compression.

Near-infrared optical imaging methods have shown promise for monitoring response to neoadjuvant chemotherapy (NAC) for breast cancer, with endogenous contrast coming from oxy- and deoxyhemoglobin. Spatial frequency domain imaging (SFDI) could be used to detect this contrast in a low-cost and portable format, but it has limited imaging depth. It is possible that local tissue compression could be used to reduce the effective tumor depth. To evaluate the potential of SFDI for therapy response prediction, we aim to predict how changes to tumor size, stiffness, and hemoglobin concentration would be reflected in contrast measured by SFDI under tissue compression. Finite element analysis of compression on an inclusion-containing soft material is combined with Monte Carlo simulation to predict the measured optical contrast. When the effect of compression on blood volume is not considered, contrast gain from compression increases with the size and stiffness of the inclusion and decreases with the inclusion depth. With a model of reduction of blood volume from compression, compression reduces imaging contrast, an effect that is greater for larger inclusions and stiffer inclusions at shallower depths. This computational modeling study represents a first step toward tracking tumor changes induced by NAC using SFDI and local compression.

Multiscale modelling and characterisation of fused filament fabricated neat and graphene nanoplatelet reinforced G-polymers

AbstractIn this study, the fused filament fabrication of novel biodegradable G-polymer is investigated, including also filaments reinforced by graphene nanoplatelets. A combined framework of computational multiscale modelling and experimental studies is applied to characterise and model the mechanical behaviour of composite and nanocomposite materials, fabricated using a 3D-printer by depositing G-polymer filaments in +45$$^\circ$$ ∘ and $$-45^\circ$$ - 45 ∘ angles. The investigation is performed on both hot-extruded single filaments and 3D-printed specimens. Experimental results of hot-extruded single filaments are utilized on the microscale to extract the macroscale constitutive models. At the microscale level, representative volume elements with different percentages of penetration are analyzed to compute the effective orthotropic elastic material properties. A comprehensive comparison study is conducted using different micromechanical models, multiscale simulation outputs, and the mechanical properties resulting from experiments. The accuracy of the results obtained from the homogenization technique is validated against realistic finite element microstructural models and experimental measurements. The results demonstrate that computational homogenization, when coupled with accurate property characterisation, serves as a reliable tool for predicting the elastic response of 3D-printed parts. Furthermore, the proposed framework reduces the need for extensive experimental replication and lowers manufacturing costs.

Antimicrobial activity of compounds identified by artificial intelligence discovery engine targeting enzymes involved in Neisseria gonorrhoeae peptidoglycan metabolism

BackgroundNeisseria gonorrhoeae (Ng) causes the sexually transmitted disease gonorrhoea. There are no vaccines and infections are treated principally with antibiotics. However, gonococci rapidly develop resistance to every antibiotic class used and there is a need for developing new antimicrobial treatments. In this study we focused on two gonococcal enzymes as potential antimicrobial targets, namely the serine protease L,D-carboxypeptidase LdcA (NgO1274/NEIS1546) and the lytic transglycosylase LtgD (NgO0626/NEIS1212). To identify compounds that could interact with these enzymes as potential antimicrobials, we used the AtomNet virtual high-throughput screening technology. We then did a computational modelling study to examine the interactions of the most bioactive compounds with their target enzymes. The identified compounds were tested against gonococci to determine minimum inhibitory and bactericidal concentrations (MIC/MBC), specificity, and compound toxicity in vitro.ResultsAtomNet identified 74 compounds that could potentially interact with Ng-LdcA and 84 compounds that could potentially interact with Ng-LtgD. Through MIC and MBC assays, we selected the three best performing compounds for both enzymes. Compound 16 was the most active against Ng-LdcA, with a MIC50 value < 1.56 µM and MBC50/90 values between 0.195 and 0.39 µM. In general, the Ng-LdcA compounds showed higher activity than the compounds directed against Ng-LtgD, of which compound 45 had MIC50 values of 1.56–3.125 µM and MBC50/90 values between 3.125 and 6.25 µM. The compounds were specific for gonococci and did not kill other bacteria. They were also non-toxic for human conjunctival epithelial cells as judged by a resazurin assay. To support our biological data, in-depth computational modelling study detailed the interactions of the compounds with their target enzymes. Protein models were generated in silico and validated, the active binding sites and amino acids involved elucidated, and the interactions of the compounds interacting with the enzymes visualised through molecular docking and Molecular Dynamics Simulations for 50 ns and Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA).ConclusionsWe have identified bioactive compounds that appear to target the N. gonorrhoeae LdcA and LtgD enzymes. By using a reductionist approach involving biological and computational data, we propose that compound Ng-LdcA-16 and Ng-LtgD-45 are promising anti-gonococcal compounds for further development.

Paradoxes in magnesium transport in type 1 Bartter's syndrome and Gitelman's syndrome: a modeling analysis.

Type 1 Bartter's syndrome and Gitelman's syndrome are characterized by mutations in two key renal Na+ transporters, Na-K-2Cl cotransporter (NKCC2) and Na-Cl cotransporter (NCC). Since these two transporters play an important role in regulating magnesium (Mg2+) and calcium (Ca2+) transport in the kidney, significant alterations in the transport of these two electrolytes are observed in type 1 Bartter's syndrome and Gitelman's syndrome. In this study, we used our sex-specific computational models of renal electrolyte transport in rats to understand the complex compensatory mechanisms, in terms of alterations in tubular dimensions and ion transporter activities, that lead to Mg2+ and Ca2+ preservation or wasting in these two genetic disorders. Given the sexual dimorphism in renal transporter patterns, we also assessed how the magnitude of these alterations may differ between males and females. Model simulations showed that in type 1 Bartter's syndrome, nephron adaptations prevent salt wasting and favor Mg2+ preservation but not Ca2+, whereas in Gitelman's syndrome, those adaptations favor Ca2+ preservation over Mg2+. In addition, our models predicted that the compensatory alterations in tubular dimensions and ion transporter activities are stronger in females than in males.NEW & NOTEWORTHY Although changes in Ca2+ excretion in type 1 Bartter's syndrome and Gitelman's syndrome are well understood, Mg2+ excretion displays an interesting paradox. This computational modeling study provides insights into how renal adaptations in these two disorders impact Ca2+ and Mg2+ transport along different nephron segments. Model simulations showed that nephron adaptations favor Mg2+ preservation over Ca2+ in Bartter's syndrome and Ca2+ preservation over Mg2+ in Gitelman's syndrome and are stronger in females than in males.

Computer Modelling Study of Volume Kinetics in Intraocular Segments Following Airbag Impact Using Finite Element Analysis.

We have previously studied the physiological and mechanical responses of the eye to blunt trauma in various situations using finite element analysis (FEA). In this study, we evaluated the volume kinetics of an airbag impact on the eye using FEA to sequentially determine the volume change rates of intraocular segments at various airbag deployment velocities. The human eye model we created was used in simulations with the FEA program PAM-GENERISTM (Nihon ESI, Tokyo, Japan). Different airbag deployment velocities, 30, 40, 50, 60 and 70 m/s, were applied in the forward direction. The volume of the deformed eye impacted by the airbag was calculated as the integrated value of all meshes in each segment, and the decrease rate was calculated as the ratio of the decreased volume of each segment at particular timepoints to the value before the airbag impact. The minimum volume of the anterior chamber was 63%, 69% and 50% at 50, 60 and 70 m/s airbag impact velocity, respectively, showing a curve with a sharp decline followed by gradual recovery. In contrast to the anterior chamber, the volume of the lens recovered promptly, reaching 80-90% at the end of observation, except for the case of 60 m/s. Following the decrease, the volume increased to more than that of baseline at 60 m/s. The rate of volume change of the vitreous was distributed in a narrow range, 99.2-100.4%. In this study, we found a large, prolonged decrease of volume in the anterior chamber, a similar large decrease followed by prompt recovery of volume in the lens, and a time-lag in the volume decrease between these tissues. These novel findings may provide an important insight into the pathophysiological mechanism of airbag ocular injuries through this further evaluation, employing a refined FEA model representing cuboidal deformation, to develop a more safe airbag system.

Computational modeling study of IL-15-NGR peptide fusion protein: a targeted therapeutics for hepatocellular carcinoma

The primary challenge to improving existing cancer treatment is to develop drugs that specifically target tumor cell. NGR peptide is tumor homing peptide that selectively target cancer cells while interleukin 15 is a pleiotropic cytokine with anticancer properties. This study computationally engineered a IL15-NGR fusion peptide by linking the homing peptide NGR with the targeting peptide IL-15. After evaluating and validating the chimeric peptide, we docked it to the IL-15Rα/IL-15Rβ/γc heterodimer receptor, examining the interactions and binding energy and lastly, molecular dynamics simulations were performed. The secondary and tertiary structures, along with physicochemical properties of the designed IL-15-NGR chimeric protein, were predicted using GOR IV, trRosetta and ProtParam online servers respectively. The quality and 3D structure validation were confirmed via ProSA-web and SAVES 6.0 analysis which predicted an ERRAT score of 96.72%, with 97.6% of residues in the Ramachandran plot, validating its structure. Finally, Docking, MD simulations and interaction analysis were performed using ClusPro 2.0 and GROMACS and PDBsum, which exhibited significant hydrogen bonding and salt bridges, confirming the formation of a stable docked complex. These results were further corroborated by simulation analysis, which demonstrated a stable and dynamic behavior of the docked complex in a biological environment. The predicted high expression value of fusion protein was 0.844 in E.coli using SOLUPROT tool. These findings suggest efficient expression of the IL15-NGR fusion protein if its gene is inserted into E. coli and indicates its potential as a safe and effective anticancer treatment, paving the way for targeted therapeutic interventions.Graphical abstract

Computational Modeling Study of the Molecular Basis of dNTP Selectivity in Human Terminal Deoxynucleotidyltransferase.

Human terminal deoxynucleotidyl transferase (TdT) can catalyze template-independent DNA synthesis during the V(D)J recombination and DNA repair through nonhomologous end joining. The capacity for template-independent random addition of nucleotides to single-stranded DNA makes this polymerase useful in various molecular biological applications involving sequential stepwise synthesis of oligonucleotides using modified dNTP. Nonetheless, a serious limitation to the applications of this enzyme is strong selectivity of human TdT toward dNTPs in the order dGTP > dTTP ≈ dATP > dCTP. This study involved molecular dynamics to simulate a potential impact of amino acid substitutions on the enzyme's selectivity toward dNTPs. It was found that the formation of stable hydrogen bonds between a nitrogenous base and amino acid residues at positions 395 and 456 is crucial for the preferences for dNTPs. A set of single-substitution and double-substitution mutants at these positions was analyzed by molecular dynamics simulations. The data revealed two TdT mutants-containing either substitution D395N or substitutions D395N+E456N-that possess substantially equalized selectivity toward various dNTPs as compared to the wild-type enzyme. These results will enable rational design of TdT-like enzymes with equalized dNTP selectivity for biotechnological applications.