Computational Insights Research Articles

Targeting CCR3 with antagonist SB 328437 sensitizes 5‑fluorouracil‑resistant gastric cancer cells: Experimental evidence and computational insights.

Gastric cancer (GC) ranks fifth globally in cancer diagnoses and third for cancer-related deaths. Chemotherapy with 5-fluorouracil (5-FU), a primary treatment, faces challenges due to the development of chemoresistance. Tumor microenvironment factors, including C-C motif chemokine receptor 3 (CCR3), can contribute to chemoresistance. The present study evaluated the effect of CCR3 receptor inhibition using the antagonist SB 328437 and the molecular dynamics of this interaction on resistance to 5-FU in gastric cancer cells. The 5-FU-resistant AGS cell line (AGS R-5FU) demonstrated notable tolerance to higher concentrations of 5-FU, with a 2.6-fold increase compared with the parental AGS cell line. Furthermore, the mRNA expression levels of thymidylate synthase (TS), a molecular marker for 5-FU resistance, were significantly elevated in AGS R-5FU cells. CCR3 was shown to be expressed at significantly higher levels in these resistant cells. Combining SB 328437 with 5-FU resulted in a significant decrease in cell viability, particularly at higher concentrations of 5-FU. Furthermore, when SB 328437 was combined with 5-FU at a high concentration, the relative mRNA expression levels of CCR3 and TS decreased significantly. Computational analysis of CCR3 demonstrated dynamic conformational changes, especially in extracellular loop 2 region, which indicated potential alterations in ligand recognition. Docking simulations demonstrated that SB 328437 bound to the allosteric site of CCR3, inducing a conformational change in ECL2 and hindering ligand recognition. The present study provides comprehensive information on the molecular and structural aspects of 5-FU resistance and CCR3 modulation, highlighting the potential for therapeutic application of SB 328437 in GC treatment.

Computational insights into the static, solvent and frequency-dependent nonlinear optical properties of head-to-tail novel non-fullerene compounds for modern electro-optic applications

Addressing the growing demand of novel nonlinear optical (NLO) materials, hyper-rayleigh-scattering (HRS) in solution, static and frequency-dependent NLO properties of novel IsoIDTC-based derivatives (AFS1-AFS9) are computed at laser frequencies of 1064 nm and 532 nm to explore SHG β (−2ω, ω, ω) and EOPE β (−ω, ω, 0) for modern electro-optic applications. Structural, electrical, and NLO features were calculated using DFT, and TDDFT modeling, HRS, and DR measurement. The polar, non-polar solvent, and gas phase NLO properties show the highest linear polarizability of 8.92 × 102 a.u. (AFS8) in water, 9.68 × 102 a.u. (AFS5) in gas, and 9.56 × 102 a.u. (AFS) in benzene. AFS8 push-pulls exhibit the highest first hyper-polarizability (βtot) at 1.05 × 105 a.u. and 1.47 × 105 a.u. in gas and benzene solvent, respectively. The proposed chromophores showed substantial SHG and EOPE values at 532 nm and 1064 nm lasers compared toIDT, hence, allowed the successful synthesis of NLO materials for future cutting-edge optoelectronic applications.

A comprehensive Study of Juglone's Effect on Polyphenol Oxidase in Cucumber: In Vitro Experiments and Computational Docking and Dynamics Insights.

This study explores the impact of juglone on cucumber (Cucumis sativus cv. Beith Alpha), scrutinizing its effects on seed germination, growth, and the polyphenol oxidase (PPO) enzyme's activity and gene expression. Employing concentrations ranging from 0.01 to 0.5 mM, we found juglone's effects to be concentration-dependent. At lower concentrations (0.01 and 0.1 mM), juglone promoted root and shoot growth along with germination, whereas higher concentrations (0.25 and 0.5 mM) exerted inhibitory effects, delineating a threshold for its allelopathic influence. Notably, PPO activity surged, especially at 0.5 mM in roots, hinting at oxidative stress involvement. Real-time PCR unveiled that juglone modulates PPO gene expression in cotyledons, peaking at 0.1 mM and diminishing at elevated levels. Correlation analyses elucidated a positive link between juglone-induced root growth and cotyledon PPO gene expression but a negative correlation with heightened root enzyme activity. Additionally, germination percentage inversely correlated with root PPO activity, while PPO activities positively associated with dopa and catechol substrates in both roots and cotyledons. Molecular docking studies revealed juglone's selective interactions with PPO's B chain, suggesting regulatory impacts. Protein interaction assessments highlighted juglone's influence on amino acid metabolism, and molecular dynamics indicated juglone's stronger, more stable binding to PPO, inferring potential alterations in enzyme function and stability. Conclusively, our findings elucidate juglone's dose-dependent physiological and biochemical shifts in cucumber plants, offering insights into its role in plant growth, stress response, and metabolic modulation.

Insights into structural vaccinology harnessed for universal coronavirus vaccine development.

Structural vaccinology is pivotal in expediting vaccine design through high-throughput screening of immunogenic antigens. Leveraging the structural and functional characteristics of antigens and immune cell receptors, this approach employs protein structural comparison to identify conserved patterns in key pathogenic components. Molecular modeling techniques, including homology modeling and molecular docking, analyze specific three-dimensional (3D) structures and protein interactions and offer valuable insights into the 3D interactions and binding affinity between vaccine candidates and target proteins. In this review, we delve into the utilization of various immunoinformatics and molecular modeling tools to streamline the development of broad-protective vaccines against coronavirus disease 2019 variants. Structural vaccinology significantly enhances our understanding of molecular interactions between hosts and pathogens. By accelerating the pace of developing effective and targeted vaccines, particularly against the rapidly mutating severe acute respiratory syndrome coronavirus 2 and other prevalent infectious diseases, this approach stands at the forefront of advancing immunization strategies. The combination of computational techniques and structural insights not only facilitates the identification of potential vaccine candidates but also contributes to the rational design of vaccines, fostering a more efficient and targeted approach to combatting infectious diseases.

Targeting the Coronavirus SARS‑CoV‑2’s Envelope, Nucleocapsid, and Spike/ Spike RBD Protein: Computational Insight from Multiple Bioactive Compounds as Potential Anti-Viral Drug Candidates

Global health, social, and economic systems have been seriously threatened by the coronavirus disease (COVID-19) pandemic. In addition to the increasing number of deaths, thousands of COVID-19 survivors continue to experience life-altering illness. This study aimed to evaluate multiple bioactive compounds from various indigenous medicinal plants against the structural proteins of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including the envelope, nucleocapsid, and spike/spike receptor-binding domain (RBD) proteins, in search of potential antiviral drug candidates. Computational analysis was used to screen for binding affinities and assess chemical interactions between ligands and target proteins. The findings revealed the top three potential compounds to bind to the envelope protein (cafestol, kahweol, and ledene), nucleocapsid protein (cafestol, kahweol, and thearubigin), spike protein (tannic acid, eugeniin, and kahweol), and spike RBD protein (kahweol, cafestol, and tannic acid). Moreover, the study identified four types of plants that contain potential bioactive compounds against SARS-CoV-2 structural proteins, including black tea (Camellia sinensis), clove (Syzygium aromaticum), common bean (Phaseolus vulgaris), and star anise (Illicium verum). Interestingly, kahweol exhibited possible binding activity against all four target proteins. This result suggests that bioactive compounds from the listed medicinal plants could potentially be developed into antiviral drugs against COVID-19.

Exploring synthesis, characterization, and computational insights into indacenodithiophene-based hole transporting materials for enhanced perovskite solar cell applications

Utilizing hole-transporting materials (HTMs) to extract and transport holes from perovskite materials to the electrode remains essential in most perovskite solar cell (PSC) architectures. Developing cost-effective and efficient HTMs is essential for advancing PSC technology. We have synthesized a novel HTM, TPA-IDT-TPA, which has an extended fused ring as the core moiety called indacenodithiophene (IDT) and p-methoxy triphenylamine (p-mTPA) as terminal groups. TPA-IDT-TPA exhibits appropriate frontier molecular orbital (FMO) energy levels that match perovskite materials. Density functional theory (DFT) simulations were performed to comprehend the electronic, excited-state, and charge transport properties. The DFT results indicate that the extended π-conjugation, rigidity, and the central core ring of the HTM enhanced the π-π stacking, contributing to efficient charge transport. The PSC constructed with TPA-IDT-TPA achieves a device efficiency of 8.34%, with high values of JSC and VOC, which can be further enhanced through molecular optimization.

Computational insights into solvent polarity associated excited state behaviour for 2-(1H-benzoimidazol-2-yl)−5-diethylamino-phenyl fluorophore

Inspired by the mesmerising charm emanating from the precisely controlled attributes displayed by 2-(1H-benzoimidazol-2-yl)−5-diethylamino-phenyl (HDP) and its derivatives in the domains of photochemistry and photobiology, our present undertaking predominantly focuses on exploring the complexities of light-triggered excited state reactions for HDP fluorophore dissolved in solvents with diverse levels of polarity. Initially, we performed molecular structure optimisation at various stages of the proton transfer process and collected data on bond length, bond angle, and core-valence bifurcation (CVB) index for the molecular framework. Subsequently, infrared (IR) vibrational spectra were analysed to evaluate the reinforcement of hydrogen bonds in different solutions. Furthermore, the investigation of orbital transitions and potential energy curves has led to the conclusion that the ESIPT process of HDP molecules is most likely to occur in nonpolar ccl4 solution, followed by chloroform solution; acetonitrile ranks last. In essence, the nonpolar aprotic solvents are more conducive to facilitating the ESIPT process. This research aims to contribute towards advancements in new luminescent materials and prove valuable in display technology and medical imaging fields while also promoting related technological development.

Computational Insights into the Intramolecular Aromatic C-C Coupling Catalyzed by the Cytochrome P450 Enzyme CYP121 from Mycobacterium tuberculosis.

CYP121 is a P450 enzyme that catalyzes the intramolecular C-C coupling of its native substrate, dicyclotyrosine (cYY). According to previous suggestions, when the cosubstrate peracetic acid was used to generate Cpd I, the substrate cYY was suggested to participate in the cleavage of the O-O bond; however, whether cYY is involved in the formation of Cpd I and how two distant aromatic carbon atoms are activated are still unclear. Here, we constructed computational models and performed QM/MM calculations to clarify the reaction mechanism. On the basis of our calculation results, cYY is not involved in the formation of Cpd I, and the C-C coupling reaction starts from hydrogen abstraction. In the second stage, the substrate should first undergo a complex conformational change, leading to two phenolic hydroxyls of cYY close to each other. In the subsequent reaction, the resultant Cpd II again abstracts a hydrogen atom from the proximal tyrosine to generate the diradical intermediate. In addition, the C-C coupling occurs in the active site, but the final aromatization may be a nonenzymatic reaction. In general, the intramolecular C-C coupling requires two basic conditions, including the active site having good flexibility and the substrate itself having a suitable and rotatable skeleton.

Computational Insights into SARS-CoV-2 Main Protease Mutations and Nirmatrelvir Efficacy: The Effects of P132H and P132H-A173V.

Nirmatrelvir, a pivotal component of the oral antiviral Paxlovid for COVID-19, targets the SARS-CoV-2 main protease (Mpro) as a covalent inhibitor. Here, we employed combined computational methods to explore how the prevalent Omicron variant mutation P132H, alone and in combination with A173V (P132H-A173V), affects nirmatrelvir's efficacy. Our findings suggest that P132H enhances the noncovalent binding affinity of Mpro for nirmatrelvir, whereas P132H-A173V diminishes it. Although both mutants catalyze the rate-limiting step more efficiently than the wild-type (WT) Mpro, P132H slows the overall rate of covalent bond formation, whereas P132H-A173V accelerates it. Comprehensive analysis of noncovalent and covalent contributions to the overall binding free energy of the covalent complex suggests that P132H likely enhances Mpro sensitivity to nirmatrelvir, while P132H-A173V may confer resistance. Per-residue decompositions of the binding and activation free energies pinpoint key residues that significantly affect the binding affinity and reaction rates, revealing how the mutations modulate these effects. The mutation-induced conformational perturbations alter drug-protein local contact intensities and the electrostatic preorganization of the protein, affecting noncovalent binding affinity and the stability of key reaction states, respectively. Our findings inform the mechanisms of nirmatrelvir resistance and sensitivity, facilitating improved drug design and the detection of resistant strains.

Structural and computational insights into the substrate specificity of acyltransferase domains from modular polyketide synthases.

Polyketides are natural products synthesized by polyketide synthases (PKSs), where acyltransferase (AT) domains play a crucial role in selection of extender units. Engineering of AT domains enables the site-specific incorporation of non-natural extender units, leading to generation of novel derivatives. Here, we determined the crystal structures of AT domains from the fifth module of tylosin PKS (TylAT5) derived from Streptomyces fradiae and the eighth module of spinosad PKS (SpnAT8) derived from Saccharopolyspora spinosa, and combined them with molecular dynamics simulations and enzyme kinetic studies to elucidate the molecular basis of substrate selection. The ethylmalonyl-CoA-specific conserved motif TAGH of TylAT5 and the MMCoA-specific conserved motif YASH of SpnAT8 were identified within the substrate-binding pocket, and several key residues close to the substrate acyl moiety were located. Through site-directed mutagenesis of four residues near the active site, we successfully reprogrammed the specificity of these two AT domains toward malonyl-CoA. Mutations in TylAT5 enhanced its catalytic activity 2.6-fold toward malonyl-CoA, and mutations in SpnAT8 eliminated the substrate promiscuity. These results extend our understanding of AT substrate specificity and would benefit the engineering of PKSs.

Computational Insights into Amide Bond Formation Catalyzed by the Condensation Domain of Nonribosomal Peptide Synthetases.

Nonribosomal peptide synthetases (NRPSs) are important enzymes that synthesize an array of nongenetically encoded peptides. The latter have diverse physicochemical properties and roles. NRPSs are modular enzymes in which, for example, the condensation (C-) domain catalyzes the formation of amide bonds. The NRPS tyrocidine synthetase from Brevibacillus brevis is responsible for synthesizing the cyclic-peptide antibiotic tyrocidine. The first step is formation of an amide bond between a proline and phenylalanine which is catalyzed by a C-domain. In this study, a multiscale computational approach (molecular dynamics and QM/MM) has been used to investigate substrate binding and catalytic mechanism of the C-domain of tyrocidine synthetase. Overall, the mechanism is found to proceed through three exergonic steps in which an active site Histidine, His222, acts as a base and acid. First, His222 acts as a base to facilitate nucleophilic attack of the prolyl nitrogen at the phenylalanyl's carbonyl carbon. This is also the rate-limiting step with a free energy barrier of 38.8 kJ mol-1. The second step is collapse of the resulting tetrahedral intermediate with cleavage of the S-C bond between the phenylalanyl and its Ppant arm, along with formation of the above amide bond. Meanwhile, the now protonated His222 imidazole has rotated toward the newly formed thiolate of the Ppant arm. In the final step, His222 acts as an acid, protonating the thiolate and regenerating a neutral His222. The overall mechanism is found to be exergonic with the final product complex being 46.3 kJ mol-1 lower in energy than the initial reactant complex.

Synthesis and evaluation of pyridine-thiophene clubbed pyrazoline hybrids as potential antimicrobial and antimycobacterial agents: experimental and computational insights

Synthesis and evaluation of pyridine-thiophene clubbed pyrazoline hybrids as potential antimicrobial and antimycobacterial agents: experimental and computational insights

Computational insights into flame development and emission formation in an ammonia engine with hydrogen-assisted pre-chamber turbulent jet ignition

Ammonia, as a promising green fuel for achieving carbon neutrality and zero-carbon emissions, encounters obstacles in practical engine applications due to its intrinsic combustion properties like low burning velocity and high autoignition temperature. Hydrogen-assisted pre-chamber turbulent jet ignition (TJI) technology has recently demonstrated great potential in extending the lean limits and enhancing the stability of ammonia combustion. As such, this study conducts a comprehensive analysis on the flame development and emission formation processes under the active pre-chamber TJI mode fueled with ammonia and hydrogen using computational fluid dynamics (CFD) modeling integrated with detailed chemical kinetics, particularly focusing on the effects of hydrogen energy ratio and spark timing. It is found that the active ammonia-hydrogen TJI engine is typically characterized by four primary physical processes involving H2 mixture preparation in the pre-chamber, flame kernel formation and development within the pre-chamber, the formation and ejection of hot jet across the orifices, and the turbulent flame initiation and propagation in the main chamber. Hydrogen injection holds a scavenging effect on the residuals in the pre-chamber while forms fuel stratification near the spark plug, enhancing the ignition stability. Besides, the current combustion mode is commonly characterized by two-stage heat release in the main chamber, but exhibits a three-stage heat release as increasing the premixed H2 ratio. The first stage is dominated by a hot jet flame, the second stage is characterized by turbulent flame propagation or autoignition, and the third stage is induced by a secondary jet ejected from the pre-chamber, which becomes more prominent as the H2 ratio increases. Hydrogen blending could not only facilitate the turbulent flame propagation of NH3-air mixture in the main chamber but also enhance the initiation of flame kernel in the pre-chamber, thereby promoting the overall combustion process and potentially improving the thermal efficiency. The N2O emission is produced in two distinct stages, wherein N2O is generated and undergoes conversion during the main combustion phase, while unburned crevice gases mix with burned gases and convert into N2O during the expansion stroke. Increasing the premixed hydrogen ratio leads to an increased in-cylinder temperature, which in turn facilitates a reduction in N2O emissions and mitigates unburned ammonia. Furthermore, optimization of the spark timing is required after implementing the hydrogen addition into the intake manifold to achieve desirable combustion phasing and further improve the thermal efficiency. Finally, a novel combustion concept, denoted as TJI assisted compression ignition mode, is proposed for achieving high thermal efficiency in ammonia engines via adopting high compression ratio and premixed ammonia-hydrogen charge under the TJI strategy.

Sulfonamide-chalcone hybrid compound suppresses cellular adhesion and migration: Experimental and computational insight

In the present study, the effect of sulfonamide-chalcone 185 (SSC185) was investigated against B16–F10 metastatic melanoma cells aggressive actions, besides migration and adhesion processes, by in silico and in vitro assays. In silico studies were used to characterize the pharmacokinetic profile and possible targets of SSC185, using the pkCSM web server, and docking simulations with AutoDock Tools. Furthermore, the antimetastatic effect of SSC185 was investigated by in vitro experiments using MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide), colony, scratch, and cell adhesion assays, and atomic force microscopy (AFM). The molecular docking results show better affinity of SSC185 with the metalloproteinases-2 (MMP-2) and α5β1 integrin. SSC185 effectively restricts the formation of colonies, migration, and adhesion of B16–F10 metastatic melanoma cells. Through the AFM images changes in cells morphology was identified, with a decrease in the filopodia and increase in the average cellular roughness. The results obtained demonstrate the potential of this molecule in inhibit the primordial steps for metastasis, which is responsible for a worse prognosis of late stage cancer, being the main cause of morbidity among cancer patients.

Nanobody engineering: computational modelling and design for biomedical and therapeutic applications.

Nanobodies, the smallest functional antibody fragment derived from camelid heavy-chain-only antibodies, have emerged as powerful tools for diverse biomedical applications. In this comprehensive review, we discuss the structural characteristics, functional properties, and computational approaches driving the design and optimisation of synthetic nanobodies. We explore their unique antigen-binding domains, highlighting the critical role of complementarity-determining regions in target recognition and specificity. This review further underscores the advantages of nanobodies over conventional antibodies from a biosynthesis perspective, including their small size, stability, and solubility, which make them ideal candidates for economical antigen capture in diagnostics, therapeutics, and biosensing. We discuss the recent advancements in computational methods for nanobody modelling, epitope prediction, and affinity maturation, shedding light on their intricate antigen-binding mechanisms and conformational dynamics. Finally, we examine a direct example of how computational design strategies were implemented for improving a nanobody-based immunosensor, known as a Quenchbody. Through combining experimental findings and computational insights, this review elucidates the transformative impact of nanobodies in biotechnology and biomedical research, offering a roadmap for future advancements and applications in healthcare and diagnostics.

Investigation of Enantioselectivity Using TADDOL Derivatives as Chiral Ligands in Asymmetric Cyanation Reactions.

This study investigates the enantioselectivity challenges of asymmetric cyanation reactions using TADDOL derivatives as chiral ligands, specifically focusing on the cyanosilylation of aldehydes and the cyanation of imines. Despite extensive optimization efforts, the highest achieved ee was only modest, peaking at 71% for the cyanosilylation reaction, while the cyanation of imines consistently resulted in racemic mixtures. Our comprehensive analysis, supported by experimental data and computational modeling, reveals significant barriers to enhancing the enantioselectivity. The results highlight a complex interplay between ligand structure and reaction conditions, demonstrating that even promising ligands such as TADDOL derivatives face substantial challenges in these reaction types. This study underscores the importance of understanding the mechanistic details through computational insights to guide future improvements in asymmetric catalysis.

"Modeling Diffusive Search by Non-Adaptive Sperm: Empirical and Computational Insights".

During fertilization, mammalian sperm undergo a winnowing selection process that reduces the candidate pool of potential fertilizers from ~106-1011 cells to 101-102 cells (depending on the species). Classical sperm competition theory addresses the positive or 'stabilizing' selection that acts on sperm phenotypes within populations of organisms but does not strictly address the developmental consequences of sperm traits among individual organisms that are under purifying selection during fertilization. It is the latter that is of utmost concern for improving assisted reproductive technologies (ART) because 'low fitness' sperm may be inadvertently used for fertilization during interventions that rely heavily on artificial sperm selection, such as intracytoplasmic sperm injection (ICSI). Importantly, some form of sperm selection is used in nearly all forms of ART (e.g., differential centrifugation, swim-up, or hyaluronan binding assays, etc.). To date, there is no unifying quantitative framework (i.e., theory of sperm selection) that synthesizes causal mechanisms of selection with observed natural variation in individual sperm traits. In this report, we reframe the physiological function of sperm as a collective diffusive search process and develop multi-scale computational models to explore the causal dynamics that constrain sperm 'fitness' during fertilization. Several experimentally useful concepts are developed, including a probabilistic measure of sperm 'fitness' as well as an information theoretic measure of the magnitude of sperm selection, each of which are assessed under systematic increases in microenvironmental selective pressure acting on sperm motility patterns.

Synthesis, Characterization, and Evaluation of Tetrazole Derivatives with Pyrrole‐2,5‐Dione Moieties as Urease Inhibitors: Exploring Structure‐Activity Relationships and Computational Insights

AbstractA series of Tetrazole derivatives containing pyrrole‐2,5‐dione groups (5 a–e) were synthesized and comprehensively characterized using HRMS, FT‐IR, and 1H−, 13C‐NMR spectroscopic techniques. These compounds were evaluated for their ability to inhibit urease activity in vitro, demonstrating remarkable inhibitory potential with IC50 values ranging from 4.325±1 to 18.28±1 μM, surpassing the standard thiourea (IC50=17.386±1 μM). Notably, compounds 5 b (IC50=4.325±1 μM), 5 e (IC50=7.411±1 μM), 5 c (IC50=9.313±1 μM), and 5 a (IC50=10.46±1 μM) exhibited notably higher activity compared to the standard thiourea. In our exploration of the structure‐activity relationship (SAR), we investigated the impact of differently substituted aryl rings on inhibitory potential. Our results highlight the crucial role of substituent positioning on the aryl ring, independent of the nature of the substituents. Additionally, computational studies were conducted on all compounds, supporting our experimental findings. Molecular docking simulations revealed a strong correlation between biological evaluation results and computational predictions, affirming the promising inhibitory activity of the compounds.

Enhanced detection of glucose with carbon quantum dot-modified copper oxide: Computational insight and machine learning modeling of electrochemical sensing

Poor conductivity and surface passivation pose critical challenges in metal oxide structures during their application for non-enzymatic oxidation. To address this, we systematically employed in-situ deposition of carbon-quantum dots (C-dots) over copper oxide (CuO), enhancing its electrocatalytic properties for direct non-enzymatic glucose oxidation in alkaline media. The process involved the systematic deposition of varying wt.% of C-dots onto the CuO nanostructure. The electrode’s sensing capability was assessed through CV, DPV, and amperometric measurements, evaluating its suitability in high (0.1 to 0.85 mM) and low glucose concentration levels (15 to 225 nM) with a representative LOD of 1.4 nM (17142.86 µA mM−1 cm−2). Additionally, the CuO-Cdot-16.6 protective coating allowed for long-term working capability, with chronoamperometric measurement confirming a 99 % current retention ability compared to pristine CuO’s 39 % retention during 3500 s of continuous measurement. DFT calculations further confirmed the efficacy of CuO substrate as a scaffold for glucose adsorption. The stable CuO-glucose complex formed due to energetically favorable conditions further strengthens its potential as a sensor. Successful recoveries of spiked glucose serum samples validated the sensor’s practical usage in complex matrices. Moreover, Machine learning was also adopted to validate the accuracy of glucose detection, where artificial neural network (ANN) model emerged as a suitable model to interpret the DPV derived data relationships, adding in sensor working capability and promising its future application in precision/intelligent healthcare.

Computational Insights into the Resistance of the Gatekeeper Mutation V564F of FGFR2 Against Pemigatinib

The fibroblast growth factor receptor 2 (FGFR2), a transmembrane receptor tyrosine kinase, is implicated in a plethora of human cancers, including intrahepatic cholangiocarcinomas. The clinically relevant V564F gatekeeper mutation conferred resistance to the current FGFR2 drug-Pemigatinib. Here, we conducted integrated computational methods to compare the protein-ligand interactions between the FGFR2 kinase domain in the wild-type and V564F mutant states and Pemigatinib. Based on molecular docking, molecular dynamic simulations and hydrogen bond analysis, we revealed that the reduced hydrogen bonding interactions in the V564F mutant were the key factor to decrease the binding affinity of Pemigatinib to the FGFR2. The per-residue free energy decomposition analysis implemented by the molecular mechanics/generalized born surface area method revealed the reduced contributions from the key residues G488, F564 and A567 located at the kinase hinge domain were responsible for the decreased binding affinity in the V564F mutant. This study elucidated the molecular mechanism for the resistance of Pemigatinib in FGFR2 triggered by the V564F mutation and may provide insights for future drug development and optimization.