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        <title>Frontiers in Chemistry | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/chemistry</link>
        <description>RSS Feed for Frontiers in Chemistry | New and Recent Articles</description>
        <language>en-us</language>
        <generator>Frontiers Feed Generator,version:1</generator>
        <pubDate>2026-08-19T09:40:19.430+00:00</pubDate>
        <ttl>60</ttl>
        <item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1830739</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1830739</link>
        <title><![CDATA[An integrative approach for rapid authentication of different parts of Camellia petelotii (Merr.) Sealy: combining ATR-FTIR spectroscopy with conventional chemometric analysis and a convolutional neural network]]></title>
        <pubdate>2026-08-19T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Chen Jingying</author><author>Zhao Yunqing</author><author>Zhang Wujun</author><author>Huang Yingzhen</author><author>Wan Yin Tew</author><author>Jingsong Liu</author><author>Liyun Ouyang</author><author>Qiyue Qiu</author><author>Chen Ying</author><author>Tiem Leong Yoon</author><author>Mun Fei Yam</author>
        <description><![CDATA[IntroductionThe flower of Camellia petelotii (Merr.) Sealy is highly valued in Traditional Chinese Medicine, making it susceptible to adulteration with its leaves or other lower-cost adulterants. This study aims to develop a robust authentication approach to distinguish different plant parts and identify adulterated mixtures using ATR-FTIR spectroscopy integrated with chemometrics and artificial intelligence.MethodsThe flowers, leaves, seeds, and mixed samples of C. petelotii were subjected to ATR-FTIR spectroscopy. The spectral data of pure plant parts were analyzed with Principal Component Analysis (PCA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA). In the machine learning phase, a Convolutional Neural Network (CNN) model was trained on spectra of pure plant parts and laboratory-prepared mixed samples. The Synthetic Minority Oversampling Technique (SMOTE) was employed to address class imbalance and sample scarcity. Model robustness was validated via Repeated Random Subsampling Validation (RRSV).ResultsATR-FTIR analysis clearly differentiated the leaves from other plant parts, revealing distinct spectral characteristics. The PCA and OPLS-DA effectively classified the three distinct plant parts with high accuracy, sensitivity, and specificity scores exceeding 95%. The OPLS-DA model achieved high internal validity (R2X, R2Y, and Q2Y ≥ 0.738). In the machine learning workflow, the baseline CNN models suffered from minority-class collapse. Implementing SMOTE effectively resolved this issue. In multi-class configurations, the SMOTE-trained models showed high predictive precision and achieved high F1-scores for Seed (0.846) and Flower (0.931) classes, but moderate performance on Mix (0.593) and Leaf (0.657) classes. The binary classification model resolved the ambiguity, increasing the average F1-scores of the Mix and Leaf classes to 0.674 and 0.932, respectively. When validated against non-augmented data across both multi-class and binary-class configurations, SMOTE-trained models showed high stability for pure plant parts but remained sensitive to the Mix class across both multi-class (F1-score: 0.361) and binary-class (F1-score: 0.249) configurations.ConclusionWhile AI-driven data augmentation mitigates sample-size constraints, classification performance remains heavily influenced by spectral characteristics. The binary classification architecture offered distinct advantages when analyzing samples with heterogeneous spectral complexity. This integrated approach may serve as a reference for quality control and authentication of botanical products.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1849931</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1849931</link>
        <title><![CDATA[Advances in nanomaterial-enhanced immunosensors for ultra-sensitive tumor marker detection: Enabling early cancer diagnostics]]></title>
        <pubdate>2026-08-18T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Shengbo Jin</author><author>Jun Yu</author><author>Yuxin Jiang</author><author>Mingzhu Li</author>
        <description><![CDATA[Tumor markers are critical for early cancer diagnosis and directly influence treatment outcomes and patient survival. Although enzyme-linked immunosorbent assay (ELISA) and radioimmunoassay (RIA) show satisfactory selectivity in clinical applications, their limited sensitivity for low-abundance biomarkers, relatively long assay time, and reproducibility issues have promoted the development of advanced immunosensing platforms. Recent progress in nanomaterial synthesis has improved immunosensor performance by enhancing antibody immobilization, electron transfer, catalytic activity, signal amplification, photoelectric conversion, and luminescence efficiency. This review summarizes nanomaterial-enhanced immunosensors for clinically relevant tumor biomarkers, including carcinoembryonic antigen (CEA), prostate-specific antigen (PSA), cancer antigen 153 (CA153), alpha-fetoprotein (AFP), cancer antigen 125 (CA125), cancer antigen 199 (CA199), and human epidermal growth factor receptor 2 (HER2). To reduce repetition and emphasize analytical performance rather than nominal material categories, this review adopts a platform-centered and mechanism-oriented framework. Electrochemical, photoelectrochemical, electrochemiluminescent, and chemiluminescent immunosensors are compared as major signal transduction platforms, with representative nanomaterials discussed according to their roles in antibody immobilization, electron-transfer acceleration, catalytic amplification, charge separation, luminescence regulation, magnetic enrichment, and interface stabilization. In addition, cross-platform comparisons of sensitivity, detection limit, specificity, recovery, assay time, storage stability, cost, scalability, and clinical applicability are provided to clarify the translational value of different sensing strategies. This comparative analysis highlights that clinical applicability is primarily determined by integrated platform performance, including sensitivity, stability, manufacturability, and compatibility with point-of-care testing, rather than by the use of a specific nanomaterial alone.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1959068</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1959068</link>
        <title><![CDATA[Retraction: Synthesis of Al-based metal-organic framework in water with caffeic acid ligand and NaOH as linker sources with highly efficient anticancer treatment]]></title>
        <pubdate>2026-08-18T00:00:00Z</pubdate>
        <category>Retraction</category>
        
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1886764</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1886764</link>
        <title><![CDATA[Flexible molecular chameleons: structural adaptability and therapeutic applications]]></title>
        <pubdate>2026-08-18T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Debosreeta Bose</author><author>Purvee Bhardwaj</author><author>Agnishwar Girigoswami</author>
        <description><![CDATA[There has been a growing focus on ‘molecular chameleons’ possessing structural flexibility; compounds that can dynamically adjust their conformations depending on the characteristics of the medium to either conceal or reveal polar parts in aqueous/lipidic environments. Drug discovery has shifted in the past few decades toward more complex molecules, such as cyclic and macrocyclic peptides, as well as PROteolysis-TArgeting Chimeras (PROTACs). These large macromolecules are intended to balance cell permeability, aqueous solubility, and strong target binding capacity for effective pharmacokinetics; though they are more difficult to design than conventional small drug molecules. Molecular chameleons are useful for this task because of their capacity to adapt to various environments. The science underlying the structural flexibility of molecular chameleons, their growing significance, role in therapeutics and design strategies using contemporary tools are all covered in this review.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1913741</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1913741</link>
        <title><![CDATA[Resolving conformational polymorphism in disulfide-rich peptide drugs]]></title>
        <pubdate>2026-08-17T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Shaozhou Zhu</author><author>Yifeng Ge</author><author>Haiwei Huang</author><author>Mingzhe Xu</author>
        <description><![CDATA[Disulfide-rich peptide therapeutics often exhibit compact cystine knot-like architectures that endow them with high conformational rigidity, proteolytic stability, and target specificity. Yet their intrinsic polymorphism and structural heterogeneity are difficult to resolve with conventional analytical methods, which lack sufficient power to distinguish subtle structural variants within highly constrained peptide frameworks. Here, cyclic ion mobility-mass spectrometry (cIM-MS), combined with accelerated thermal stress testing, was applied to a manufacturing batch of ziconotide and linaclotide under native and thermally stressed conditions. Pronounced conformational heterogeneity was observed for both drugs even under native conditions. Upon thermal stress, notable degradation and structural reorganization occurred, revealing conformational changes that were not adequately captured by conventional methods. The high-resolution separation achieved by cIM-MS enabled detailed mapping of coexisting conformers and their stress-induced transitions. These results demonstrate that cIM-MS provides a spatially resolved analytical platform for interrogating higher-order structural heterogeneity in disulfide-rich peptide therapeutics, extending the capabilities of conventional mass spectrometry and offering a generalizable approach for structural characterization and quality assessment.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1959100</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1959100</link>
        <title><![CDATA[Retraction: Synthesis and characterization of an Fe-MOF@Fe3O4 nanocatalyst and its application as an organic nanocatalyst for one-pot synthesis of dihydropyrano[2,3-c]chromenes]]></title>
        <pubdate>2026-08-17T00:00:00Z</pubdate>
        <category>Retraction</category>
        
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1913683</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1913683</link>
        <title><![CDATA[Ion intercalation, redox, and interfacial mechanisms of MXene-based negative-electrode systems for rechargeable batteries]]></title>
        <pubdate>2026-08-14T00:00:00Z</pubdate>
        <category>Mini Review</category>
        <author>Bangsheng Yin</author><author>Shengjun Ji</author><author>Jiawen Tian</author><author>Haotian Wu</author><author>Wenyue Si</author>
        <description><![CDATA[MXenes combine metallic conductivity, redox-active transition-metal layers, and chemically tunable surfaces, making them attractive components of negative-electrode systems for lithium-, sodium-, potassium-, zinc-, and multivalent-ion batteries. However, interpreting MXene-based negative-electrode systems only by reversible capacity obscures the coupled processes that determine their electrochemical behavior. This mini review reframes MXene-based negative-electrode systems around the coupled logic of ion entry, charge compensation, and structural evolution. We discuss how interlayer galleries, surface terminations, confined water or solvent molecules, and metal-center redox cooperate or compete during charge storage. Particular emphasis is placed on the distinction between true intercalation, pseudo-intercalation, surface pseudocapacitance, partner-phase conversion/alloying in MXene-containing hybrid anodes, and electrolyte-regulated desolvation. Recent examples across alkali, aqueous zinc, and multivalent systems show that high-rate performance is obtained when ion access, electron transport, and lattice breathing are balanced rather than maximized independently. We highlight operando and multiscale measurements needed to connect local coordination changes with electrode-level kinetics, and we propose design principles for MXene-based negative-electrode systems that preserve redox accessibility while limiting restacking, oxidation, and parasitic interfacial reactions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1890266</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1890266</link>
        <title><![CDATA[Multidimensional characterization of heterogeneity in pesticide co-exposure patterns]]></title>
        <pubdate>2026-08-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Han Su</author><author>Lezhen Zhang</author><author>Wenjun Tian</author><author>Bingru Lu</author><author>Xiangrui Guo</author><author>Yiqing Liu</author>
        <description><![CDATA[ObjectivesThis study analyzed clinical data from 1641 pesticide-exposed patients screened for a total of 159 pesticide compounds admitted to Shandong First Medical University Affiliated Provincial Hospital from 1 January 2023 to 31 December 2024, aiming to elucidate the multidimensional heterogeneity of pesticide co-exposure patterns.MethodsClinical information and biological samples were collected from all participants. Pesticide detection was performed using Agilent 7890B-7250 Q-TOF/MS and AB SCIEX Triple Quad 4500MD mass spectrometry systems. Seasonal, gender-specific, and age-group variations in pesticide exposure were assessed, and a co-occurrence network was constructed to evaluate concurrent exposure patterns and concentration distributions.ResultsHerbicides exhibited the highest exposure prevalence within their respective tested sub-cohorts. Specifically, glyphosate showed a targeted detection frequency of 49.32% (144/292) among the screened individuals. Concentration peaks for glyphosate and paraquat occurred between July and September, with median levels reaching 3.42 and 3.15 log10 μg/L, respectively. Pesticide exposure displayed a bimodal age distribution, with a secondary peak among individuals aged 15–20 years and a primary peak in those aged 55–60 years. In the 40–55 age group, male exposure prevalence was significantly higher than female (male-to-female ratio: 2.8:1). Network analysis identified 38 significant co-occurrence patterns (r > 0.5, P < 0.0016), with the most prominent involving glyphosate, imidacloprid, and metolachlor. Log-transformed pesticide concentrations revealed marked differences in variability across chemical classes. Herbicides (e.g., glyphosate, paraquat) and certain broad-spectrum insecticides (e.g., chlorfenapyr) showed highly right-skewed concentration distributions, whereas tebuconazole and cinosulfuron exhibited relatively concentrated profiles. Thiamethoxam demonstrated substantially greater concentration variability compared to other compounds, indicating pronounced heterogeneity in its application patterns. Collectively, these findings highlight complex heterogeneity in pesticide exposure across temporal, demographic, and chemical dimensions.ConclusionThis study reveals distinct multidimensional heterogeneity in pesticide exposure, providing critical evidence for developing targeted intervention strategies. Tailored protective measures based on seasonal trends, gender-age subgroups, and prevalent co-exposure patterns may more effectively mitigate pesticide-related risks among agricultural populations.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1874752</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1874752</link>
        <title><![CDATA[Computational perspective on structure, energetics, and bonding of FeC2O isomers with astrochemical significance]]></title>
        <pubdate>2026-08-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Abhirami R. J.</author><author>Senthur Pandi Rajasabai</author>
        <description><![CDATA[Iron in its elemental form has rarely been detected in the interstellar medium despite being the most abundant refractory element. The presence of iron oxides in the interstellar medium and the recent discovery of FeC in the circumstellar envelope of IRC+10,216 suggest iron-carbon-oxygen molecules as potential interstellar species. In light of this possibility, the potential energy surface of FeC2O has been investigated computationally using different levels of density functional theory calculations, yielding fourteen, seven, and twenty isomers across the quintet, triplet, and singlet electronic states, respectively. Within the examined DFT frameworks, the lowest energy isomer of FeC2O is in the quintet electronic state with a linear structure. Single-point (U)CCSD(T) calculations with T1 diagnostics reveal considerable multireference character in certain geometries. CASSCF optimizations are performed on quintet state geometries to account for the multireference character. Various computational tools, such as adaptive natural density partitioning (AdNDP) analysis, molecular orbital (MO) analysis, and Wiberg Bond Indices (WBI), are employed to elucidate the bonding characteristics of the global minimum geometry. The spectroscopic parameters in both infrared and microwave domains have been successfully computed. The total and the partial density of states are plotted to evaluate how different atoms contribute to the electronic structure. The structural, energetic, and spectroscopic parameters presented in this work have significant implications for future astronomical research.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1908317</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1908317</link>
        <title><![CDATA[Degree-based topological indices and their graph energies in the QSPR analysis and ranking of UV-filter compounds]]></title>
        <pubdate>2026-08-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Merin Manuel</author><author>Parthiban Angamuthu</author>
        <description><![CDATA[Ultraviolet (UV) filters are essential ingredients in sunscreens and personal care products, and understanding their physicochemical properties is important for evaluating their performance and applicability. In this study, selected degree-based topological indices and their corresponding graph-energy descriptors were investigated as molecular descriptors for a set of commercially relevant UV-filter compounds. Quantitative structure-property relationship (QSPR) models were developed for molecular weight, complexity, XlogP, water solubility, topological polar surface area, refractivity, and polarizability. The results indicate that both classes of descriptors exhibit strong predictive potential for molecular weight, complexity, refractivity, and polarizability, while weaker relationships were observed for XlogP, water solubility, and polar surface area. The developed models were evaluated using regression analysis, leave-one-out cross-validation, and Monte Carlo validation, which produced consistent results for the well-performing properties. Furthermore, TOPSIS, SAW, and VIKOR methods were employed to rank the investigated UV-filters based on their physicochemical characteristics. The resulting rankings showed strong agreement, identifying Diethylhexyl Butamido Triazone, Ethylhexyl Triazone, and Bisoctrizole as the most promising candidates. The findings highlight the potential of degree-based topological descriptors and their graph energies for QSPR modeling, while the MCDM framework provides a systematic approach for the comparative evaluation and prioritization of UV-filter compounds.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1959085</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1959085</link>
        <title><![CDATA[Retraction: Microwave-assisted synthetic method of novel Bi2O3 nanostructure and its application as a high-performance nano-catalyst in preparing benzylidene barbituric acid derivatives]]></title>
        <pubdate>2026-08-14T00:00:00Z</pubdate>
        <category>Retraction</category>
        
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1862613</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1862613</link>
        <title><![CDATA[A structure and function-based complete mutational map of human hemoglobin using AI]]></title>
        <pubdate>2026-08-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Franco Salvatore</author><author>Franco G. Brunello</author><author>Claudio D. Schuster</author><author>Marcelo A. Martí</author>
        <description><![CDATA[Hemoglobin (Hb), a well-characterized protein central to oxygen transport and molecular medicine, serves as a model for studying how sequence variations influence protein structure and function. Its precise activity depends on tightly regulated structural dynamics, which can be disrupted by mutations that give rise to structural hemoglobinopathies, including sickle cell disease, unstable hemoglobins, methemoglobins, and hemoglobins with altered oxygen affinity, each associated with distinct functional and clinical consequences. Among genetic variants, missense mutations are the most widely studied in clinical settings. Accurately predicting their clinical impact remains challenging, requiring integration of evolutionary, biochemical, and structural data. While broad deep learning models like AlphaMissense show promise, they often lack interpretability and protein-specific precision. This motivates the development of focused models that leverage detailed knowledge of individual proteins, like hemoglobin, to improve both predictive power and mechanistic understanding. In this work, we conducted a comprehensive analysis of all known and potential human adult hemoglobin (HbA) variants, guided by the hypothesis that a deep understanding of the sequence-structure-function relationship in Hb can yield interpretable and predictive insights into the functional and clinical consequences of single amino acid substitutions. We curated an updated dataset of HbA variants annotated with their clinical classifications, Benign, Pathogenic, or of Uncertain Significance (VUS), and systematically mapped each to a range of features, including structural location and classification, predicted impact on folding stability, and evolutionary conservation. Using this data, we developed a pathogenicity prediction model and benchmarked it against AlphaMissense, demonstrating strong and complementary performance. Additionally, we generated a complete mutational landscape of all possible single amino acid substitutions (SAS) in HbA, providing a resource for future clinical interpretation. Our findings provide insight into the molecular basis for variant effects in HbA and highlight the utility of combining structure-informed features with Machine Learning (ML) for variant interpretation. Moreover, our results offer a framework for evaluating the portability and interpretability of variant effect predictors across structurally dynamic systems, with implications in the improvement of variant classification in other protein families.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1959084</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1959084</link>
        <title><![CDATA[Retraction: Synthesis and characterization of new 1,4-dihydropyran derivatives by novel Ta-MOF nanostructures as reusable nanocatalyst with antimicrobial activity]]></title>
        <pubdate>2026-08-13T00:00:00Z</pubdate>
        <category>Retraction</category>
        
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1924748</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1924748</link>
        <title><![CDATA[Recent advances in photodynamic therapy systems based on pillar[n]arene host–guest chemistry]]></title>
        <pubdate>2026-08-12T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Fuqiang Zhao</author><author>Zhiying Zhu</author><author>Liang Li</author>
        <description><![CDATA[Photodynamic therapy (PDT) is a minimally invasive and low-toxicity strategy for tumors and bacterial infections. However, conventional small-molecule photosensitizers have poor water solubility, severe aggregation-caused quenching and weak tumor targeting, restricting their clinical translation. Macrocyclic host-guest supramolecular assembly improves the performance of photosensitizers via reversible noncovalent recognition. Pillar[n]arenes feature symmetric electron-rich cavities, abundant modifiable sites and wide guest compatibility, showing outstanding advantages over cyclodextrins, calixarenes and cucurbiturils for responsive photosensitizing platforms. This review summarizes recent advances of pillar[n]arene host-guest systems in PDT. We introduce the structural and recognition features of pillar[n]arenes, classify the fabrication of pillar[n]arene-photosensitizer complexes, and interpret how host-guest inclusion alleviates fluorescence quenching, elevates singlet oxygen yield and triggers tumor microenvironment-responsive drug release. Their applications in anti-tumor PDT, antibacterial photodynamic disinfection and imaging-guided therapy are outlined. We also discuss translational obstacles including insufficient biocompatibility and limited deep-tissue penetration, and propose future directions involving targeted functionalization, multi-modal synergy and degradable macrocyclic skeletons. This work clarifies the structure-activity relationship of pillar[n]arene-based PDT systems and offers guidelines for designing high-performance supramolecular theranostic agents.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1893737</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1893737</link>
        <title><![CDATA[Recent advances in synthesis and medicinal chemistry of pyrrolodiazepines]]></title>
        <pubdate>2026-08-12T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Mengyang Zhou</author><author>Shutao Wang</author>
        <description><![CDATA[Nitrogen-containing heterocyclic compounds represent fundamental structural elements in contemporary medicinal chemistry. Pyrrolodiazepines, which result from the fusion of pyrrole and diazepine rings, integrate the beneficial properties of both parent structures and have emerged as a significant area of research in synthetic chemistry and pharmaceutical development in recent years. This review provides a systematic overview of the synthetic methodologies for pyrrolodiazepine derivatives that have been developed recently, encompassing transition-metal catalysis, cascade cyclization, multicomponent reactions, photoredox catalysis, base-mediated cyclization, and environmentally friendly synthesis approaches. The advantages and limitations of each method are critically evaluated. Furthermore, the biological activities of pyrrolodiazepines are extensively reviewed, addressing their antitumor, antibacterial, antiviral, central nervous system regulatory, metabolic, and cardiovascular effects, along with corresponding structure–activity relationship analyses. Finally, the review identifies the current challenges in the synthesis and application of pyrrolodiazepines and explores potential future development directions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1869559</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1869559</link>
        <title><![CDATA[MetaCYP: a unified framework for prediction of cytochrome P450 metabolic sites and reaction types via multimodal deep learning]]></title>
        <pubdate>2026-08-12T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Jiamin Chang</author><author>Xuhai Huang</author><author>Boxue Tian</author>
        <description><![CDATA[IntroductionCytochrome P450 (CYP) enzymes are the predominant drug-metabolizing proteins in humans, collectively governing the structural transformation of drugs and xenobiotics while directly shaping their pharmacological activity and toxicological profiles. Accurate prediction of CYP–substrate reaction sites and reaction types is therefore central to drug discovery and metabolic risk assessment. Existing computational models, however, largely depend on intrinsic molecular properties or hardcoded reaction rules, constraining their generalization across CYP isoforms.MethodsHere we present MetaCYP, a multimodal deep learning framework that predicts bonds of metabolism (BoMs) and reaction types in CYP-mediated biotransformation. MetaCYP encodes CYP amino acid sequences with the protein language model ESM-2 and extracts bond-level substrate features using Uni-Mol, integrating both modalities through an attention-based cross-modal fusion mechanism that captures enzyme–substrate interactions.ResultsThis architecture enables a single unified model to resolve isoform-specific catalytic selectivity for identical substrates. MetaCYP achieves state-of-the-art performance in BoM prediction (MCC: 0.741; ROC-AUC: 0.956) and reaction type prediction (MCC: 0.796; ROC-AUC: 0.946), outperforming current benchmarks.DiscussionMetaCYP establishes a unified deep learning framework that models reaction sites and reaction types from enzyme–substrate information, offering a mechanistically grounded and interpretable tool for elucidating CYP catalytic selectivity. Its capacity to improve the accuracy of ADME property predictions, alongside its scalability across isoforms, positions it as a practical resource for early-stage drug screening, metabolic risk assessment, and rational drug design.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1876389</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1876389</link>
        <title><![CDATA[Modeling and optimization of hydrogenation for crude oil by estimating hydrogen solubility in the solvent at different temperatures]]></title>
        <pubdate>2026-08-11T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Zhongtian Zhao</author>
        <description><![CDATA[A novel approach was introduced to predict the solubility of hydrogen in Athabasca bitumen sample by leveraging a hybrid approach based on Harmony Search Algorithm (HS) and AdaBoost. The solubility of H2 in the samples is of great importance for treatment of heavy hydrocarbon in petroleum processing and can help optimize processes. In the correlation of data, pressure and temperature were used as the inputs, while the hydrogen solubility was assigned the sole response for the modeling. This approach was applied to three popular regression models: K-Nearest Neighbors (KNN), Theil-Sen, and Lasso, resulting in hybrid models named HSA-KNN, HSA-TS, and HSA-LAS, respectively. The HS algorithm is used to optimize the hyperparameters of the Adaboost and base models, and then AdaBoost is applied to enhance the performance of the base models. The HSA-KNN model achieved an R2 score of 0.96466, MSE of 6.2790E-03, and a maximum error of 1.80485E-01, while the HSA-TS model achieved an R2 score of 0.96433, MSE of 6.3994E-03, and a maximum error of 1.40763E-01. The HSA-LAS model, on the other hand, achieved an R2 score of 0.89249.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1866827</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1866827</link>
        <title><![CDATA[Direct synthesis of molecularly imprinted nanozymes with a biomimetic catalytic motif for glycosidic bond cleavage]]></title>
        <pubdate>2026-08-11T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Mohan Lakavathu</author><author>Yan Zhao</author>
        <description><![CDATA[Carbohydrates are the most abundant organic molecules on Earth and play essential roles in biology. Natural glycosidases cleave glycosidic linkages using a pair of conserved carboxylic acid residues. Here we report the direct synthesis of nanozymes that mimic glycosidases through molecular imprinting of thiosemicarbazide-derived glycan templates, prepared in one step from unprotected mono- or oligosaccharides. The thiosemicarbazide group binds strongly to a dicarboxylic acid functional monomer (FM), enabling installation of the double-acid catalytic motif into the imprinted active site. The resulting nanozymes cleave glycosidic bonds in oligo- and polysaccharides (e.g., cellobiose and cellulose) by a mechanism analogous to retaining glycosidases. Molecular imprinting also allows the active site to accommodate a single or predefined number of sugar residues, tuning both the size of the pocket and the distance between binding and catalytic groups, thereby enabling rational control of the cleavage site along the substrate.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1896796</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1896796</link>
        <title><![CDATA[QSPR modelling of PPI drugs using hybrid topological indices]]></title>
        <pubdate>2026-08-11T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>L. Monisha</author><author>R. Jayagopal</author>
        <description><![CDATA[PPIs are one of the most often prescribed drug groups for ailments involving high stomach acid production. PPIs permanently suppress the H+/K + -ATPase enzyme in gastric parietal cells, blocking acid secretion. Topological indices are quantitative analysers that are used to define the structural attributes of molecules which transmit topological information such as adjacency, branching and connectivity to numerical values. In this paper, we explore the chemical significance of degree-based hybrid topological indices for proton pump inhibitors (PPIs) and evaluate their correlation with the physicochemical properties of PPIs. Our goal is to utilize Quantitative Structure Property Relationship analysis to identify correlations between structural characteristics and physicochemical properties. This approach underscores the value of topological indices in evaluating the properties of PPIs. This analysis helps to comprehend structural activity correlations in domains such as drug design and material research by providing insights into molecular behaviour.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fchem.2026.1898133</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fchem.2026.1898133</link>
        <title><![CDATA[Sustainable thymol-based formulations with amoxicillin and Melaleuca alternifolia essential oil]]></title>
        <pubdate>2026-08-10T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Zehra Edis</author><author>Jon Zaccary Regala</author>
        <description><![CDATA[Antimicrobial resistance (AMR) against antibiotics is caused by the evolution of pathogens to endure antibiotics, rendering once powerful treatments now useless. Amoxicillin (A), a well-known antibiotic is subjected to AMR and could be more effective in combination with plant-based extracts. Tea Tree essential oil (T) and thymol (t) are known antimicrobial agents but are hampered by their lipophilicity, volatility, oxidative degradation and skin irritation. These disadvantages can be mitigated by combinations to achieve better drug delivery outcomes. Thymol, a monoterpenoid has remarkable antimicrobial activities, but several pathogens are resistant to it. T is utilized since centuries against ailments but requires nanoencapsulation due to drug-delivery problems. Formulations consisting of T, thymol, and amoxicillin (A) were investigated as possible alternatives against AMR. The best combination with highest antimicrobial properties was identified as Tt2A2, consisting of T, thymol, and A at 1:2:2 proportions, respectively. Small-sized particles of Tt2A2 were subjected to ultraviolet-visible (UV-Vis) spectrometry, Fourier transform infrared (FTIR) spectroscopy, x-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive x-ray (EDX) spectroscopy analysis. Tt2A2 was tested against ten microbial reference strains on discs, surgical sutures, cotton gauze bandages, surgical face masks, and KN95 masks by agar-disc diffusion methods. The formulations of Tt2A2 were effective against all ten reference pathogens achieving zones of inhibition (ZOI) of up to 30–35 mm. Antimicrobial activity of Tt2A2 is proportional to T concentrations and can be fine-tuned according to target pathogen and biomaterial. The Gram-positive S. pneumoniae ATCC 49619 showed high susceptibility with 33.7 mm mean ZOI and a better performance in Tt2A2a. The notorious Gram-negative pathogen P. mirabilis ATCC 29906 was inhibited with 30 mm and in average performed better in Tt2A2b with higher T concentration. The formulations exhibited potential as an antimicrobial agent on surgical sutures, masks and bandages, as well as a disinfective agent. Stability studies revealed the same inhibition zones for up to 3–6 months for all 10 reference strains. However, a steady decline to intermediate inhibitory levels by Gram-positive reference strains was observed towards 18 months of storage.]]></description>
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