ACS Omega最新文献

{"title":"Atomic Interaction-Based Prediction of Phase Formations in High-Entropy Alloys","authors":"Md Tohidul Islam,&nbsp;Stephen A. Giles,&nbsp;Debasis Sengupta,&nbsp;Krishna Rajan and Scott R. Broderick*,&nbsp;","doi":"10.1021/acsomega.5c0130410.1021/acsomega.5c01304","DOIUrl":"https://doi.org/10.1021/acsomega.5c01304https://doi.org/10.1021/acsomega.5c01304","url":null,"abstract":"<p >High-entropy alloys (HEAs) are of particular interest due to their unique combination of high strength, ductility, and fracture resistance. These properties are largely impacted by the phases and number of phases present in the alloy. Due to the enormous chemical design space, with typically five or six elements present in the alloys in addition to the various processing parameters, the prediction of the number of phases is challenging. While there have been multiple recent reports of phase predictions through data-driven models, an alternate approach is proposed and demonstrated here. In this work, phase prediction is performed using features derived from DFT-calculated pairwise interactions among constituent elements (incorporating bonding and structure) rather than relying solely on traditional elemental descriptors such as electronegativity. By focusing on atomic interaction features, our model provides a novel perspective on the phase stability in HEAs. This approach yields a predictive model for phase formation in HEAs that is comparable in accuracy to prior models while offering improved interpretability. By analyzing the contributions of various binary interactions to the prediction, the model provides insight into the atomic-scale factors influencing whether an alloy forms a single-phase solid solution (SS) or multiphase microstructure.</p>","PeriodicalId":22,"journal":{"name":"ACS Omega","volume":"10 23","pages":"24560–24575 24560–24575"},"PeriodicalIF":3.7,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsomega.5c01304","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144296453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pen-on-Paper Label-Free Surface-Enhanced Raman Scattering (SERS) Detection of Tetracycline in Milk","authors":"Alida Russo,&nbsp;Martina Piletti,&nbsp;Aidan J. Quinn and Daniela Iacopino*,&nbsp;","doi":"10.1021/acsomega.5c0163710.1021/acsomega.5c01637","DOIUrl":"https://doi.org/10.1021/acsomega.5c01637https://doi.org/10.1021/acsomega.5c01637","url":null,"abstract":"<p >Monitoring food quality requires the development of low-cost and sensitive analytical tools with label-free and point-of-site detection capabilities. Surface-enhanced Raman scattering (SERS) is a powerful analytical technique that combines fingerprint detection capabilities with high sensitivity. In this paper, we present the pen-on-paper fabrication of SERS substrates, whereby plasmonic nanoinks were written on a paper substrate and used for the detection of food contaminant residues. To construct sensitive and robust SERS sensors, four different nanoinks with different plasmonic properties were synthesized and tested on eight papers of different weights, textures, and hydrophilicities. The combination of silver nanoink and Bristol printing paper resulted in the strongest SERS substrate, which was used for crystal violet (CV) and tetracycline detection. Concentrations as low as 10^–12 M were obtained for CV and 2.5 ppm of tetracycline in milk, showing the application potential of these paper-based SERS sensors for label-free detection of residuals in complex food matrices.</p>","PeriodicalId":22,"journal":{"name":"ACS Omega","volume":"10 23","pages":"24710–24719 24710–24719"},"PeriodicalIF":3.7,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsomega.5c01637","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144296640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rational Design of Zeolites to Remove Siloxane-Related Pollutants with High Adsorption Loading and Enhanced Adsorption Energy","authors":"Shiru Lin,&nbsp;Biao Liu,&nbsp;Yekun Wang,&nbsp;Yinghe Zhao,&nbsp;Arturo J. Hernández-Maldonado* and Zhongfang Chen*,&nbsp;","doi":"10.1021/acsomega.4c1088610.1021/acsomega.4c10886","DOIUrl":"https://doi.org/10.1021/acsomega.4c10886https://doi.org/10.1021/acsomega.4c10886","url":null,"abstract":"<p >Though siloxanes and their derivatives have been widely used, they are emerging and persistent pollutants in water systems. Developing high-performance and low-cost adsorbents to remove siloxane-related pollutants is an essential strategy for removing these contaminants. Through Grand Canonical Monte Carlo (GCMC) simulations, we computed and evaluated the adsorption performances of 246 experimentally available zeolite frameworks toward three silanols, namely, trimethylsilanol (TMS), dimethylsilanediol (DMSD), monomethylsilanetriol (MMST), and the coexisting contaminant in siloxane-impacted environments, dimethylsulfone (DMSO₂), and obtained the best sorbents for each pollutant. To seek multifunctional zeolites, we first screened out the top 10 zeolite frameworks based on the loading values, among which the framework RWY showed the best performance. We further demonstrated that introducing dopants can enhance adsorption performance by taking RWY as an example. This work not only identified the most promising zeolite frameworks for removing linear siloxanes and derivatives, but also provided a relatively efficient and practical computational approach for screening sorbent materials for other emerging pollutants, balancing accuracy with tractable computational cost.</p>","PeriodicalId":22,"journal":{"name":"ACS Omega","volume":"10 23","pages":"24160–24168 24160–24168"},"PeriodicalIF":3.7,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsomega.4c10886","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144296455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimized Adsorption of Dyes and Antibiotics onto Natural Acacia Ataxacantha for Water Treatment","authors":"Khaled Chawraba*,&nbsp;Wassim El Malti*,&nbsp;Assil Akil,&nbsp;Malak Hamieh,&nbsp;Mohammad Hammoud,&nbsp;Digambara Patra,&nbsp;Joumana Toufaily and Akram Hijazi,&nbsp;","doi":"10.1021/acsomega.5c0204610.1021/acsomega.5c02046","DOIUrl":"https://doi.org/10.1021/acsomega.5c02046https://doi.org/10.1021/acsomega.5c02046","url":null,"abstract":"<p >This study explores the potential of<i>Acacia Ataxacantha</i>(Acacia) biomass as a low-cost and effective biosorbent for removing methylene blue dye (MB) and ciprofloxacin antibiotic (CIP) from water. The biosorbent was thoroughly characterized using FTIR, BET, SEM-EDX, XRD, and TGA-DTG, confirming the presence of key functional groups (−OH, −COOH). Optimal removal was achieved at room temperature, pH 7, and a biomass dosage of 2 g/L, with short equilibrium times of 30 min for MB and 5 min for CIP─faster than many conventional adsorbents. Isotherm analysis revealed that MB adsorption followed the Temkin model, whereas CIP conformed to the Langmuir model. The latter model showed maximum adsorption capacities of 133 mg/g for MB and 171 mg/g for CIP, which are comparable to or better than those of other biosorbents. The surface coverage at 25 °C was 36% for MB and 32% for CIP, indicating partial site utilization. Kinetic studies indicated that the adsorption process fits a pseudo-second-order model. Activation energy calculations yielded 34.5 kJ/mol for MB and −23.0 kJ/mol for CIP, indicating distinct adsorption mechanisms. Thermodynamic analysis confirmed that both adsorption processes were exothermic and spontaneous at 25 °C, with MB showing stronger interaction energy than CIP. A basic cost analysis estimated the production cost of 1 kg of Acacia biosorbent at 1.54 USD. Regeneration tests showed good reusability for up to four cycles for both MB and CIP. These results suggest that Acacia is a cost-effective and sustainable biosorbent for removing MB and CIP from water, offering a practical alternative to energy-intensive treatment methods.</p>","PeriodicalId":22,"journal":{"name":"ACS Omega","volume":"10 23","pages":"24847–24861 24847–24861"},"PeriodicalIF":3.7,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsomega.5c02046","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144296541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of Donor/Withdrawing Groups in an 3,5-Aryl-Substituted Pyrazole Organocatalyst for the Chemical Fixation of CO2","authors":"Gabriel Elias Taliateli Oliveira Prado,&nbsp;Karine Braga Enes,&nbsp;Álvaro Farias Arruda da Mata,&nbsp;Gabriel Cerqueira,&nbsp;Marcone Augusto Leal de Oliveira,&nbsp;Luiz Antônio Sodré Costa,&nbsp;Felipe Terra Martins,&nbsp;Meiry Edivirges Alvarenga,&nbsp;Rafael Pavão das Chagas,&nbsp;Mara Rubia Costa Couri* and Jorge Luiz Sônego Milani*,&nbsp;","doi":"10.1021/acsomega.4c1130710.1021/acsomega.4c11307","DOIUrl":"https://doi.org/10.1021/acsomega.4c11307https://doi.org/10.1021/acsomega.4c11307","url":null,"abstract":"<p >A series of 13 pyrazole derivatives, each featuring varied aryl groups in the 3,5-positions, were synthesized and characterized, including the determination of crystalline structures for compounds <b>11</b> and <b>13</b>. These pyrazoles, in the presence of tetrabutylammonium bromide (TBAB), selectively produced propylene cyclic carbonate (PC), with conversions reaching up to 90% and turnover frequency (TOF) = 75 h^–1 under optimal conditions (0.4 mol % of <b>13</b> and TBAB, 120 °C, 3 h, 30 bar). A 3³ Box–Behnken experimental design, with triplicate in the central point, was employed to evaluate the effects of temperature, catalyst, and cocatalyst loading. The nature of the aryl substituent significantly influenced the conversion rates, with electron-withdrawing groups (e.g., NO₂) yielding higher conversion than electron-donating groups (e.g., Me, MeO). Notably, pyrazoles featuring strong electron-donating <i>p</i>-OH-C₆H₄ (<b>11</b>–<b>13</b>) achieved the highest conversions, suggesting that the hydroxyl group also acts as a catalytic site. Density functional theory (DFT) calculations provided insight into the reaction mechanism and energy profiles, highlighting the roles of both the hydroxyl (OH) and amino (NH) groups in the catalytic cycle of compound <b>13</b>.</p>","PeriodicalId":22,"journal":{"name":"ACS Omega","volume":"10 23","pages":"24224–24234 24224–24234"},"PeriodicalIF":3.7,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsomega.4c11307","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144296639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-Driven Drug Discovery: A Comprehensive Review","authors":"Fábio J. N. Ferreira,&nbsp; and ,&nbsp;Agnaldo S. Carneiro*,&nbsp;","doi":"10.1021/acsomega.5c0054910.1021/acsomega.5c00549","DOIUrl":"https://doi.org/10.1021/acsomega.5c00549https://doi.org/10.1021/acsomega.5c00549","url":null,"abstract":"<p >Artificial intelligence (AI) and machine learning (ML) offer transformative potential to address the persistent challenges of traditional drug discovery, characterized by high costs, lengthy timelines, and low success rates. This comprehensive review critically analyzes recent advancements (2019–2024) in AI/ML methodologies across the entire drug discovery pipeline, from target identification to clinical development. We examine diverse AI techniques, including deep learning, graph neural networks, and transformers, focusing on their application in key areas such as target identification, lead discovery, hit optimization, and preclinical safety assessment. Our in-depth comparative analysis highlights the advantages, limitations, and practical challenges associated with different AI approaches, emphasizing critical factors for successful implementation such as data quality, model validation, and ethical considerations. The review synthesizes current applications, identifies persistent gaps─particularly in data accessibility, interpretability, and clinical translation─and proposes future directions to unlock the full potential of AI in creating safer, more effective, and accessible medicines. By emphasizing transparent methodologies, robust validation, and ethical frameworks, this review aims to guide the responsible and impactful integration of AI into pharmaceutical research and development.</p>","PeriodicalId":22,"journal":{"name":"ACS Omega","volume":"10 23","pages":"23889–23903 23889–23903"},"PeriodicalIF":3.7,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsomega.5c00549","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144296671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational Exploration of the Ability of the 2-Methyltetrols Produced from Photooxidation of Isoprene to Form Prenucleation Complexes","authors":"Conor J. Bready,&nbsp;Alexandra E. Sorescu,&nbsp;Caroline S. Glick and George C. Shields*,&nbsp;","doi":"10.1021/acsomega.5c0198110.1021/acsomega.5c01981","DOIUrl":"https://doi.org/10.1021/acsomega.5c01981https://doi.org/10.1021/acsomega.5c01981","url":null,"abstract":"<p >A central question in the formation of secondary aerosols is whether organic molecules participate in the formation of prenucleation clusters or are they only adsorbed after formation of larger aerosols? The difficulty in understanding the role of organic molecules in aerosol formation is that there are very few studies of prenucleation clusters produced from various organics and sulfuric acid, so it is uncertain whether organic compounds form prenucleation clusters. Isoprene is the most abundant volatile biogenic organic compound (VOC) emitted into the atmosphere, accounting for about 70% of biogenic VOC emissions, excluding methane. Each year, approximately 600 teragrams of isoprene enter the atmosphere, primarily from natural sources like vegetation. This makes it a significant component of atmospheric organic molecules, much more prevalent than other VOCs emitted by plants or anthropogenic activities. Photooxidation of isoprene produces the diastereomeric tetrols, 2-methylthreitol and 2-methylerythritol, which contain four hydroxyl groups. We completed a comprehensive conformational search of both tetrols, and extensively explored the potential energy surfaces of these tetrols complexed with sulfuric acid and water. We report the vast ensemble of structures that are within 1 kcal/mol of the DLPNO-CCSD(T)/CBS//ωB97X-D/6-31++G** minimum for each system. These high level Δ<i>G</i>° values for each system were used to estimate the concentrations of all the possible complexes from these molecules in the lower troposphere. At the upper limit of tetrol concentration, we find that the two diastereomers will bind to one to three water molecules in high concentrations. However, formation of sulfuric acid–tetrol–water complexes lead to lower concentrations, leading us to suggest that these tetrols are unlikely to be involved in the formation of prenucleation clusters that will lead to further aerosol growth. Researchers should continue the search for organic molecules that lead to prenucleation.</p>","PeriodicalId":22,"journal":{"name":"ACS Omega","volume":"10 23","pages":"24811–24831 24811–24831"},"PeriodicalIF":3.7,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsomega.5c01981","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144296732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use of Rice Husk as a Biosorbent for Analytical Purposes: Physicochemical, Morphological Characterization and Application in Human Breast Milk","authors":"Leonardo Corrêa Cardoso*,&nbsp;Gustavo Andrade Ugalde,&nbsp;Tielle Moraes de Almeida,&nbsp;Jaquelini da Silva Reis,&nbsp;Maria Odete da Silva Dalan,&nbsp;Fernanda Ziegler Reginato,&nbsp;Berenice de Oliveira Cruz Rodrigues,&nbsp;Cristiane de Bona da Silva,&nbsp;Fábio Andrei Duarte,&nbsp;Ederson Rossi Abaide,&nbsp;Marcio Antonio Mazutti and André Valle de Bairros,&nbsp;","doi":"10.1021/acsomega.4c1120010.1021/acsomega.4c11200","DOIUrl":"https://doi.org/10.1021/acsomega.4c11200https://doi.org/10.1021/acsomega.4c11200","url":null,"abstract":"<p >The secretion of medicines in breast milk is a crucial topic in clinical medicine. LC-DAD stands out in the literature for its simplicity, cost-effectiveness, and reproducibility. Chromatographic techniques, often coupled with cleaning methods such as μQuEChERS, have proven efficient in analyzing drugs across biological matrices. This study aims to characterize alternative sustainable biosorbents with a high silica content for analytical use, aiming to reduce environmental impact. Commercial sorbents (PSA, C18, GCB) and biosorbents (rice husk (RH), cork, orange bagasse, and passion fruit) were evaluated, with RH presenting superior results. RH was then characterized through laser diffraction, SEM, FT-IR spectroscopy, X-ray diffraction, and thermogravimetric analysis, among others. Key results include SPAN (2.567 ± 0.09), <i>D</i>[4,3] (126 ± 27), and a nonuniform morphology compared to commercial sorbents. RH composition was 27% cellulose, 13% hemicellulose, 9% lignin, and 23% extractives, with notable properties such as WRI (72%) and ZP (−19.2 ± 0.8). Unlike prior studies, this work provides unprecedented physicochemical and morphological characterization of biosorbents, demonstrating RH as a promising and sustainable alternative to traditional sorbents like C18.</p>","PeriodicalId":22,"journal":{"name":"ACS Omega","volume":"10 23","pages":"24200–24213 24200–24213"},"PeriodicalIF":3.7,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsomega.4c11200","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144296454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental and Simulation Study on the Explosion of a Coal/Methane Mixed System","authors":"Changhu Li,&nbsp;Pengjiang Deng*,&nbsp;Youwei Guo,&nbsp;Bingbing Zhang,&nbsp;Yansong Zhang and Xiangrui Wei,&nbsp;","doi":"10.1021/acsomega.5c0161610.1021/acsomega.5c01616","DOIUrl":"https://doi.org/10.1021/acsomega.5c01616https://doi.org/10.1021/acsomega.5c01616","url":null,"abstract":"<p >This study investigates the microscale suppression mechanisms of four powder explosion suppressants on coal dust/methane (CH₄) mixed system explosions. Combining experimental and numerical simulation methods, we explore the gas-phase reaction processes and the role of free radicals in the explosion suppression. Results show that all suppressants reduce the maximum explosion pressure and pressure rise rate, with MPP being the most effective, reducing pressure by 38%. Suppressants inhibit explosions through physical (heat absorption) and chemical (free-radical consumption) mechanisms. Phosphorus-containing intermediates from NH₄H₂PO₄ and MPP react with free radicals, while NaHCO₃ and MCA decompose to produce inert gases and consume O• and H• radicals. This work provides a theoretical foundation for optimizing explosion suppressants in mining safety applications.</p>","PeriodicalId":22,"journal":{"name":"ACS Omega","volume":"10 23","pages":"24730–24739 24730–24739"},"PeriodicalIF":3.7,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsomega.5c01616","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144296641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BioBrigit, a Hybrid Machine Learning and Knowledge-Based Approach to Model Metal Pathways in Proteins: Application to a Dicopper Tyrosinase","authors":"Raúl Fernández-Díaz,&nbsp;Lorena Roldán-Martín,&nbsp;Mariona Sodupe,&nbsp;José-Emilio Sánchez-Aparicio and Jean-Didier Maréchal*,&nbsp;","doi":"10.1021/acsomega.5c0060810.1021/acsomega.5c00608","DOIUrl":"https://doi.org/10.1021/acsomega.5c00608https://doi.org/10.1021/acsomega.5c00608","url":null,"abstract":"<p >The interaction of metallic species with proteins has been fundamental in evolution and is key in many physiological processes. How metals bind to proteins also holds promise in many fields, such as the design of new biocatalysts or the fight against pathogens. Nonetheless, uncovering the mechanism under which proteins recruit metal ions is far from understood and is one of the challenges in bioinorganic chemistry and structural biology. Computational methods are among the most promising tools for this endeavor. Only a handful of efficient structural predictors of metal binding sites exist. Most of the work focuses on identifying the most stable binding sites in the protein scaffolds. Although these methods are interesting, they do not consider the exploration of transient, suboptimal binding sites that could be relevant in metal binding pathways in proteins. At the far end of modeling capabilities nowadays, we introduce BioBrigit, a hybrid Machine Learning─knowledge-based approach that suggests metal binding pathways in proteins. To demonstrate the method’s viability, we apply it to the dicopper tyrosinase from <i>Streptomyces castaneoglobisporus</i>, a system for which crystallographic experiments allowed the identification of a series of transient sites of the copper in its path from a chaperone to the final catalytic site. Combined with homology modeling and large-scale molecular dynamics, BioBrigit allows for computational characterization of all experimental sites and a better understanding of the copper recruitment mechanism. BioBrigit appears as an asset in a field full of unknowns such as metal binding to proteins and opens the way to further algorithms in this area.</p>","PeriodicalId":22,"journal":{"name":"ACS Omega","volume":"10 23","pages":"24412–24421 24412–24421"},"PeriodicalIF":3.7,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsomega.5c00608","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144296669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}