IF 4.3 3区生物学

Methods Pub Date : 2025-09-10 DOI: 10.1016/j.ymeth.2025.08.012

Fernando Silva, Gustavo Costa, Francisco Veiga, Vera Moura, Francisca Dias, Fátima Cerqueira, Rui Medeiros, Ana Cláudia Paiva-Santos

{"title":"Rapid in vitro and computer-aided method for assessing synergistic interactions between NSAIDs and analgesics.","authors":"Fernando Silva, Gustavo Costa, Francisco Veiga, Vera Moura, Francisca Dias, Fátima Cerqueira, Rui Medeiros, Ana Cláudia Paiva-Santos","doi":"10.1016/j.ymeth.2025.08.012","DOIUrl":"10.1016/j.ymeth.2025.08.012","url":null,"abstract":"<p><p>Pain is a complex phenomenon that plays a significant role in various diseases, influencing both the physical and psychological well-being of individuals. In clinical practice, combining nonsteroidal anti-inflammatory drugs (NSAIDs) with analgesics, such as paracetamol or metamizole, has become a widely adopted strategy to manage pain. Although the synergistic effects of combining NSAIDs with analgesics are well recognized in clinical practice, this approach is primarily based on empirical clinical experience. Our work aims to present a rapid method for evaluating the anti-inflammatory effects of drug combinations through in vitro assays combined with computer-aided data processing and analysis. We conducted two simple and rapid in vitro assays, the Griess and DPPH assays, to evaluate the effects of NSAID-analgesic combinations and demonstrate their synergistic interactions, using the free web application SynergyFinder Plus. This computer-aided analysis enabled a quantitative assessment of drug interactions, enhancing the interpretation of the experimental data. Furthermore, to better understand the results obtained from previous experiments, we analysed the anti-inflammatory effects of ketoprofen and dexketoprofen in combination with metamizole and paracetamol through quantitative real-time PCR (qRT-PCR). Our findings reveal synergistic interactions between NSAIDs and analgesics in terms of their anti-inflammatory and antioxidant activities. This work could be the first step for the study of the mechanisms behind the synergistic interactions between NSAIDs and analgesics for the treatment of pain, mainly when inflammatory processes are involved. Consequently, this study aims to contribute to the exploration of non-opioid drug combinations, addressing the urgent need for alternative analgesic strategies that minimize opioid use.</p>","PeriodicalId":390,"journal":{"name":"Methods","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144937936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimization of 13C stable isotope labeling for the study of tricarboxylic cycle intermediates in mouse models 小鼠模型中三羧基循环中间体的13C稳定同位素标记优化。

IF 4.3 3区生物学

Methods Pub Date : 2025-09-10 DOI: 10.1016/j.ymeth.2025.09.004

Jarrod Laro , Monica Ness , Joseane Godinho , Randy Coats , Laura-Isobel McCall

{"title":"Optimization of 13C stable isotope labeling for the study of tricarboxylic cycle intermediates in mouse models","authors":"Jarrod Laro , Monica Ness , Joseane Godinho , Randy Coats , Laura-Isobel McCall","doi":"10.1016/j.ymeth.2025.09.004","DOIUrl":"10.1016/j.ymeth.2025.09.004","url":null,"abstract":"<div><div>The tricarboxylic acid cycle (TCA), also known as the Krebs Cycle or the citric acid cycle, is an essential metabolic pathway involved in energy production that is often impacted by disease, making it of key interest to identify effective, affordable, and simple ways to monitor the impact of disease on TCA metabolism. <sup>13</sup>C-based stable isotope labeling is a useful technique to track pathway alterations in living hosts. However, infusion-based methodologies are slow and expensive despite achieving steady-state labeling. Bolus-based methods are cheaper, faster, and compatible with biohazardous models, but require optimization to achieve maximum labeling. Herein, we performed bolus-based stable isotope labeling experiments in mouse models to identify the optimal dosage amount, label administration length, fast length prior to label administration, <sup>13</sup>C-labeled precursor, and route of administration for the TCA cycle in the esophagus, heart, kidney, liver, plasma, and proximal colon. <sup>13</sup>C-glucose at a concentration of 4 mg/g administered via intraperitoneal injection followed by a 90 min label incorporation period achieved the best overall TCA labeling. For most organs, a 3 h fast prior to label administration improved labeling, but labeling in the heart was better with no fasting period, showcasing the need to optimize methodology on an organ-by-organ basis. We also identified that bolus administration of glucose provided little impact on metabolism compared to vehicle control. The experiments outlined here provide critical information for designing in vivo stable isotope labeling experiments for the study of the TCA cycle.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"244 ","pages":"Pages 75-81"},"PeriodicalIF":4.3,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145051513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ResDeepGS: A deep learning-based method for crop phenotype prediction ResDeepGS：基于深度学习的作物表型预测方法。

IF 4.3 3区生物学

Methods Pub Date : 2025-09-08 DOI: 10.1016/j.ymeth.2025.07.013

Chaokun Yan , Jiabao Li , Qi Feng , Junwei Luo , Huimin Luo

{"title":"ResDeepGS: A deep learning-based method for crop phenotype prediction","authors":"Chaokun Yan , Jiabao Li , Qi Feng , Junwei Luo , Huimin Luo","doi":"10.1016/j.ymeth.2025.07.013","DOIUrl":"10.1016/j.ymeth.2025.07.013","url":null,"abstract":"<div><div>Genomic selection (GS) is a breeding technique that utilizes genomic markers to predict the genetic potential of crops and animals. This approach holds significant promise for accelerating the improvement of agronomic traits and addressing food security challenges. While traditional breeding methods based on statistical or machine learning techniques have been useful in predicting traits for some crops, they often fail to capture the complex interactions between genotypes and phenotypes. Additionally, these methods struggle to handle large-scale data, limiting their predictive performance. Recent advancements in deep learning offer a promising solution by better capturing nonlinear relationships and gene interactions.</div><div>In this study, we propose a novel crop phenotype prediction method, ResDeepGS, which leverages deep learning techniques. The model consists of two main components: the feature selection module and the phenotype prediction module. The feature selection module employs an incremental recursive feature elimination method, combining the strengths of recursive feature elimination and incremental learning to improve both the efficiency and reliability of feature selection. The phenotype prediction module integrates an enhanced multi-layer convolutional neural network with residual structures and dropout strategies to better capture complex relationships in gene data, accelerate convergence, and reduce overfitting. Through extensive experimentation, we demonstrate that ResDeepGS outperforms current state-of-the-art methods on three datasets: wheat, maize, and soybean. Notably, on the wheat dataset, ResDeepGS improved prediction accuracy by 5% to 9%, highlighting its superior performance in genomic selection tasks. These results underscore the robustness and adaptability of ResDeepGS, offering a promising solution for enhancing crop breeding efficiency and addressing future food security challenges.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"244 ","pages":"Pages 65-74"},"PeriodicalIF":4.3,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145032613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Michaelis-Menten kinetics of RasGAP proteins by a rapid fluorescence-based assay RasGAP蛋白的Michaelis-Menten动力学

IF 4.3 3区生物学

Methods Pub Date : 2025-09-08 DOI: 10.1016/j.ymeth.2025.09.003

Maxum E. Paul , Kimberly J. Vish , Titus J. Boggon

{"title":"Michaelis-Menten kinetics of RasGAP proteins by a rapid fluorescence-based assay","authors":"Maxum E. Paul , Kimberly J. Vish , Titus J. Boggon","doi":"10.1016/j.ymeth.2025.09.003","DOIUrl":"10.1016/j.ymeth.2025.09.003","url":null,"abstract":"<div><div>Ras small GTPases are essential for a wide range of cellular processes. These proteins cycle between the GDP-loaded and GTP-loaded states, and the actions of GTPase activating proteins (GAPs) are necessary to stimulate Ras-mediated GTP hydrolysis. Here, we provide a protocol to achieve Michaelis-Menten kinetic profiling of GAP-mediated stimulation of a small GTPase by real-time monitoring of inorganic phosphate release <em>in vitro</em>. This is achieved using fluorescence of the Phosphate Sensor protein, an MDCC conjugate with periplasmic phosphate binding protein (PstS). We use H-Ras small GTPase pre-loaded with GTP and its stimulation by p120RasGAP (RasGAP, RASA1) as an example of this protocol. We discuss protocol design, assay development, data collection, processing, and analysis. Typical assays comprise up to twenty simultaneous reactions with phosphate production rates on the order of tens of nM/s. We also provide guidelines for the optimization of reagent conditions, particularly salt concentrations, and assess their functional impact. The described protocol provides a convenient and comprehensive method to achieve accurate monitoring of small GTPase activation by GAP proteins using widely available materials and suitable to a range of applications.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"244 ","pages":"Pages 108-117"},"PeriodicalIF":4.3,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145032559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unveiling the pathogenicity of allosteric protein mutations via multifaceted feature ensembling 通过多面特征集合揭示变构蛋白突变的致病性。

IF 4.3 3区生物学

Methods Pub Date : 2025-09-08 DOI: 10.1016/j.ymeth.2025.07.014

Huiling Zhang , Xijian Li , Junwen Huang , Yuetong Li , Shaozhen Cai , Haiyan Wang , Yanjie Wei

{"title":"Unveiling the pathogenicity of allosteric protein mutations via multifaceted feature ensembling","authors":"Huiling Zhang , Xijian Li , Junwen Huang , Yuetong Li , Shaozhen Cai , Haiyan Wang , Yanjie Wei","doi":"10.1016/j.ymeth.2025.07.014","DOIUrl":"10.1016/j.ymeth.2025.07.014","url":null,"abstract":"<div><div>Allostery proteins play a central role in biological processes and systems. Uncovering the biological effects of allosteric protein mutations and their role in disease progression remains a significant challenge. Theoretically, computational approaches hold the potential to enable large-scale interpretation of genetic variants in allosteric proteins. Nevertheless, general-purpose variant effect prediction (VEP) methodologies overlook the characteristic disparities across different genes. What is more critical is that individual tools frequently display inconsistencies, biases, and fluctuations in quality. Consequently, the predictions obtained from existing VEP approaches are considered insufficiently reliable. In the present research, we constructed an a multifaceted-feature-based ensemble learning approach to forecast the pathogenicity of missense mutations within allosteric proteins. The proposed method used categorical boosting to integrate four types of features, namely, sequence information, AlphaFold2-extracted biochemical properties, prediction scores from other VEP methods, and allele frequency from gnomAD. Our method demonstrated superior performance with an AUC of 0.912 when tested on a benchmark allosteric protein dataset, outperforming 22 general VEP methods. To facilitate the identification of pathogenic mutations in the sea of rare variants discovered as sequencing studies expand on a large scale, we provided the pathogenicity probabilities of all potential amino acid substitutions in 202 allosteric-protein-encoding genes. To sum up, our research indicates that multifaceted-feature-based ensemble learning models can offer valuable independent evidence for interpreting missense mutations in allosteric proteins, which will be broadly applicable in both research and clinical contexts.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"244 ","pages":"Pages 82-91"},"PeriodicalIF":4.3,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145032583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deciphering cellular heterogeneity: Breakthroughs and prospects of single-cell-level SERS analysis in precision medicine 解读细胞异质性：精准医学中单细胞水平SERS分析的突破与展望

IF 4.3 3区生物学

Methods Pub Date : 2025-09-07 DOI: 10.1016/j.ymeth.2025.09.002

Biqing Chen, Jiayin Gao, Haizhu Sun, Yan Liu, Yinghan Zhao, Xiaohong Qiu

{"title":"Deciphering cellular heterogeneity: Breakthroughs and prospects of single-cell-level SERS analysis in precision medicine","authors":"Biqing Chen, Jiayin Gao, Haizhu Sun, Yan Liu, Yinghan Zhao, Xiaohong Qiu","doi":"10.1016/j.ymeth.2025.09.002","DOIUrl":"10.1016/j.ymeth.2025.09.002","url":null,"abstract":"<div><div>Single-cell surface-enhanced Raman scattering (SERS) has emerged as a powerful tool for precision medicine owing to its label-free detection, ultrasensitivity, and unique molecular fingerprinting. Unlike conventional bulk analysis, it enables detailed characterization of cellular heterogeneity, with particular promise in circulating tumor cell (CTC) identification, tumor microenvironment (TME) metabolic profiling, subcellular imaging, and drug sensitivity assessment. Coupled with microfluidic droplet systems, SERS supports high-throughput single-cell analysis and multiparametric screening, while integration with complementary modalities such as fluorescence microscopy and mass spectrometry enhances temporal and spatial resolution for monitoring live cells. Despite hurdles in nanoprobe safety, complex spectral interpretation, and clinical translation, advances in AI-driven data processing (e.g., convolutional neural networks) and miniaturized devices are accelerating progress toward intraoperative guidance, improved liquid biopsy, and primary healthcare adoption. Looking ahead, its applications in single-cell metabolomics, exosome studies, and microbial detection hold promise for uncovering disease mechanisms and fostering personalized diagnostics and therapeutics.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"244 ","pages":"Pages 7-29"},"PeriodicalIF":4.3,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Strain promoted click labeling of oligonucleotides on solid-phase support 应变促进在固相载体上的寡核苷酸点击标记。

IF 4.3 3区生物学

Methods Pub Date : 2025-09-06 DOI: 10.1016/j.ymeth.2025.09.001

Michaela Beranova , Petra Grossova , Jiri Demuth , Filip Kostelansky , Veronika Novakova , Petr Zimcik , Miroslav Miletin

{"title":"Strain promoted click labeling of oligonucleotides on solid-phase support","authors":"Michaela Beranova , Petra Grossova , Jiri Demuth , Filip Kostelansky , Veronika Novakova , Petr Zimcik , Miroslav Miletin","doi":"10.1016/j.ymeth.2025.09.001","DOIUrl":"10.1016/j.ymeth.2025.09.001","url":null,"abstract":"<div><div>Chemically modified oligonucleotides (ONs) are essential tools in molecular biology, diagnostics, and therapeutics. Strain-promoted azide–alkyne cycloaddition (SPAAC) offers an efficient and bioorthogonal method for ON functionalization. While SPAAC reactions on solid-phase support provide distinct advantages, particularly for the incorporation of lipophilic labels, factors influencing their efficiency remain poorly characterized. The interplay between the physicochemical properties of the modifying molecule, the nature of the solid support, and the labeling site within the ON chain has not been systematically evaluated. In this study, we systematically investigate how modifying molecule properties (size, polarity) and concentration, solid support type, labeling site within the ON chain, and reaction time influence efficiency of labeling. Our findings demonstrate that while polar modifying molecules react efficiently across all solid supports, lipophilic molecules can exhibit reduced reactivity on glass-based supports, particularly in positions close to the 3́-end of the oligonucleotide attached to the support. We further show that conjugation at the 5′-terminus consistently yields the highest efficiencies, with a gradual decline observed as the modification site approaches the 3′-end. A 1 mM concentration of labeling reagent was sufficient to achieve high yields on polystyrene support for all labels and on CPG 500 for the polar labels. The size of the modifying molecule had a lesser effect compared to other factors. The method also benefits from recovery and reusability of the unreacted label. These results enable the rational design of efficient ON labeling protocols on solid-phase support while minimizing reagent consumption, contributing to both cost-effectiveness and environmental sustainability.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"244 ","pages":"Pages 46-54"},"PeriodicalIF":4.3,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145022572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AI-augmented prediction of high-risk PINK1 variants associated with Parkinson’s disease: integrating multilayered bioinformatics, MD simulation, and deep learning 人工智能增强预测与帕金森病相关的高危PINK1变异：整合多层生物信息学、MD模拟和深度学习

IF 4.3 3区生物学

Methods Pub Date : 2025-09-04 DOI: 10.1016/j.ymeth.2025.08.014

Hafeez Ur Rehman , Dawood Ahmad Warraich , Abdur Rehman , Israr Fatima , Yuxuan Meng , Mohamed Aldaw , Yanheng Ding , Ruiqi Zhang , Yu Ni , Zhijie He , Hao Zhang , Zhibo Wang , Lijun Feng , Yingcui Yu , Mingzhi Liao

{"title":"AI-augmented prediction of high-risk PINK1 variants associated with Parkinson’s disease: integrating multilayered bioinformatics, MD simulation, and deep learning","authors":"Hafeez Ur Rehman , Dawood Ahmad Warraich , Abdur Rehman , Israr Fatima , Yuxuan Meng , Mohamed Aldaw , Yanheng Ding , Ruiqi Zhang , Yu Ni , Zhijie He , Hao Zhang , Zhibo Wang , Lijun Feng , Yingcui Yu , Mingzhi Liao","doi":"10.1016/j.ymeth.2025.08.014","DOIUrl":"10.1016/j.ymeth.2025.08.014","url":null,"abstract":"<div><div>Parkinson’s disease is a prevalent neurodegenerative disease, in which genetic mutations in many genes play an important role in its pathogenesis. Among these, a mutation in the PINK1 gene, a mitochondrial-targeted serine/threonine putative kinase 1 that protects cells from stress-induced mitochondrial dysfunction, is implicated in autosomal recessive Parkinsonism. However, the exact etiology is not well understood. Therefore, this study aimed to identify the most damaging non-synonymous single-nucleotide polymorphisms (nsSNPs) distributed in the kinase domain of the PINK1 gene and their structural and functional alterations using a range of bioinformatics and deep learning tools. Next, to find the possible impact of these mutations on PINK1 interactions and binding affinities, a protein–protein interaction and molecular docking analysis were conducted. Finally, molecular dynamics (MD) simulations were performed to observe the stability and dynamic behaviour of the pathogenic SNPs on the PINK1 protein over time. Our integrated bioinformatics and deep learning approaches predicted 5 SNPs (C166R, E240K, D362N, D362Y, and C388R) as high-risk candidates for disrupting PINK1 structure and function. In conclusion, we propose that the pathogenicity of these variants may provide an important clue to understanding the mechanism by which pathogenic nsSNPs contribute to PD, thereby enhancing future diagnostic value for the disease and serving as potential targets for new drugs.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"244 ","pages":"Pages 30-45"},"PeriodicalIF":4.3,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145008071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Capturing G protein-coupled receptors into native lipid-bilayer nanodiscs using new diisobutylene/maleic acid (DIBMA) copolymers 利用新型二异丁烯/马来酸（DIBMA）共聚物将G蛋白偶联受体捕获到天然脂质双层纳米圆盘中。

IF 4.3 3区生物学

Methods Pub Date : 2025-09-04 DOI: 10.1016/j.ymeth.2025.08.013

Ci Chu , Carolyn Vargas , Maria Carolina Barbosa , Simon Sommerhage , Gerald N. Rechberger , David Pahovnik , Ema Žagar , Gunnar F. Schröder , Sandro Keller , Manuel Etzkorn

{"title":"Capturing G protein-coupled receptors into native lipid-bilayer nanodiscs using new diisobutylene/maleic acid (DIBMA) copolymers","authors":"Ci Chu , Carolyn Vargas , Maria Carolina Barbosa , Simon Sommerhage , Gerald N. Rechberger , David Pahovnik , Ema Žagar , Gunnar F. Schröder , Sandro Keller , Manuel Etzkorn","doi":"10.1016/j.ymeth.2025.08.013","DOIUrl":"10.1016/j.ymeth.2025.08.013","url":null,"abstract":"<div><div>Many membrane proteins, including G protein-coupled receptors (GPCRs), are susceptible to denaturation when extracted from their native membrane by detergents. Therefore, alternative methods have been developed, including amphiphilic copolymers that enable the direct extraction of functional membrane proteins along with their surrounding lipids. Among these amphiphilic copolymers, styrene/maleic acid (SMA) and diisobutylene/maleic acid (DIBMA) polymers have been extensively studied. Despite their many benefits, SMA and DIBMA polymers also have considerable drawbacks limiting their applications. Herein, we describe a series of new amphiphilic copolymers derived from DIBMA via partial amidation of the carboxylate pendant groups with various biocompatible amines. We characterize the new polymer’s nanodisc-forming properties and ability to extract the melanocortin 4 receptor (MC<sub>4</sub>R), a prototypical class A GPCR. While each new DIBMA variant displays features that may be favorable for selected applications, we identified a PEGylated DIBMA variant called mPEG<sub>4</sub>-DIBMA as particularly promising. In the tested system mPEG<sub>4</sub>-DIBMA abolishes unspecific interactions and outperforms other polymers by achieving higher extraction efficiencies of MC<sub>4</sub>R from Sf9 insect cell membranes. The new nanodisc-forming polymer combines two key advantages that are crucial for investigating GPCRs in a well-defined but still native lipid-bilayer environment, thus paving the way for manifold future applications.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"244 ","pages":"Pages 55-64"},"PeriodicalIF":4.3,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145008085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient RNA nucleotide encoding enhances the accurate prediction of ac4C modifications 高效的RNA核苷酸编码增强了对ac4C修饰的准确预测。

IF 4.3 3区生物学

Methods Pub Date : 2025-08-31 DOI: 10.1016/j.ymeth.2025.07.012

Na Li , Xiao Wang , Ming Zeng , Feng Cao , Ke Qiu , Jianbo Qiao

引用次数: 0

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