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Peptide-Scaffolded Detergents for Membrane Protein Studies

CHEMISTRY-A EUROPEAN JOURNAL 2025年第16期31卷 e202404520页

作者： Yang, Meifang Dai, Yili Zhou, Fang Zhou, Xin Qiu, Yanli Tan, Yan zhao, suwen Xue, Dongxiang zhao, Fei Tao, Houchao Shanghai Univ Tradit Chinese Med Innovat Res Inst Tradit Chinese Med Shanghai Frontiers Sci Ctr TCM Chem Biol Shanghai 201203 Peoples R China Univ South China Inst Pharm & Pharmacol Hengyang Med Sch Hengyang 421001 Hunan Peoples R China ShanghaiTech Univ iHuman Inst Shanghai 201210 Peoples R China

Detergents are essential for preserving the structural integrity and functionality of membrane proteins (MPs) outside the biological membrane or in aqueous solution, and thus ensuring accurate biochemical and structural analyses. Here, we introduce peptide-scaffolded detergents, a novel class of hybrid molecules formed by preassembling detergent monomers with peptides of varying lengths, mediated via Click chemistry. These detergents are characterized by scalable, straightforward synthesis and enhanced solubility. Among the variants, A4B2 emerged as the optimal detergent, demonstrating superior thermal stabilization across a range of G protein-coupled receptors, including A2AAR, SMO and GLP-1R. Additionally, A4B2 exhibits a low critical micelle concentration and small micelle size, together making it particularly effective for electron microscopy studies of A2AAR. This innovative design leverages the benefits of peptide-based and traditional detergents, offering new insights for the development of advanced detergents in MP research.

关键词： Peptide-scaffolded detergents Membrane proteins Micelle Click reaction

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"Living Detergents": an in Situ Detergent Tailoring Strategy for Efficient Membrane Protein Stabilization and Analysis

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CHEMISTRY-A EUROPEAN JOURNAL 2025年第28期31卷 e202501128页

作者： Dai, Yili Yang, Meifang Luo, Weiling Qiu, Yanli Zhou, Fang Zheng, Xing zhao, Fei Yao, Xu zhao, suwen Tao, Houchao Univ South China Inst Pharm & Pharmacol Hengyang Med Sch Hengyang 421001 Hunan Peoples R China Shanghai Univ Tradit Chinese Med Innovat Res Inst Tradit Chinese Med Shanghai Frontiers Sci Ctr TCM Chem Biol Shanghai 201203 Peoples R China ShanghaiTech Univ iHuman Inst Shanghai 201210 Peoples R China Hunan Vocat Coll Sci & Technol Dept Pharm Changsha 410004 Hunan Peoples R China

Detergents are essential molecular tools for membrane protein (MP) research, yet traditional detergents with static properties often fail to address the diverse and evolving needs of MP studies. To this end, this study introduces "living detergents", an innovative class of detergents equipped with functional tags that enable bioorthogonal modifications with externally introduced structural elements. This approach allows for not only the parallel generation of new detergents, but also in situ tuning of MP samples within freshly formed detergents. The efficacy of this strategy was demonstrated through the rapid identification of optimal detergents for high-quality electron microscopy studies of A2AAR. Overall, this flexible and robust platform enables efficient tailoring of detergents, advancing the exploration of detergent structure-function relationships in MP research and opening pathways for more specialized solutions for diverse experimental demands.

关键词： bioorthogonal reaction living detergent membrane proteins micelle Introduction

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Conformational ensembles for protein structure prediction

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SCIENTIFIC REPORTS 2025年第1期15卷 1-17页

作者： Yang, Jiaan Cheng, Wen Xiang Zhang, Peng Wu, Gang Sheng, Si Tong Yang, Junjie zhao, suwen Hu, Qiyue Ji, Wenxin Shi, Qiong Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen 518055 Guangdong Peoples R China Micro Biotech Ltd Shanghai 200123 Peoples R China Huazhong Univ Sci & Technol Tongji Med Coll Sch Basic Med Wuhan 430030 Hubei Peoples R China HYK High Throughput Biotechnol Inst Shenzhen 518057 Guangdong Peoples R China Wuhan Int Biohub Cooperat Wuhan 430075 Hubei Peoples R China ShanghaiTech Univ iHuman Inst Shanghai 201210 Peoples R China Beyang Therapeut Co Ltd Shanghai 201210 Peoples R China Chinese Acad Sci Shanghai Adv Res Inst Natl Facil Prot Sci Shanghai Shanghai 201210 Peoples R China Shenzhen Univ Coll Life Sci & Oceanog Lab Aquat Genom Shenzhen 518057 Peoples R China Shenzhen Univ Adv Technol Biomed Engn Shenzhen 518060 Peoples R China

Acquisition of conformational ensembles for a protein is a challenging task, which is actually involving to the solution for protein folding problem and the study of intrinsically disordered protein. Despite AlphaFold with artificial intelligence acquired unprecedented accuracy to predict structures, its result is limited to a single state of conformation and it cannot provide multiple conformations to display protein intrinsic disorder. To overcome the barrier, a FiveFold approach was developed with a single sequence method. It applied the protein folding shape code (PFSC) uniformly to expose local folds of five amino acid residues, formed the protein folding variation matrix (PFVM) to reveal local folding variations along sequence, obtained a massive number of folding conformations in PFSC strings, and then an ensemble of multiple conformational protein structures is constructed. The P53_HUMAN as a well-known protein and LEF1_HUMAN and Q8GT36_SPIOL as typical disordered proteins are token as the benchmark to evaluate the predicted outcomes. The results demonstrated an effective algorithm and biological meaningful process well to predict protein multiple conformation structures.

关键词： Protein structure prediction Protein conformation Protein folding Intrinsically disordered protein Protein intrinsic disorder AlphaFold

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Topography-guided, patterned, customized corneal crosslinking for non-invasive astigmatism correction

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EYE 2025年第6期39卷 1193-1202页

作者： Fan, Zixin Jiang, Xinyi zhao, suwen Dou, Ningxin Yao, Fei Zhang, Shaochong Cai, Gangpei Li, Yang Wu, Yiheng He, Weidong Zhang, Guoming Mi, Shengli Jinan Univ Shenzhen Eye Hosp Shenzhen Eye Inst Shenzhen Guangdong Peoples R China Tsinghua Univ Int Grad Sch Shenzhen Biomfg Engn Lab Shenzhen Guangdong Peoples R China Sun Yat Sen Univ Affiliated Hosp 5 Guangdong Prov Engn Res Ctr Mol Imaging Zhuhai Guangdong Peoples R China

Objectives: To propose and evaluate a novel, non-invasive approach for enduring corneal astigmatism correction based on topography-guided, patterned, customized riboflavin-ultraviolet A corneal collagen crosslinking (CXL). Methods: Astigmatism was modelled on both eyes of rabbits. A randomly selected eye of each rabbit was treated by the proposed CXL procedure with another eye as control. The proposed procedure was performed by a self-built intelligent platform through delivering ultraviolet A lattice in a refined and patterned manner, based on pre-operative corneal topography. The long-term effectiveness, stability, and safety were investigated for 180 days, with topographic measurements, anterior segment optical coherence tomography (AS-OCT), and in vivo corneal confocal microscopy (IVCM). Results: Spatially selective demarcation lines in AS-OCT images and trabecular patterned hyperdense structure with abundant needle-like processes in IVCM images were detected in the CXL eyes, revealing spatially selective crosslinking. Reductions of astigmatic magnitude (in the steep axis: 0.46 +/- 0.28 vs. 2.15 +/- 0.58 dioptres, P < 0.001) and high order aberration (0.38 +/- 0.18 vs. 0.59 +/- 0.19, P = 0.009) with increase of visual strehl ratio (0.21 +/- 0.06 vs. 0.13 +/- 0.03, P < 0.001) were found in the CXL eyes after CXL and maintained for 180 days, compared to inconspicuous changes in the control eyes. No obvious opacity and inflammation were observed in the CXL eyes, and transient loss of endothelial cells in the treated area was recovered in the subsequent visit. Conclusions: The proposed novel, non-invasive approach safely fulfilled corneal astigmatism correction with visual quality improvement as well as a decrease in high-order aberration.

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Cryo-EM structure of an activated GPR4-Gs signaling complex

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NATURE COMMUNICATIONS 2025年第1期16卷 1-10页

作者： Ma, Yitong Wang, Yijie Tang, Mengyuan Weng, Yuan Chen, Ying Xu, Yueming An, Shuxiao Wu, Yiran zhao, suwen Xu, Huanhuan Li, Dali Liu, Mingyao Lu, Weiqiang Ru, Heng Song, Gaojie East China Normal Univ Inst Biomed Sci Shanghai Frontiers Sci Ctr Genome Editing & Cell T Shanghai Key Lab Regulatory Biol Shanghai Peoples R China East China Normal Univ Sch Life Sci Shanghai Peoples R China Zhejiang Univ Affiliated Hosp 2 Life Sci Inst Sch MedZhejiang Prov Key Lab Canc Mol Cell Biol Hangzhou Zhejiang Peoples R China ShanghaiTech Univ iHuman Inst Shanghai Peoples R China ShanghaiTech Univ Sch Life Sci & Technol Shanghai Peoples R China Yunnan Agr Univ Coll Sci Kunming Peoples R China

G protein-coupled receptor 4 (GPR4) belongs to the subfamily of proton-sensing GPCRs (psGPCRs), which detect pH changes in extracellular environment and regulate diverse physiological responses. GPR4 was found to be overactivated in acidic tumor microenvironment as well as inflammation sites, with a triad of acidic residues within the transmembrane domain identified as crucial for proton sensing. However, the 3D structure remains unknown, and the roles of other conserved residues within psGPCRs are not well understood. Here we report cryo-electron microscopy (cryo-EM) structures of active zebrafish GPR4 at both pH 6.5 and 8.5, each highlighting a distribution of histidine and acidic residues at the extracellular region. Cell-based assays show that these ionizable residues moderately influence the proton-sensing capacity of zebrafish GPR4, compared to the more significant effects of the triad residues. Furthermore, we reveal a cluster of aromatic residues within the orthosteric pocket that may propagate the signaling to the intercellular region via repacking the aromatic patch at the central region. This study provides a framework for future signaling and functional investigation of psGPCRs.

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Large-Scale Analysis of Bioactive Ligand Conformational Strain Energy by Ab Initio Calculation

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JOURNAL OF CHEMICAL INFORMATION AND MODELING 2021年第3期61卷 1180-1192页

作者： Tong, Jiahui zhao, suwen ShanghaiTech Univ iHuman Inst Shanghai 201210 Peoples R China ShanghaiTech Univ Sch Life Sci & Technol Shanghai 201210 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci Shanghai Inst Nutr & Hlth Shanghai 200031 Peoples R China

Ligand conformational strain energy (LCSE) plays an important role in virtual screening and lead optimization. While various studies have provided insights into LCSE for small-molecule ligands in the Protein Data Bank (PDB), conclusions are inconsistent mainly due to small datasets, poor quality control of crystal structures, and molecular mechanics (MM) or low-level quantum mechanics (QM) calculations. Here, we built a high-quality dataset (LigBoundConf) of 8145 ligand-bound conformations from PDB crystal structures and calculated LCSE at the M062X-D3/ma-TZVPP (SMD)//M062X-D3/def2-SVP(SMD) level for each case in the dataset. The mean/median LCSE is 4.6/3.7 kcal/mol for 6672 successfully calculated cases, which is significantly lower than the estimates based on molecular mechanics in many previous analyses. Especially, when removing ligands with nonaromatic ring(s) that are prone to have large LCSEs due to electron density overfitting, the mean/median LCSE was reduced to 3.3/2.5 kcal/mol. We further reveal that LCSE is correlated with several ligand properties, including formal atomic charge, molecular weight, number of rotatable bonds, and number of hydrogen-bond donors and acceptors. In addition, our results show that although summation of torsion strains is a good approximation of LCSE for most cases, for a small fraction (about 6%) of our dataset, it underestimates LCSEs if ligands could form nonlocal intramolecular interactions in the unbound state. Taken together, our work provides a comprehensive profile of LCSE for ligands in PDB, which could help ligand conformation generation, ligand docking pose evaluation, and lead optimization.

关键词： Ligands Energy Conformation Molecular structure Electron density

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A semi-supervised self-training method based on density peaks and natural neighbors

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JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 2021年第2期12卷 2939-2953页

作者： zhao, suwen Li, Junnan Chongqing Univ Coll Bioengn Chongqing 400044 Peoples R China Guilin Univ Aerosp Technol Dept Elect Engn Guilin 541004 Peoples R China Chongqing Univ Coll Comp Sci Chongqing Key Lab Software Theory & Technol Chongqing 400044 Peoples R China

The semi-supervised self-training method is one of the successful methodologies of semi-supervised classification and can train a classifier by exploiting both labeled data and unlabeled data. However, most of the self-training methods are limited by the distribution of initial labeled data, heavily rely on parameters and have the poor ability of prediction in the self-training process. To solve these problems, a novel self-training method based on density peaks and natural neighbors (STDPNaN) is proposed. In STDPNaN, an improved parameter-free density peaks clustering (DPCNaN) is firstly presented by introducing natural neighbors. The DPCNaN can reveal the real structure and distribution of data without any parameter, and then helps STDPNaN restore the real data space with the spherical or non-spherical distribution. Also, an ensemble classifier is employed to improve the predictive ability of STDPNaN in the self-training process. Intensive experiments show that (a) STDPNaN outperforms state-of-the-art methods in improving classification accuracy ofknearest neighbor, support vector machine and classification and regression tree;(b) STDPNaN also outperforms comparison methods without any restriction on the number of labeled data;(c) the running time of STDPNaN is acceptable.

关键词： Self-training method Semi-supervised classification Semi-supervised learning Natural neighbors Density peaks

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Structural basis of β-glucopyranoside salicin recognition by a human bitter taste GPCR

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Cell Reports 2025年第5期44卷 115604页

作者： Wang, Xin Zhou, Cui Ao, Weizhen Wu, Lijie Wu, Yiran Xu, Weixiu Liu, Shenhui Tan, Qiwen Wang, Ling zhao, Fei Liu, Junlin Pei, Yuan zhao, suwen Hua, Tian iHuman Institute ShanghaiTech University Shanghai 201210 China School of Life Science and Technology ShanghaiTech University Shanghai 201210 China Lingang Laboratory Shanghai 200031 China

The human perception of bitterness is mediated by type 2 taste receptors (TAS2Rs), which recognize a broad array of bitter substances with distinct chemical properties. TAS2R16 exhibits a pronounced selectivity for β-glucoside-moiety-containing compounds, such as salicin from willow bark. However, the molecular mechanism of moiety-specific recognition and receptor activation in TAS2R16 remains unclear. Here, we present cryoelectron microscopy structures of the salicin-activated human TAS2R16 complexed with gustducin and G_i1 and G_i2 proteins. The binding mode of salicin with TAS2R16 and the specific interactions of the β-D-glucopyranoside moiety are detailed. Together with molecular docking and mutagenesis data, this study uncovers the structural underpinnings of TAS2R16’s group-specific recognition, receptor activation, and subsequent gustducin and G_i protein coupling. These findings advance our understanding of human bitter taste receptors and provide a foundation for structural modifications of bitter glycosides, opening potential therapeutic applications. © 2025 The Author(s)

关键词： bitter taste receptor CP: Molecular biology GPCR salicin TAS2R16 β-glucopyranoside

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ELS: A Fast Parameter-Free Edition Algorithm With Natural Neighbors-Based Local Sets for k Nearest Neighbor

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IEEE ACCESS 2020年 8卷 123773-123782页

作者： zhao, suwen Li, Junnan Guilin Univ Aerosp Technol Dept Elect Engn Guilin 541004 Peoples R China Chongqing Univ Coll Bioengn Chongqing 400030 Peoples R China Chongqing Univ Coll Comp Sci Chongqing Key Lab Software Theory & Technol Chongqing 400044 Peoples R China

The instance reduction is one of the data preprocessing methods and aims to remove noises and (or) redundant instances from the training set. In the instance reduction, one of the most representative techniques is the edition method which can remove harmful instances from the training set to improve the prediction accuracy of k nearest neighbor (KNN). Nevertheless, most of existing edition methods still have some drawbacks, such as the parameter dependency, high computational time and relatively low accuracy. To solve these problems, we present a new fast parameter-free edition method based on local sets with natural neighbors (ELS). In ELS, we define a new concept of local sets by introducing natural neighbors. ELS can use the local sets to keep more reasonable class boundaries and effectively filtering out noisy instances (including global outliers). The main advantages of ELS are that (a) it is parameter-free;(b) it can remove global outliers and noisy instances;(c) it is relatively fast. Experiments clearly verify that (a) ELS outperforms existing representative edition methods in improving the prediction accuracy of KNN;(b) ELS can improve the performance of the condensation method and hybrid method in terms of both accuracy and reduction;(c) ELS consumes relatively low running time.

关键词： Data preprocessing instance reduction edition methods natural neighbors local sets nearest neighbors

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Knowledge distillation of face recognition via attention cosine similarity review

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IET COMPUTER VISION 2024年第7期18卷 875-887页

作者： Wang, Zhuo zhao, suwen Guo, Wanyi Xian Univ Architecture & Technol Coll Informat & Control Engn Xian Peoples R China

Deep learning-based face recognition models have demonstrated remarkable performance in benchmark tests, and knowledge distillation technology has been frequently accustomed to obtain high-precision real-time face recognition models specifically designed for mobile and embedded devices. However, in recent years, the knowledge distillation methods for face recognition, which mainly focus on feature or logit knowledge distillation techniques, neglect the attention mechanism that play an important role in the domain of neural networks. An innovation cross-stage connection review path of the attention cosine similarity knowledge distillation method that unites the attention mechanism with review knowledge distillation method is proposed. This method transfers the attention map obtained from the teacher network to the student through a cross-stage connection path. The efficacy and excellence of the proposed algorithm are demonstrated in popular benchmark tests. The authors propose a cross-stage connection review of the attention cosine similarity knowledge distillation method. This method leverages the teacher's shallow multi-stage attention maps to guide deep single-stage attention map in the student model. In the AMFM module, multi-stage attention map is fused, and in the HCCSL module, the spatial pyramid pooling technique is employed obtain multi-level of attention map information, different levels of attention context information and attention map are calculated cosine similarity loss. The proposed algorithm superior performance is compared to sota methods. image

关键词： computer vision convolutional neural nets face recognition

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