Proteomics最新文献_第9页

DREAMweb: An online tool for graph‐based modeling of NMR protein structure DREAMweb：基于图形的核磁共振蛋白质结构建模在线工具

IF 3.4 4区生物学

Proteomics Pub Date : 2024-04-17 DOI: 10.1002/pmic.202300379

Niladri Ranajan Das, Kunal Narayan Chaudhury, Debnath Pal

{"title":"DREAMweb: An online tool for graph‐based modeling of NMR protein structure","authors":"Niladri Ranajan Das, Kunal Narayan Chaudhury, Debnath Pal","doi":"10.1002/pmic.202300379","DOIUrl":"https://doi.org/10.1002/pmic.202300379","url":null,"abstract":"The value of accurate protein structural models closely conforming to the experimental data is indisputable. DREAMweb deploys an improved DREAM algorithm, DREAMv2, that incorporates a tighter bound in the constraint set of the underlying optimization approach. This reduces the artifacts while modeling the protein structure by solving the distance‐geometry problem. DREAMv2 follows a bottom‐up strategy of building smaller substructures for regions with a larger concentration of experimental bounds and consolidating them before modeling the rest of the protein structure. This improves secondary structure conformance in the final models consistent with experimental data. The proposed method efficiently models regions with sparse coverage of experimental data by reducing the possibility of artifacts compared to DREAM. To balance performance and accuracy, smaller substructures ( atoms) are solved in this regime, allowing faster builds for the other parts under relaxed conditions. DREAMweb is accessible as an internet resource. The improvements in results are showcased through benchmarks on 10 structures. DREAMv2 can be used in tandem with any NMR‐based protein structure determination workflow, including an iterative framework where the NMR assignment for the NOESY spectra is incomplete or ambiguous. DREAMweb is freely available for public use at http://pallab.cds.iisc.ac.in/DREAM/ and downloadable at https://github.com/niladriranjandas/DREAMv2.git.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140615333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Polyglutamine disease proteins: Commonalities and differences in interaction profiles and pathological effects 多谷氨酰胺疾病蛋白：相互作用和病理效应的共性与差异

IF 3.4 4区生物学

Proteomics Pub Date : 2024-04-14 DOI: 10.1002/pmic.202300114

Megan Bonsor, Orchid Ammar, Sigrid Schnoegl, Erich E. Wanker, Eduardo Silva Ramos

{"title":"Polyglutamine disease proteins: Commonalities and differences in interaction profiles and pathological effects","authors":"Megan Bonsor, Orchid Ammar, Sigrid Schnoegl, Erich E. Wanker, Eduardo Silva Ramos","doi":"10.1002/pmic.202300114","DOIUrl":"10.1002/pmic.202300114","url":null,"abstract":"Currently, nine polyglutamine (polyQ) expansion diseases are known. They include spinocerebellar ataxias (SCA1, 2, 3, 6, 7, 17), spinal and bulbar muscular atrophy (SBMA), dentatorubral-pallidoluysian atrophy (DRPLA), and Huntington's disease (HD). At the root of these neurodegenerative diseases are trinucleotide repeat mutations in coding regions of different genes, which lead to the production of proteins with elongated polyQ tracts. While the causative proteins differ in structure and molecular mass, the expanded polyQ domains drive pathogenesis in all these diseases. PolyQ tracts mediate the association of proteins leading to the formation of protein complexes involved in gene expression regulation, RNA processing, membrane trafficking, and signal transduction. In this review, we discuss commonalities and differences among the nine polyQ proteins focusing on their structure and function as well as the pathological features of the respective diseases. We present insights from AlphaFold-predicted structural models and discuss the biological roles of polyQ-containing proteins. Lastly, we explore reported protein–protein interaction networks to highlight shared protein interactions and their potential relevance in disease development.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202300114","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140567689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Imputation of missing values in lipidomic datasets 脂质体数据集缺失值的估算

IF 3.4 4区生物学

Proteomics Pub Date : 2024-04-11 DOI: 10.1002/pmic.202300606

Nicolas Frölich, Christian Klose, Elisabeth Widén, Samuli Ripatti, Mathias J. Gerl

{"title":"Imputation of missing values in lipidomic datasets","authors":"Nicolas Frölich, Christian Klose, Elisabeth Widén, Samuli Ripatti, Mathias J. Gerl","doi":"10.1002/pmic.202300606","DOIUrl":"10.1002/pmic.202300606","url":null,"abstract":"Lipidomic data often exhibit missing data points, which can be categorized as missing completely at random (MCAR), missing at random, or missing not at random (MNAR). In order to utilize statistical methods that require complete datasets or to improve the identification of potential effects in statistical comparisons, imputation techniques can be employed. In this study, we investigate commonly used methods such as zero, half-minimum, mean, and median imputation, as well as more advanced techniques such as k-nearest neighbor and random forest imputation. We employ a combination of simulation-based approaches and application to real datasets to assess the performance and effectiveness of these methods. Shotgun lipidomics datasets exhibit high correlations and missing values, often due to low analyte abundance, characterized as MNAR. In this context, k-nearest neighbor approaches based on correlation and truncated normal distributions demonstrate best performance. Importantly, both methods can effectively impute missing values independent of the type of missingness, the determination of which is nearly impossible in practice. The imputation methods still control the type I error rate.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202300606","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140567651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Differential expression of N‐glycopeptides derived from serum glycoproteins in mild cognitive impairment (MCI) patients 轻度认知障碍（MCI）患者血清糖蛋白中 N-糖肽的表达差异

IF 3.4 4区生物学

Proteomics Pub Date : 2024-04-11 DOI: 10.1002/pmic.202300620

Cristian D. Gutierrez Reyes, Mojgan Atashi, Mojibola Fowowe, Sherifdeen Onigbinde, Oluwatosin Daramola, David M. Lubman, Yehia Mechref

{"title":"Differential expression of N‐glycopeptides derived from serum glycoproteins in mild cognitive impairment (MCI) patients","authors":"Cristian D. Gutierrez Reyes, Mojgan Atashi, Mojibola Fowowe, Sherifdeen Onigbinde, Oluwatosin Daramola, David M. Lubman, Yehia Mechref","doi":"10.1002/pmic.202300620","DOIUrl":"https://doi.org/10.1002/pmic.202300620","url":null,"abstract":"Mild cognitive impairment (MCI) is an early stage of memory loss that affects cognitive abilities with the aging of individuals, such as language or visual/spatial comprehension. MCI is considered a prodromal phase of more complicated neurodegenerative diseases such as Alzheimer's. Therefore, accurate diagnosis and better understanding of the disease prognosis will facilitate prevention of neurodegeneration. However, the existing diagnostic methods fail to provide precise and well‐timed diagnoses, and the pathophysiology of MCI is not fully understood. Alterations of the serum N‐glycoproteome expression could represent an essential contributor to the overall pathophysiology of neurodegenerative diseases and be used as a potential marker to assess MCI diagnosis using less invasive procedures. In this approach, we identified N‐glycopeptides with different expressions between healthy and MCI patients from serum glycoproteins. Seven of the N‐glycopeptides showed outstanding AUC values, among them the antithrombin‐III Asn224 + 4‐5‐0‐2 with an AUC value of 1.00 and a p value of 0.0004. According to proteomics and ingenuity pathway analysis (IPA), our data is in line with recent publications, and the glycoproteins carrying the identified N‐sites play an important role in neurodegeneration.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140567649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Functional proteomics reveals that Slr0237 is a SigE-regulated glycogen debranching enzyme pivotal for glycogen breakdown 功能蛋白质组学发现，Slr0237 是一种受 SigE 调控的糖原去支链酶，对糖原分解至关重要

IF 3.4 4区生物学

Proteomics Pub Date : 2024-04-05 DOI: 10.1002/pmic.202300222

Ye Liu, Haitao Ge, Dandan Lu

引用次数: 0

Contents: Proteomics 7'24 内容蛋白质组学 7'24

IF 3.4 4区生物学

Proteomics Pub Date : 2024-04-04 DOI: 10.1002/pmic.202470043

引用次数: 0

Editorial Board: Proteomics 7'24 编辑委员会：蛋白质组学 7'24

IF 3.4 4区生物学

Proteomics Pub Date : 2024-04-04 DOI: 10.1002/pmic.202470042

引用次数: 0

Proteomic profiling of small extracellular vesicles derived from mouse pancreatic cancer and stellate cells: Role in pancreatic cancer 从小鼠胰腺癌细胞和星状细胞中提取的细胞外小泡的蛋白质组分析：在胰腺癌中的作用

IF 3.4 4区生物学

Proteomics Pub Date : 2024-04-03 DOI: 10.1002/pmic.202300067

Chamini J. Perera, SM Zahid Hosen, Tanzila Khan, Haoyun Fang, Alpha Raj Mekapogu, Zhihong Xu, Marco Falasca, Suresh T. Chari, Jeremy S. Wilson, Ron Pirola, David W. Greening, Minoti V. Apte

{"title":"Proteomic profiling of small extracellular vesicles derived from mouse pancreatic cancer and stellate cells: Role in pancreatic cancer","authors":"Chamini J. Perera, SM Zahid Hosen, Tanzila Khan, Haoyun Fang, Alpha Raj Mekapogu, Zhihong Xu, Marco Falasca, Suresh T. Chari, Jeremy S. Wilson, Ron Pirola, David W. Greening, Minoti V. Apte","doi":"10.1002/pmic.202300067","DOIUrl":"10.1002/pmic.202300067","url":null,"abstract":"Small extracellular vesicles (sEVs) are cell-derived vesicles evolving as important elements involved in all stages of cancers. sEVs bear unique protein signatures that may serve as biomarkers. Pancreatic cancer (PC) records a very poor survival rate owing to its late diagnosis and several cancer cell-derived proteins have been reported as candidate biomarkers. However, given the pivotal role played by stellate cells (PSCs, which produce the collagenous stroma in PC), it is essential to also assess PSC-sEV cargo in biomarker discovery. Thus, this study aimed to isolate and characterise sEVs from mouse PC cells and PSCs cultured alone or as co-cultures and performed proteomic profiling and pathway analysis. Proteomics confirmed the enrichment of specific markers in the sEVs compared to their cells of origin as well as the proteins that are known to express in each of the culture types. Most importantly, for the first time it was revealed that PSC-sEVs are enriched in proteins (including G6PI, PGAM1, ENO1, ENO3, and LDHA) that mediate pathways related to development of diabetes, such as glucose metabolism and gluconeogenesis revealing a potential role of PSCs in pancreatic cancer-related diabetes (PCRD). PCRD is now considered a harbinger of PC and further research will enable to identify the role of these components in PCRD and may develop as novel candidate biomarkers of PC.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202300067","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140594709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Differential effects of physiological agonists on the proteome of platelet-derived extracellular vesicles 生理激动剂对血小板源性细胞外囊泡蛋白质组的不同影响。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-03-31 DOI: 10.1002/pmic.202300391

Mitchell J. Moon, Alin Rai, Prerna Sharma, Haoyun Fang, James D. McFadyen, David W. Greening, Karlheinz Peter

{"title":"Differential effects of physiological agonists on the proteome of platelet-derived extracellular vesicles","authors":"Mitchell J. Moon, Alin Rai, Prerna Sharma, Haoyun Fang, James D. McFadyen, David W. Greening, Karlheinz Peter","doi":"10.1002/pmic.202300391","DOIUrl":"10.1002/pmic.202300391","url":null,"abstract":"Arterial thrombosis manifesting as heart attack and stroke is the leading cause of death worldwide. Platelets are central mediators of thrombosis that can be activated through multiple activation pathways. Platelet-derived extracellular vesicles (pEVs), also known as platelet-derived microparticles, are granular mixtures of membrane structures produced by platelets in response to various activating stimuli. Initial studies have attracted interest on how platelet agonists influence the composition of the pEV proteome. In the current study, we used physiological platelet agonists of varying potencies which reflect the microenvironments that platelets experience during thrombus formation: adenosine diphosphate, collagen, thrombin as well as a combination of thrombin/collagen to induce platelet activation and pEV generation. Proteomic profiling revealed that pEVs have an agonist-dependent altered proteome in comparison to their cells of origin, activated platelets. Furthermore, we found that various protein classes including those related to coagulation and complement (prothrombin, antithrombin, and plasminogen) and platelet activation (fibrinogen) are attributed to platelet EVs following agonist stimulation. This agonist-dependent altered proteome suggests that protein packaging is an active process that appears to occur without de novo protein synthesis. This study provides new information on the influence of physiological agonist stimuli on the biogenesis and proteome landscape of pEVs.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202300391","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140331348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Open-source large language models in action: A bioinformatics chatbot for PRIDE database. 行动中的开源大型语言模型：用于 PRIDE 数据库的生物信息学聊天机器人。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-03-31 DOI: 10.1002/pmic.202400005

Jingwen Bai, Selvakumar Kamatchinathan, Deepti J Kundu, Chakradhar Bandla, Juan Antonio Vizcaíno, Yasset Perez-Riverol

{"title":"Open-source large language models in action: A bioinformatics chatbot for PRIDE database.","authors":"Jingwen Bai, Selvakumar Kamatchinathan, Deepti J Kundu, Chakradhar Bandla, Juan Antonio Vizcaíno, Yasset Perez-Riverol","doi":"10.1002/pmic.202400005","DOIUrl":"https://doi.org/10.1002/pmic.202400005","url":null,"abstract":"We here present a chatbot assistant infrastructure (https://www.ebi.ac.uk/pride/chatbot/) that simplifies user interactions with the PRIDE database's documentation and dataset search functionality. The framework utilizes multiple Large Language Models (LLM): llama2, chatglm, mixtral (mistral), and openhermes. It also includes a web service API (Application Programming Interface), web interface, and components for indexing and managing vector databases. An Elo-ranking system-based benchmark component is included in the framework as well, which allows for evaluating the performance of each LLM and for improving PRIDE documentation. The chatbot not only allows users to interact with PRIDE documentation but can also be used to search and find PRIDE datasets using an LLM-based recommendation system, enabling dataset discoverability. Importantly, while our infrastructure is exemplified through its application in the PRIDE database context, the modular and adaptable nature of our approach positions it as a valuable tool for improving user experiences across a spectrum of bioinformatics and proteomics tools and resources, among other domains. The integration of advanced LLMs, innovative vector-based construction, the benchmarking framework, and optimized documentation collectively form a robust and transferable chatbot assistant infrastructure. The framework is open-source (https://github.com/PRIDE-Archive/pride-chatbot).","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140331349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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