• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

肽效用（PU）搜索服务器：一种用于从多个数据库搜索肽序列的新工具。

Peptide Utility (PU) search server: A new tool for peptide sequence search from multiple databases.

作者信息

Chamoli Tanishq, Khera Alisha, Sharma Akanksha, Gupta Anshul, Garg Sonam, Mamgain Kanishk, Bansal Aayushi, Verma Shriya, Gupta Ankit, Alajangi Hema K, Singh Gurpal, Barnwal Ravi P

机构信息

Department of Computer Science and Engineering, Chandigarh College of Engineering and Technology, Chandigarh, India.

Department of Biophysics, Panjab University, Chandigarh 160014, India.

出版信息

Heliyon. 2022 Dec 10;8(12):e12283. doi: 10.1016/j.heliyon.2022.e12283. eCollection 2022 Dec.

DOI:10.1016/j.heliyon.2022.e12283
PMID:36590540
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9800339/
Abstract

Proteins are essential building blocks in humans that have garnered huge attention from researchers worldwide due to their numerous therapeutic applications. To date, different computational tools have been developed to extract pre-existing information on these biological molecules, but most of these tools suffer from limitations such as non-user friendly interface, redundancy of data, etc. To overcome these limitations, a user-friendly interface, the Peptide Utility (PU) webserver (https://chain-searching.herokuapp.com/) has been developed for searching and analyzing homologous and identical protein/peptide sequences that can be searched from approximately 0.4 million sequences (structural and sequence information) in both online and offline modes. The PU web server can also be used to study different types of interactions in PDBSum, identifying the most dominating interface residues, the most prevalent interactions, and the interaction preferences of different residues. The webserver would also pave way for the design of novel therapeutic peptides and folds by identifying conserved residues in the three-dimensional structure space of proteins.

摘要

蛋白质是人体必需的组成部分，因其众多的治疗应用而受到全球研究人员的广泛关注。迄今为止，已经开发了不同的计算工具来提取这些生物分子的现有信息，但这些工具大多存在诸如用户界面不友好、数据冗余等局限性。为克服这些局限性，已开发出一个用户友好的界面——肽工具（PU）网络服务器（https://chain-searching.herokuapp.com/），用于搜索和分析同源及相同的蛋白质/肽序列，这些序列可在在线和离线模式下从约40万条序列（结构和序列信息）中进行搜索。PU网络服务器还可用于研究PDBSum中的不同类型相互作用，识别最主要的界面残基、最普遍的相互作用以及不同残基的相互作用偏好。该网络服务器还将通过识别蛋白质三维结构空间中的保守残基，为新型治疗性肽和折叠结构的设计铺平道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233a/9800339/35b9bb34d51e/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233a/9800339/dbccf9d230b4/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233a/9800339/e1edaf2248e8/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233a/9800339/45d6b781c1a7/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233a/9800339/2e240a856b63/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233a/9800339/58aea1f38358/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233a/9800339/40bb1ab6a54e/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233a/9800339/35b9bb34d51e/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233a/9800339/dbccf9d230b4/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233a/9800339/e1edaf2248e8/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233a/9800339/45d6b781c1a7/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233a/9800339/2e240a856b63/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233a/9800339/58aea1f38358/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233a/9800339/40bb1ab6a54e/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233a/9800339/35b9bb34d51e/gr7.jpg

相似文献

1
Peptide Utility (PU) search server: A new tool for peptide sequence search from multiple databases.肽效用（PU）搜索服务器：一种用于从多个数据库搜索肽序列的新工具。
Heliyon. 2022 Dec 10;8(12):e12283. doi: 10.1016/j.heliyon.2022.e12283. eCollection 2022 Dec.
2
Propedia: a database for protein-peptide identification based on a hybrid clustering algorithm.Propedia：一种基于混合聚类算法的蛋白质-肽鉴定数据库。
BMC Bioinformatics. 2021 Jan 2;22(1):1. doi: 10.1186/s12859-020-03881-z.
3
PeptideMine--a webserver for the design of peptides for protein-peptide binding studies derived from protein-protein interactomes.PeptideMine--一个用于设计蛋白质-肽相互作用研究中肽的网络服务器，这些肽是从蛋白质-蛋白质相互作用组中衍生出来的。
BMC Bioinformatics. 2010 Sep 22;11:473. doi: 10.1186/1471-2105-11-473.
4
PDB-tools web: A user-friendly interface for the manipulation of PDB files.PDB-tools 网页：一个用于操作 PDB 文件的用户友好界面。
Proteins. 2021 Mar;89(3):330-335. doi: 10.1002/prot.26018. Epub 2020 Nov 7.
5
The visualCMAT: A web-server to select and interpret correlated mutations/co-evolving residues in protein families.可视化CMAT：一个用于选择和解释蛋白质家族中相关突变/共同进化残基的网络服务器。
J Bioinform Comput Biol. 2018 Apr;16(2):1840005. doi: 10.1142/S021972001840005X. Epub 2017 Dec 28.
6
SEQATOMS: a web tool for identifying missing regions in PDB in sequence context.SEQATOMS：一种用于在序列背景下识别PDB中缺失区域的网络工具。
Nucleic Acids Res. 2008 Jul 1;36(Web Server issue):W255-9. doi: 10.1093/nar/gkn237. Epub 2008 May 7.
7
RNA FRABASE 2.0: an advanced web-accessible database with the capacity to search the three-dimensional fragments within RNA structures.RNA FRABASE 2.0：一个高级的网络可访问数据库，具有搜索 RNA 结构中三维片段的能力。
BMC Bioinformatics. 2010 May 6;11:231. doi: 10.1186/1471-2105-11-231.
8
SCOWLP: a web-based database for detailed characterization and visualization of protein interfaces.SCOWLP：一个用于蛋白质界面详细表征和可视化的基于网络的数据库。
BMC Bioinformatics. 2006 Mar 2;7:104. doi: 10.1186/1471-2105-7-104.
9
Peptipedia: a user-friendly web application and a comprehensive database for peptide research supported by Machine Learning approach.Peptipedia：一个用户友好的网页应用程序和一个全面的肽研究数据库，由机器学习方法支持。
Database (Oxford). 2021 Sep 3;2021. doi: 10.1093/database/baab055.
10
Epsilon-Q: An Automated Analyzer Interface for Mass Spectral Library Search and Label-Free Protein Quantification.Epsilon-Q：用于质谱文库搜索和无标记蛋白质定量的自动化分析仪接口。
J Proteome Res. 2017 Dec 1;16(12):4435-4445. doi: 10.1021/acs.jproteome.6b01019. Epub 2017 Apr 4.

引用本文的文献

1
MultiPep-DLCL: recognition of multifunctional therapeutic peptides through deep learning with label-sequence contrastive learning.MultiPep-DLCL：通过带有标签序列对比学习的深度学习识别多功能治疗性肽。
Brief Bioinform. 2025 May 1;26(3). doi: 10.1093/bib/bbaf274.
2
Uniquome: Construction and decoding of a novel proteomic atlas that contains new peptide entities.独特蛋白质组：一种包含新肽段实体的新型蛋白质组图谱的构建与解读。
Comput Struct Biotechnol J. 2025 May 21;27:2123-2138. doi: 10.1016/j.csbj.2025.05.027. eCollection 2025.
3
Multimodal geometric learning for antimicrobial peptide identification by leveraging alphafold2-predicted structures and surface features.

本文引用的文献

1
Pseudo-Isolated α-Helix Platform for the Recognition of Deep and Narrow Targets.用于识别深而窄目标的拟孤立 α-螺旋平台。
J Am Chem Soc. 2022 Aug 31;144(34):15519-15528. doi: 10.1021/jacs.2c03858. Epub 2022 Aug 16.
2
In pursuit of next-generation therapeutics: Antimicrobial peptides against superbugs, their sources, mechanism of action, nanotechnology-based delivery, and clinical applications.追求下一代治疗方法：针对超级细菌的抗菌肽、它们的来源、作用机制、基于纳米技术的递药系统以及临床应用。
Int J Biol Macromol. 2022 Oct 1;218:135-156. doi: 10.1016/j.ijbiomac.2022.07.103. Epub 2022 Jul 20.
3
TPpred-ATMV: therapeutic peptide prediction by adaptive multi-view tensor learning model.
利用AlphaFold2预测结构和表面特征的多模态几何学习用于抗菌肽鉴定
Brief Bioinform. 2025 May 1;26(3). doi: 10.1093/bib/bbaf261.
4
NeuroPpred-MSN: A Neuropeptide Prediction Model Based on Multi-feature Fusion and Siamese Networks.NeuroPpred-MSN：一种基于多特征融合和连体网络的神经肽预测模型。
Interdiscip Sci. 2025 Jun 3. doi: 10.1007/s12539-025-00730-6.
5
Antimicrobial peptide biological activity, delivery systems and clinical translation status and challenges.抗菌肽的生物活性、递送系统以及临床转化现状与挑战。
J Transl Med. 2025 Mar 7;23(1):292. doi: 10.1186/s12967-025-06321-9.
6
Reinforcement learning-driven exploration of peptide space: accelerating generation of drug-like peptides.基于强化学习的肽空间探索：加速类药肽的生成。
Brief Bioinform. 2024 Jul 25;25(5). doi: 10.1093/bib/bbae444.
7
CycPeptMP: enhancing membrane permeability prediction of cyclic peptides with multi-level molecular features and data augmentation.CycPeptMP：利用多层次分子特征和数据增强提高环状肽的膜通透性预测。
Brief Bioinform. 2024 Jul 25;25(5). doi: 10.1093/bib/bbae417.
8
A two-stage computational framework for identifying antiviral peptides and their functional types based on contrastive learning and multi-feature fusion strategy.基于对比学习和多特征融合策略的抗病毒肽及其功能类型识别的两阶段计算框架。
Brief Bioinform. 2024 Mar 27;25(3). doi: 10.1093/bib/bbae208.
9
FEOpti-ACVP: identification of novel anti-coronavirus peptide sequences based on feature engineering and optimization.FEOpti-ACVP：基于特征工程和优化的新型抗冠状病毒肽序列的鉴定。
Brief Bioinform. 2024 Jan 22;25(2). doi: 10.1093/bib/bbae037.
10
iAMP-Attenpred: a novel antimicrobial peptide predictor based on BERT feature extraction method and CNN-BiLSTM-Attention combination model.iAMP-Attenpred：一种基于 BERT 特征提取方法和 CNN-BiLSTM-Attention 组合模型的新型抗菌肽预测器。
Brief Bioinform. 2023 Nov 22;25(1). doi: 10.1093/bib/bbad443.
TPpred-ATMV：基于自适应多视图张量学习模型的治疗性肽预测。
Bioinformatics. 2022 May 13;38(10):2712-2718. doi: 10.1093/bioinformatics/btac200.
4
Highly accurate protein structure prediction with AlphaFold.利用 AlphaFold 进行高精度蛋白质结构预测。
Nature. 2021 Aug;596(7873):583-589. doi: 10.1038/s41586-021-03819-2. Epub 2021 Jul 15.
5
Propedia: a database for protein-peptide identification based on a hybrid clustering algorithm.Propedia：一种基于混合聚类算法的蛋白质-肽鉴定数据库。
BMC Bioinformatics. 2021 Jan 2;22(1):1. doi: 10.1186/s12859-020-03881-z.
6
DBAASP v3: database of antimicrobial/cytotoxic activity and structure of peptides as a resource for development of new therapeutics.DBAASP v3：抗菌/细胞毒性肽的活性和结构数据库，是开发新疗法的资源。
Nucleic Acids Res. 2021 Jan 8;49(D1):D288-D297. doi: 10.1093/nar/gkaa991.
7
Machine learning-guided discovery and design of non-hemolytic peptides.机器学习指导的非溶血肽的发现和设计。
Sci Rep. 2020 Oct 6;10(1):16581. doi: 10.1038/s41598-020-73644-6.
8
PlantPepDB: A manually curated plant peptide database.植物肽数据库：一个人工整理的植物肽数据库。
Sci Rep. 2020 Feb 10;10(1):2194. doi: 10.1038/s41598-020-59165-2.
9
Improved protein structure prediction using potentials from deep learning.利用深度学习势进行蛋白质结构预测的改进。
Nature. 2020 Jan;577(7792):706-710. doi: 10.1038/s41586-019-1923-7. Epub 2020 Jan 15.
10
Applications of Molecular Dynamics Simulation in Structure Prediction of Peptides and Proteins.分子动力学模拟在肽和蛋白质结构预测中的应用
Comput Struct Biotechnol J. 2019 Jul 26;17:1162-1170. doi: 10.1016/j.csbj.2019.07.010. eCollection 2019.