• 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

蛋白质-配体结合位点的计算机模拟鉴定与表征

In silico Identification and Characterization of Protein-Ligand Binding Sites.

作者信息

Roche Daniel Barry, McGuffin Liam James

机构信息

Institut de Biologie Computationnelle, LIRMM, CNRS, Université de Montpellier, 860 rue de St Priest, 34095, Montpellier, France.

Centre de Recherche en Biologie cellulaire de Montpellier, CNRS-UMR 5237, 1919 Route de Mende, Montpellier, 34293, France.

出版信息

Methods Mol Biol. 2016;1414:1-21. doi: 10.1007/978-1-4939-3569-7_1.

DOI:10.1007/978-1-4939-3569-7_1
PMID:27094282
Abstract

Protein-ligand binding site prediction methods aim to predict, from amino acid sequence, protein-ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein-ligand interactions has become extremely important to help determine a protein's functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein-ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein-ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein-ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.

摘要

蛋白质 - 配体结合位点预测方法旨在根据氨基酸序列,利用序列信息、结构信息或两者结合来预测蛋白质 - 配体相互作用、推定配体和配体结合位点残基。蛋白质 - 配体相互作用的计算机模拟表征对于帮助确定蛋白质的功能已变得极为重要,因为基于体内的功能阐释无法跟上当前序列数据库的增长速度。此外,体外生化功能阐释耗时、成本高,且对于大规模分析(如药物发现)可能不可行。因此,必须利用蛋白质 - 配体相互作用的计算机模拟预测来辅助功能阐释。在此,我们简要讨论蛋白质功能预测、蛋白质 - 配体相互作用预测、蛋白质结构预测技术关键评估(CASP)和连续自动评估(CAMEO)竞赛,以及它们在塑造该领域中的作用。我们还详细讨论了我们用于蛋白质 - 配体相互作用结构信息预测的前沿网络服务器方法FunFOLD。此外我们提供了使用FunFOLD网络服务器和可下载应用程序FunFOLD3的分步指南,以及一些实际应用示例,其中FunFOLD方法已用于辅助功能阐释。

相似文献

1
In silico Identification and Characterization of Protein-Ligand Binding Sites.蛋白质-配体结合位点的计算机模拟鉴定与表征
Methods Mol Biol. 2016;1414:1-21. doi: 10.1007/978-1-4939-3569-7_1.
2
Toolbox for Protein Structure Prediction.蛋白质结构预测工具箱。
Methods Mol Biol. 2016;1369:363-77. doi: 10.1007/978-1-4939-3145-3_23.
3
Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods with a Focus on FunFOLD3.蛋白质及其相互作用伙伴:聚焦FunFOLD3的蛋白质-配体结合位点预测方法介绍
Methods Mol Biol. 2021;2365:43-58. doi: 10.1007/978-1-0716-1665-9_3.
4
FunFOLD: an improved automated method for the prediction of ligand binding residues using 3D models of proteins.FunFOLD:一种改进的基于蛋白质 3D 模型预测配体结合残基的自动化方法。
BMC Bioinformatics. 2011 May 16;12:160. doi: 10.1186/1471-2105-12-160.
5
Continuous Automated Model EvaluatiOn (CAMEO) complementing the critical assessment of structure prediction in CASP12.连续自动模型评估(CAMEO)对蛋白质结构预测关键评估(CASP12)的补充
Proteins. 2018 Mar;86 Suppl 1(Suppl 1):387-398. doi: 10.1002/prot.25431. Epub 2017 Dec 17.
6
Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods.蛋白质及其相互作用伙伴:蛋白质-配体结合位点预测方法介绍
Int J Mol Sci. 2015 Dec 15;16(12):29829-42. doi: 10.3390/ijms161226202.
7
The FunFOLD2 server for the prediction of protein-ligand interactions.FunFOLD2 服务器:用于预测蛋白质-配体相互作用。
Nucleic Acids Res. 2013 Jul;41(Web Server issue):W303-7. doi: 10.1093/nar/gkt498. Epub 2013 Jun 12.
8
The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction.IntFOLD 服务器:一个集成的蛋白质折叠识别、3D 模型质量评估、固有无序预测、结构域预测和配体结合位点预测的网络资源。
Nucleic Acids Res. 2011 Jul;39(Web Server issue):W171-6. doi: 10.1093/nar/gkr184. Epub 2011 Mar 31.
9
IntFOLD: an integrated server for modelling protein structures and functions from amino acid sequences.IntFOLD:一个用于从氨基酸序列建模蛋白质结构和功能的集成服务器。
Nucleic Acids Res. 2015 Jul 1;43(W1):W169-73. doi: 10.1093/nar/gkv236. Epub 2015 Mar 27.
10
FunFOLDQA: a quality assessment tool for protein-ligand binding site residue predictions.FunFOLDQA:一种用于蛋白质-配体结合位点残基预测的质量评估工具。
PLoS One. 2012;7(5):e38219. doi: 10.1371/journal.pone.0038219. Epub 2012 May 30.

引用本文的文献

1
Characterization of Novel ACE-Inhibitory Peptides from Jellyfish Venom Hydrolysate: In Vitro and In Silico Approaches.水母毒液水解产物中新型血管紧张素转换酶抑制肽的表征:体外和计算机模拟方法
Mar Drugs. 2025 Jun 26;23(7):267. doi: 10.3390/md23070267.
2
Heparin-binding of the human chitinase-like protein YKL-40 is allosterically modified by chitin oligosaccharides.人几丁质酶样蛋白YKL-40的肝素结合被几丁质寡糖变构修饰。
Biochem Biophys Rep. 2024 Dec 24;41:101908. doi: 10.1016/j.bbrep.2024.101908. eCollection 2025 Mar.
3
Design and selection of peptides to block the SARS-CoV-2 receptor binding domain by molecular docking.
通过分子对接设计和筛选阻断严重急性呼吸综合征冠状病毒2(SARS-CoV-2)受体结合域的肽段。
Beilstein J Nanotechnol. 2022 Jul 22;13:699-711. doi: 10.3762/bjnano.13.62. eCollection 2022.
4
Bioinformatic Analysis of Two TOR (Target of Rapamycin)-Like Proteins Encoded by Revealed Structural Similarities with Functional Homologs.生物信息学分析两个由 编码的 TOR(雷帕霉素靶蛋白)样蛋白,揭示了与功能同源物的结构相似性。
Genes (Basel). 2021 Jul 28;12(8):1139. doi: 10.3390/genes12081139.
5
Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods with a Focus on FunFOLD3.蛋白质及其相互作用伙伴:聚焦FunFOLD3的蛋白质-配体结合位点预测方法介绍
Methods Mol Biol. 2021;2365:43-58. doi: 10.1007/978-1-0716-1665-9_3.
6
Structure-Function Relationship Study of a Secretory Amoebic Phosphatase: A Computational-Experimental Approach.分泌型阿米巴磷酸酶的结构-功能关系研究:计算-实验方法。
Int J Mol Sci. 2021 Feb 22;22(4):2164. doi: 10.3390/ijms22042164.
7
ResiRole: residue-level functional site predictions to gauge the accuracies of protein structure prediction techniques.ResiRole:残基水平功能位点预测,以评估蛋白质结构预测技术的准确性。
Bioinformatics. 2021 Apr 20;37(3):351-359. doi: 10.1093/bioinformatics/btaa712.
8
Determining protein similarity by comparing hydrophobic core structure.通过比较疏水核心结构来确定蛋白质相似性。
Heliyon. 2017 Feb 7;3(2):e00235. doi: 10.1016/j.heliyon.2017.e00235. eCollection 2017 Feb.
9
Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods.蛋白质及其相互作用伙伴:蛋白质-配体结合位点预测方法介绍
Int J Mol Sci. 2015 Dec 15;16(12):29829-42. doi: 10.3390/ijms161226202.