Propedia: a database for protein-peptide identification based on a hybrid clustering algorithm.
Propedia: a database for protein-peptide identification based on a hybrid clustering algorithm.
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Propedia：基于混合聚类算法的蛋白质-肽识别数据库。
DOI：
10.1186/s12859-020-03881-z
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发表时间：
2021-01-02
影响因子：
3
通讯作者：
de Melo-Minardi RC
中科院分区：
文献类型：
--
作者：
Martins PM;Santos LH;Mariano D;Queiroz FC;Bastos LL;Gomes IS;Fischer PHC;Rocha REO;Silveira SA;de Lima LHF;de Magalhães MTQ;Oliveira MGA;de Melo-Minardi RC
蛋白质-肽相互作用在多种生物学过程中起着重要作用，例如细胞信号传导、调节网络、免疫应答和酶抑制。肽的特点是低毒性和小的界面面积;因此，它们是治疗策略、合理药物规划和蛋白质抑制的良好靶标。大约10%的伦理药物市场是基于蛋白质/肽的。此外，据估计，40%的蛋白质相互作用由肽介导。尽管生物学数据量快速增长，特别是关于序列和结构的数据，但仍然缺乏广泛和全面的蛋白质-肽数据库和工具，这些数据库和工具允许检索、表征和理解蛋白质-肽识别，从而支持肽设计。 我们介绍了Propedia，一个全面的和最新的数据库与Web界面，允许聚类，搜索和可视化的蛋白质-肽复合物根据不同的标准。Propedia包含来自蛋白质数据库的19，000多个高分辨率结构，包括蛋白质-肽复合物的结构和序列信息。与其他肽数据库相比，Propedia的主要优势在于它允许对相似性和冗余性进行更全面的分析。它是基于混合聚类算法构建的，该算法通过序列、界面结构和结合位点对肽进行比较和分组。Propedia通过图形化、用户友好和功能性界面提供，用户可以检索和分析复合物，并下载每个搜索数据集。我们进行了案例研究，并验证了Propedia评分的效用，以排名有希望的相互作用的肽。在一项涉及预测抑制SARS-CoV-2主要蛋白酶的肽的研究中，我们发现与SARS-CoV-2主要蛋白酶的不同肽复合物之间的相似性相关的Propedia评分与分子动力学自由能计算一致。Propedia是一个数据库和工具，用于支持基于结构的特殊用途肽的合理设计。蛋白质-肽相互作用可用于预测、分类和评分复合物或用于设计新分子。Propedia是一个随时可用的Web服务器，具有友好和资源丰富的界面，可在https://bioinfo.dcc.ufmg.br/propedia上获得
Protein–peptide interactions play a fundamental role in a wide variety of biological processes, such as cell signaling, regulatory networks, immune responses, and enzyme inhibition. Peptides are characterized by low toxicity and small interface areas; therefore, they are good targets for therapeutic strategies, rational drug planning and protein inhibition. Approximately 10% of the ethical pharmaceutical market is protein/peptide-based. Furthermore, it is estimated that 40% of protein interactions are mediated by peptides. Despite the fast increase in the volume of biological data, particularly on sequences and structures, there remains a lack of broad and comprehensive protein–peptide databases and tools that allow the retrieval, characterization and understanding of protein–peptide recognition and consequently support peptide design. We introduce Propedia, a comprehensive and up-to-date database with a web interface that permits clustering, searching and visualizing of protein–peptide complexes according to varied criteria. Propedia comprises over 19,000 high-resolution structures from the Protein Data Bank including structural and sequence information from protein–peptide complexes. The main advantage of Propedia over other peptide databases is that it allows a more comprehensive analysis of similarity and redundancy. It was constructed based on a hybrid clustering algorithm that compares and groups peptides by sequences, interface structures and binding sites. Propedia is available through a graphical, user-friendly and functional interface where users can retrieve, and analyze complexes and download each search data set. We performed case studies and verified that the utility of Propedia scores to rank promissing interacting peptides. In a study involving predicting peptides to inhibit SARS-CoV-2 main protease, we showed that Propedia scores related to similarity between different peptide complexes with SARS-CoV-2 main protease are in agreement with molecular dynamics free energy calculation. Propedia is a database and tool to support structure-based rational design of peptides for special purposes. Protein–peptide interactions can be useful to predict, classifying and scoring complexes or for designing new molecules as well. Propedia is up-to-date as a ready-to-use webserver with a friendly and resourceful interface and is available at: https://bioinfo.dcc.ufmg.br/propedia
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Hammock：一种隐藏的基于马尔可夫模型的肽聚类算法，以识别大型数据集中的蛋白质相互作用共识基序。
DOI：
10.1093/bioinformatics/btv522
发表时间：
2016-01-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Krejci A;Hupp TR;Lexa M;Vojtesek B;Muller P
通讯作者：
Muller P
影响因子：
14.9
作者：
Gautam A;Chaudhary K;Singh S;Joshi A;Anand P;Tuknait A;Mathur D;Varshney GC;Raghava GP
通讯作者：
Raghava GP
Biopython：用于计算分子生物学和生物信息学的免费 Python 工具。
DOI：
10.1093/bioinformatics/btp163
发表时间：
2009-06-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Cock PJ;Antao T;Chang JT;Chapman BA;Cox CJ;Dalke A;Friedberg I;Hamelryck T;Kauff F;Wilczynski B;de Hoon MJ
通讯作者：
de Hoon MJ
DOI：
10.1093/database/bas015
发表时间：
2012
期刊：
Database : the journal of biological databases and curation
影响因子：
--
作者：
Gautam A;Singh H;Tyagi A;Chaudhary K;Kumar R;Kapoor P;Raghava GP
通讯作者：
Raghava GP
影响因子：
5.6
作者：
LEE, B;RICHARDS, FM
通讯作者：
RICHARDS, FM