<1>. Histone related resources. (1) Histone Modification databases. (2) Histone Protein databases. <2>. Acetylation related resources. (1) Acetylation databases. (2) Prediction of Acetylation sites. <3>. Methylation related resources. (1) Prediction of Methylation sites.
<1>. Histone related resources.
1. Histone Modification databases.
(1) CPLM: a database of protein lysine modifications, which occur at active ε-amino groups of specific lysine residues in proteins and are critical for orchestrating various biological processes, including acetylation and methylation (Liu Z., et al., 2014).
(2) HHMD: the human histone modification database. focuses on the storage and integration of histone modification datasets that were obtained from laboratory experiments. The latest release of HHMD incorporates 43 location-specific histone modifications in human (Zhang, et al., 2010).
(4) EpimiR: a database of curated mutual regulation between miRNAs and epigenetic modifications, which collects 1974 regulations between 19 kinds of epigenetic modifications, such as DNA methylation, histone acetylation, H3K4me3, H3S10p. (Dai E, et al., 2014).
(5) GED: a manually curated comprehensive resource for epigenetic modification of gametogenesis. The database integrates three kinds information of epigenetic modifications during gametogenesis (DNA methylation, histone modification and RNA regulation) (Bai W, et al., 2016).
(7) SysPTM: provides a systematic and sophisticated platform for proteomic PTM research, equipped not only with a knowledge base of manually curated multi-type modification data, but also with four fully developed, in-depth data mining tools (Li H, et al., 2009).
(8) HistoneHits: a database for histone mutations and their phenotypes. This database combines assay results (phenotypes) with information about sequences, structures, post-translational modifications, and evolutionary conservation (Huang H, et al., 2009).
(9) PEpiD: a prostate epigenetic database in mammals. The Prostate Epigenetic Database archives the three extensively characterized epigenetic mechanisms DNA methylation, histone modification, and microRNA implicated in prostate cancer of human, mouse, and rat.(Shi J, et al., 2013).2. Histone Protein databases.
(1) The Histone Database: The Histone Sequence Database is a curated collection of sequences and structures of histones and non-histone proteins containing histone folds, assembled from major public databases (Mariño-Ramírez, et al., 2011).
(2) ChromDB: the chromatin database, displays chromatin-associated proteins, including RNAi-associated proteins, for a broad range of organisms.(Gendler, et al., 2008).
1. Acetylation Databases.
(1) PhosphoSitePlus: (PSP) is a comprehensive, manually curated and interactive resource on post-translational modifications (PTM). PSP contains encompasses 130000 non-redundant modification sites, manily on phosphorylation, ubiquitinylation and acetylation (Hornbeck, et al., 2004).
(2) g2pDB: A Database Mapping Protein Post-Translational Modifications to Genomic Coordinates. The original data comes mainly from published studies, many of which involve the investigation of post-translational modification acceptor site assignments, e.g., phosphorylation, ubiquitination, SUMOylation, acetylation, and N-linked glycosylation sites. (Keegan S, et al., 2016).
(3) dbPTM 2.0: integrates experimentally verified PTMs from several databases, and to annotate the predicted PTMs on Swiss-Prot proteins , 2,071 acetylation sites were included while most of which were N-alpha-terminal ones (Lee TY, et al., 2006) .
(4) HPRD release 9: HPRD currently contains information for 16,972 PTMs which belong to various categories such as acetylation (259), while phosphorylation (10,858), dephosphorylation (3,118) and glycosylation (1,860) form the majority of the annotated PTMs. At least one enzyme responsible for PTMs has been annotated for 8,960 PTMs, which resulted in the documentation of 7,253 enzyme - substrate relationships (Keshava Prasad, et al., 2009).2. Prediction of acetylation sites.
(2) NetAcet 1.0: a web server predicts N-terminal acetylation sites. The method was trained on yeast data but, as mentioned in the article describing the method, it obtains similar performance values on mammalian substrates acetylated by NatA orthologs (Kiemer, et al., 2005).
(3) PredMod: combine experimental methods with clustering analysis of protein sequences to predict protein acetylation based on the sequence characteristics of acetylated lysines within histones (Basu, et al., 2009).
(4) LysAcet 1.1: prediction of lysine acetylation by support vector machines (Li,, et al., 2009).
1. Prediction of Methylation sites.
(5) Methy SVMIACO (The Methy SVMIACO can be acquired freely on request from the authors): Identification of protein methylation sites by coupling improved ant colony optimization algorithm and support vector machine (Li, et al., 2011).