Khater Shradha, Mohanty Debasisa
Bioinformatics Centre, National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India.
Bioinformatics Centre, National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India
Database (Oxford). 2015 Apr 29;2015:bav039. doi: 10.1093/database/bav039. Print 2015.
With the recent discoveries of novel post-translational modifications (PTMs) which play important roles in signaling and biosynthetic pathways, identification of such PTM catalyzing enzymes by genome mining has been an area of major interest. Unlike well-known PTMs like phosphorylation, glycosylation, SUMOylation, no bioinformatics resources are available for enzymes associated with novel and unusual PTMs. Therefore, we have developed the novPTMenzy database which catalogs information on the sequence, structure, active site and genomic neighborhood of experimentally characterized enzymes involved in five novel PTMs, namely AMPylation, Eliminylation, Sulfation, Hydroxylation and Deamidation. Based on a comprehensive analysis of the sequence and structural features of these known PTM catalyzing enzymes, we have created Hidden Markov Model profiles for the identification of similar PTM catalyzing enzymatic domains in genomic sequences. We have also created predictive rules for grouping them into functional subfamilies and deciphering their mechanistic details by structure-based analysis of their active site pockets. These analytical modules have been made available as user friendly search interfaces of novPTMenzy database. It also has a specialized analysis interface for some PTMs like AMPylation and Eliminylation. The novPTMenzy database is a unique resource that can aid in discovery of unusual PTM catalyzing enzymes in newly sequenced genomes. Database URL: http://www.nii.ac.in/novptmenzy.html
随着最近发现的在信号传导和生物合成途径中起重要作用的新型翻译后修饰(PTM),通过基因组挖掘来鉴定此类PTM催化酶已成为一个主要关注领域。与磷酸化、糖基化、SUMO化等众所周知的PTM不同,目前没有与新型和不寻常PTM相关的酶的生物信息学资源。因此,我们开发了novPTMenzy数据库,该数据库编目了参与五种新型PTM(即AMP化、消除化、硫酸化、羟基化和脱酰胺化)的实验表征酶的序列、结构、活性位点和基因组邻域信息。基于对这些已知PTM催化酶的序列和结构特征的全面分析,我们创建了隐马尔可夫模型概况,用于识别基因组序列中相似的PTM催化酶结构域。我们还创建了预测规则,将它们分组到功能亚家族中,并通过基于结构的活性位点口袋分析来解读其机制细节。这些分析模块已作为novPTMenzy数据库的用户友好搜索界面提供。它还具有针对AMP化和消除化等一些PTM的专门分析界面。novPTMenzy数据库是一种独特的资源,可有助于在新测序的基因组中发现不寻常的PTM催化酶。数据库网址:http://www.nii.ac.in/novptmenzy.html