Abstract
The pathways of protein post-translational modifications (PTMs) have been shown to play particularly important roles for almost any biological process. Identification of PTM substrates along with information on the exact sites is fundamental for fully understanding or controlling biological processes. Alternative computational strategies would help to annotate PTMs in a high-throughput manner. Traditional algorithms are suited for identifying the common organisms and tissues that have a complete PTM atlas or extensive experimental data. While annotation of rare PTMs in most organisms is a clear challenge. In this work, to this end we have developed a novel homology-based pipeline named PTMProber that allows identification of potential modification sites for most of the proteomes lacking PTMs data. Cross-promotion E-value (CPE) as stringent benchmark has been used in our pipeline to evaluate homology to known modification sites. Independent-validation tests show that PTMProber achieves over 58.8% recall with high precision by CPE benchmark. Comparisons with other machine-learning tools show that PTMProber pipeline performs better on general predictions. In addition, we developed a web-based tool to integrate this pipeline at http://bioinfo.ncu.edu.cn/PTMProber/index.aspx. In addition to pre-constructed prediction models of PTM, the website provides an extensional functionality to allow users to customize models.
Highlights
Search Tool)[8] queries and align post-translational modifications (PTMs) sites of known proteomes to identify the putative sites in Ectocarpus siliculosus
PTMProber is a homology-based pipeline that is first of its kind to identify PTM sites
M2 represents PTMProber M2 model that constructed by all collected PTM data.) for each type of PTMs including phosphorylation, acetylation, ubiquitination, methylation and sumoylation on Rattus norvegicus, Gallus gallus and Bos taurus
Summary
Search Tool)[8] queries and align PTM sites of known proteomes to identify the putative sites in Ectocarpus siliculosus. In PTMProber V1.0, we have collected PTM data from several sources[11,12], and constructed general prediction models for five PTM types including phosphorylation (serine, threonine and tyrosine), acetylation (lysine), ubiquitination (lysine), methylation (lysine and arginine), sumoylation (lysine) that were used for cellular conditions of 340 organisms. It is noted, that using the current pre-constructed models users cannot correlate prediction with other particular PTM; the cellular conditions of query proteome come not from the 340 organisms. PTMProber is freely available at http://bioinfo.ncu.edu.cn/PTMProber/index.aspx that provides a valuable pipeline for biologists to predict PTM sites up to the whole proteome level
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