Dataset Information

Pupylation sites on SARS-CoV-2 N

ABSTRACT: As a test for the effectiveness of SPIDER with RNA-protein pairs, we examined SARS-CoV-2 Nucleoprotein. We used Nucleoprotein and specific biotin-RNA to validate the efficiency of spider capturing N and analysised the pupylation sites of N protein by mass spectrometry

ORGANISM(S): Severe Acute Respiratory Syndrome Coronavirus 2

SUBMITTER: Shengce Tao

PROVIDER: PXD026518 | iProX | Fri Jun 04 00:00:00 BST 2021

REPOSITORIES: iProX

ACCESS DATA

Publications

Specific pupylation as IDEntity reporter (SPIDER) for the identification of protein-biomolecule interactions.

Jiang He-Wei HW Chen Hong H Zheng Yun-Xiao YX Wang Xue-Ning XN Meng Qingfeng Q Xie Jin J Zhang Jiong J Zhang ChangSheng C Xu Zhao-Wei ZW Chen Zi-Qing ZQ Wang Lei L Kong Wei-Sha WS Zhou Kuan K Ma Ming-Liang ML Zhang Hai-Nan HN Guo Shu-Juan SJ Xue Jun-Biao JB Hou Jing-Li JL Liu Zhe-Yi ZY Niu Wen-Xue WX Wang Fang-Jun FJ Wang Tao T Li Wei W Wang Rui-Na RN Dang Yong-Jun YJ Czajkowsky Daniel M DM Pei JianFeng J Dong Jia-Jia JJ Tao Sheng-Ce SC

Science China. Life sciences 20230414 8

Protein-biomolecule interactions play pivotal roles in almost all biological processes. For a biomolecule of interest, the identification of the interacting protein(s) is essential. For this need, although many assays are available, highly robust and reliable methods are always desired. By combining a substrate-based proximity labeling activity from the pupylation pathway of Mycobacterium tuberculosis and the streptavidin (SA)-biotin system, we developed the Specific Pupylation as IDEntity Repor ...[more]

PMID: 37059927

Similar Datasets

Project description:Schmitz2014 - RNA triplex formation The model is parameterized using the parameters for gene CCDC3 from Supplementary Table S1. The two miRNAs which form the triplex together with CCDC3 are miR-551b and miR-138. This model is described in the article: Cooperative gene regulation by microRNA pairs and their identification using a computational workflow. Schmitz U, Lai X, Winter F, Wolkenhauer O, Vera J, Gupta SK. Nucleic Acids Res. 2014 Jul; 42(12): 7539-7552 Abstract: MicroRNAs (miRNAs) are an integral part of gene regulation at the post-transcriptional level. Recently, it has been shown that pairs of miRNAs can repress the translation of a target mRNA in a cooperative manner, which leads to an enhanced effectiveness and specificity in target repression. However, it remains unclear which miRNA pairs can synergize and which genes are target of cooperative miRNA regulation. In this paper, we present a computational workflow for the prediction and analysis of cooperating miRNAs and their mutual target genes, which we refer to as RNA triplexes. The workflow integrates methods of miRNA target prediction; triplex structure analysis; molecular dynamics simulations and mathematical modeling for a reliable prediction of functional RNA triplexes and target repression efficiency. In a case study we analyzed the human genome and identified several thousand targets of cooperative gene regulation. Our results suggest that miRNA cooperativity is a frequent mechanism for an enhanced target repression by pairs of miRNAs facilitating distinctive and fine-tuned target gene expression patterns. Human RNA triplexes predicted and characterized in this study are organized in a web resource at www.sbi.uni-rostock.de/triplexrna/. This model is hosted on BioModels Database and identified by: BIOMD0000000530. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Dataset Information

Pupylation sites on SARS-CoV-2 N

Publications

Specific pupylation as IDEntity reporter (SPIDER) for the identification of protein-biomolecule interactions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets