ArticleBioinformatics (Oxford, England)2018
ADPredict: ADP-ribosylation site prediction based on physicochemical and structural descriptors.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 27 citations in OpenAlex.
- BTAF1: a key regulator of DNA end resection and predictor of chemotherapy sensitivity in gastric cancer.Cell death and differentiation · 2026Article
- PARP4 ADP-ribosylates PIDD1 to complete a phospho/SUMO/PAR-ylation cascade that orchestrates PIDDosome assembly.Science advances · 2026Article
- S-phase PARylation of microprotein RSMC enhances the function of Sororin in sister chromatid cohesion.The EMBO journal · 2026Article
- Mono-ADP-ribosylating PARP enzymes in cellular signaling and disease.Journal of cell science · 2025Review
- Nudix Hydrolase 13 Impairs the Initiation of Colorectal Cancer by Inhibiting PKM1 ADP-Ribosylation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- PARP12-mediated ADP-ribosylation contributes to breast cancer cell fate by regulating AKT activation and DNA-damage response.Cellular and molecular life sciences : CMLS · 2025Article
- The CYLD-PARP1 feedback loop regulates DNA damage repair and chemosensitivity in breast cancer cells.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Nudix hydrolase 23 post-translationally regulates carotenoid biosynthesis in plants.The Plant cell · 2024Article
- Article
- BTApep-TAT peptide inhibits ADP-ribosylation of BORIS to induce DNA damage in cancer.Molecular cancer · 2022Article
- PKD-dependent PARP12-catalyzed mono-ADP-ribosylation of Golgin-97 is required for E-cadherin transport from Golgi to plasma membrane.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Deficiency of PARP-1 and PARP-2 in the mouse uterus results in decidualization failure and pregnancy loss.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Identification of Novel Candidate Epitopes on SARS-CoV-2 Proteins for South America: A Review of HLA Frequencies by Country.Frontiers in immunology · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: ADP-ribosylation is a post-translational modification (PTM) implicated in several crucial cellular processes, ranging from regulation of DNA repair and chromatin structure to cell metabolism and stress responses. To date, a complete understanding of ADP-ribosylation targets and their modification sites in different tissues and disease states is still lacking. Identification of ADP-ribosylation sites is required to discern the molecular mechanisms regulated by this modification. This motivated us to develop a computational tool for the prediction of ADP-ribosylated sites. Results: Here, we present ADPredict, the first dedicated computational tool for the prediction of ADP-ribosylated aspartic and glutamic acids. This predictive algorithm is based on (i) physicochemical properties, (ii) in-house designed secondary structure-related descriptors and (iii) three-dimensional features of a set of human ADP-ribosylated proteins that have been reported in the literature. ADPredict was developed using principal component analysis and machine learning techniques; its performance was evaluated both internally via intensive bootstrapping and in predicting two external experimental datasets. It outperformed the only other available ADP-ribosylation prediction tool, ModPred. Moreover, a novel secondary structure descriptor, HM-ratio, was introduced and successfully contributed to the model development, thus representing a promising tool for bioinformatics studies, such as PTM prediction. Availability and implementation: ADPredict is freely available at www.ADPredict.net. Supplementary information: Supplementary data are available at Bioinformatics online.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.