Evidence map›Paper›PMID 29322920›Full record

ArticleBMC systems biology2017

Investigation and identification of functional post-translational modification sites associated with drug binding and protein-protein interactions.

Min-Gang Su, Julia Tzu-Ya Weng, Justin Bo-Kai Hsu, Kai-Yao Huang, Yu-Hsiang Chi, Tzong-Yi Lee

Open access · diamondAbstract read
In one paragraph

Article in BMC systems biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 9% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 52 citations in OpenAlex.

  1. Pooled it
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  17. Achieving a Deeper Understanding of Drug Metabolism and Responses Using Single-Cell Technologies.Drug metabolism and disposition: the biological fate of chemicals · 2023
    Review
  18. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Min-Gang SuDepartment of Computer Science and Engineering, Yuan Ze University, Taoyuan, 320, Taiwan.
Julia Tzu-Ya WengDepartment of Computer Science and Engineering, Yuan Ze University, Taoyuan, 320, Taiwan.
Justin Bo-Kai HsuDepartment of Medical Research, Taipei Medical University Hospital, Taipei, 110, Taiwan.
Kai-Yao HuangDepartment of Computer Science and Engineering, Yuan Ze University, Taoyuan, 320, Taiwan.
Yu-Hsiang ChiDepartment of Computer Science and Engineering, Yuan Ze University, Taoyuan, 320, Taiwan.
Tzong-Yi LeeDepartment of Computer Science and Engineering, Yuan Ze University, Taoyuan, 320, Taiwan. francis@saturn.yzu.edu.tw.
Yuan Ze University · TWMackay Memorial Hospital · TWTaipei Medical University Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProtein post-translational modification (PTM) plays an essential role in various cellular processes that modulates the physical and chemical properties, folding, conformation, stability and activity of proteins, thereby modifying the functions of proteins. The improved throughput of mass spectrometry (MS) or MS/MS technology has not only brought about a surge in proteome-scale studies, but also contributed to a fruitful list of identified PTMs. However, with the increase in the number of identified PTMs, perhaps the more crucial question is what kind of biological mechanisms these PTMs are involved in. This is particularly important in light of the fact that most protein-based pharmaceuticals deliver their therapeutic effects through some form of PTM. Yet, our understanding is still limited with respect to the local effects and frequency of PTM sites near pharmaceutical binding sites and the interfaces of protein-protein interaction (PPI). Understanding PTM's function is critical to our ability to manipulate the biological mechanisms of protein.

resultsIn this study, to understand the regulation of protein functions by PTMs, we mapped 25,835 PTM sites to proteins with available three-dimensional (3D) structural information in the Protein Data Bank (PDB), including 1785 modified PTM sites on the 3D structure. Based on the acquired structural PTM sites, we proposed to use five properties for the structural characterization of PTM substrate sites: the spatial composition of amino acids, residues and side-chain orientations surrounding the PTM substrate sites, as well as the secondary structure, division of acidity and alkaline residues, and solvent-accessible surface area. We further mapped the structural PTM sites to the structures of drug binding and PPI sites, identifying a total of 1917 PTM sites that may affect PPI and 3951 PTM sites associated with drug-target binding. An integrated analytical platform (CruxPTM), with a variety of methods and online molecular docking tools for exploring the structural characteristics of PTMs, is presented. In addition, all tertiary structures of PTM sites on proteins can be visualized using the JSmol program.

conclusionResolving the function of PTM sites is important for understanding the role that proteins play in biological mechanisms. Our work attempted to delineate the structural correlation between PTM sites and PPI or drug-target binding. CurxPTM could help scientists narrow the scope of their PTM research and enhance the efficiency of PTM identification in the face of big proteome data. CruxPTM is now available at http://csb.cse.yzu.edu.tw/CruxPTM/ .

Indexed as

Protein Interaction MappingProtein Processing, Post-TranslationalHumansModels, MolecularPharmaceutical PreparationsProtein BindingProteinsProtein Structure, TertiaryPharmaceutical PreparationsProteins

Identifiers

PMID29322920
PMCPMC5763307
OpenAlexW2780557617

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.