Evidence map›Paper›PMID 39543034›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

Advances in Prediction of Posttranslational Modification Sites Known to Localize in Protein Supersecondary Structures.

Pawel Pratyush, Dukka B Kc

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
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

2 authors.

Pawel PratyushComputer Science Department, Michigan Technological University, Houghton, MI, USA.
Dukka B KcComputer Science Department, Michigan Technological University, Houghton, MI, USA. dbkc@mtu.edu.

Funding

National Science Foundation #1564606National Science Foundation # 1901793
6 · The paper itself

Abstract

Posttranslational modifications (PTMs) play a crucial role in modulating the structure, function, localization, and interactions of proteins, with many PTMs being localized within supersecondary structures, such as helical pairs. These modifications can significantly influence the conformation and stability of these structures. For instance, phosphorylation introduces negative charges that alter electrostatic interactions, while acetylation or methylation of lysine residues affects the stability and interactions of alpha helices or beta strands. Given the pivotal role of supersecondary structures in the overall protein architecture, their modulation by PTMs is essential for protein functionality. This chapter explores the latest advancements in predicting sites for the five PTMs (phosphorylation, acetylation, glycosylation, methylation, and ubiquitination) known to be localized within supersecondary structures. The chapter highlights the recent advances in the prediction of these PTM sites, including the use of global contextualized embeddings from protein language models, integration of structural information, utilization of reliable positive and negative sites, and application of contrastive learning. These methodologies and emerging trends offer a roadmap for novel innovations in addressing PTM prediction challenges, particularly those linked to supersecondary structures.

Indexed as

Protein Processing, Post-TranslationalProteinsAcetylationComputational BiologyDatabases, ProteinGlycosylationHumansMethylationModels, MolecularPhosphorylationProtein ConformationSoftwareUbiquitinationProteins3D structureAcetylationContrastive learningGlycosylationPhosphorylationPosttranslational modificationProtein language modelSupersecondary structuretransformerUbiquitination

Identifiers

What OpenQuestion holds

Textmetadata
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.