Post-Translational Protein Modifications of Rare and Unconventional Types: Implications in Functions and Diseases
Bibliographic record
Abstract
Protein post-translational modification (PTM) occurs following their biosynthesis and is a key cellular event that defines their ultimate functional properties. It is an important control mechanism for display of biological functions of proteins often in a profound manner. It may switch on or off a protein's function. Several studies have been conducted to understand their mechanisms, physiological pathways and functional properties. PTMs have been shown to alter structural, conformational and physicochemical properties of proteins. So far a variety of protein modifications have been detected in physiological systems. These involve covalent modifications of amino acids via their side chains, backbone peptide bonds and terminal moieties. Following PTM, proteins may become (a) pathologically toxic, (b) biologically active or inactive, (c) more or less susceptible to proteolytic processing, (d) increasingly/decreasingly bound to its partner protein/s, or (e) modified with altered protease activities. These changes may affect pathways linked to cell signaling/transduction, trafficking, storing, expression, binding and/or affinity. Any of these events may be linked to metabolic, growth and/or chronic dysfunctions with serious health consequences that may include cancer, cardiovascular disease, stroke, viral/bacterial/parasite infections, inflammation, thrombosis, diabetes; central nervous system related conditions. Some of the modifications are more prevalent physiologically and widely studied. However, in recent years additional PTMs have been described that are less common. These include glypiation, neddylayion, siderophorylation, sumoylation, AMPylation, Cholesteroylation and others which are also important. This manuscript provides a comprehensive review of these rare and unconventional types of protein modifications and their functional implications to health, metabolism and disease conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".