Evidence map›Paper›PMID 41129276›Full record

ReviewThe FEBS journal2026

Artificial lipidation of proteins and peptides: from mechanism to clinical applications.

Jiaming Mu, Emily Vong, Sheiliza Carmali

Abstract readReview
In one paragraph

Review in The FEBS journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Recombinant Protein Drugs: A 2025 Update.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2026
    Review
  4. Review
  5. Review
  6. Article
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

3 authors.

Jiaming MuSchool of Pharmacy, Queen's University Belfast, UK.
Emily VongSchool of Pharmacy, Queen's University Belfast, UK.
Sheiliza CarmaliSchool of Pharmacy, Queen's University Belfast, UK.ORCID 0000-0003-3436-4745

Funding

Queen's University/China Scholarship Council PhD Scholarship
6 · The paper itself

Abstract

The landscape of modern medicine has been transformed by protein-based therapeutics, offering targeted treatments for complex disorders with remarkable specificity and efficacy. However, these biologics face significant limitations in clinical settings, including rapid clearance, vulnerability to enzymatic degradation, poor absorption across biological membranes and inefficient distribution within target tissues. Artificial lipidation provides an innovative solution to these challenges, by the deliberate attachment of lipid groups to proteins and peptide structures. This biomimetic approach harnesses principles observed in natural post-translational modifications to create therapeutics with superior pharmacological profiles. By strategically incorporating lipid moieties, researchers can significantly prolong circulation half-life through albumin binding, protect against proteolytic breakdown, facilitate cellular uptake, customize pharmacokinetic parameters and enhance tissue-specific targeting. This Review provides a comprehensive analysis of current lipidation technologies, contrasting covalent modification strategies with noncovalent complexation approaches. We examine the molecular mechanisms underlying the therapeutic benefits, survey successful clinical applications and explore emerging opportunities across diverse therapeutic areas. Through this analysis, we offer insights to guide rational design decisions for developing optimized lipidated biotherapeutics with enhanced clinical performance.

Indexed as

LipidsPeptidesProteinsAnimalsHumansProtein Processing, Post-TranslationalLipidsPeptidesProteinsalbumin bindingdrug deliveryhalf‐life extensionprotein lipidationtherapeutic peptides

Identifiers

PMID41129276
PMCPMC12958104

What Socratic 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 Socratic graph.