ArticlePLoS computational biology2018
Population-specific design of de-immunized protein biotherapeutics.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The trial behind it
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Who cites it
11 citing papers in PubMed, 19 citations in OpenAlex.
- Antimicrobial peptides in the era of resistance: integrating AI-driven design, host-microbe interactions, and nanotechnological delivery.Frontiers in microbiology · 2026Review
- Robust genome and cell engineering via in vitro and in situ circularized RNAs.Nature biomedical engineering · 2025Article
- A bispecific CD40 agonistic antibody allowing for antibody-peptide conjugate formation to enable cancer-specific peptide delivery, resulting in improved T proliferation and anti-tumor immunity in mice.Nature communications · 2024Article
- Machine learning for functional protein design.Nature biotechnology · 2024Review
- Recent Advances in Pharmaceutical Design: Unleashing the Potential of Novel Therapeutics.Current pharmaceutical biotechnology · 2024Review
- Accelerating therapeutic protein design with computational approaches toward the clinical stage.Computational and structural biotechnology journal · 2023Review
- Improved prediction of HLA antigen presentation hotspots: Applications for immunogenicity risk assessment of therapeutic proteins.Immunology · 2021Article
- Mitigation of T-cell dependent immunogenicity by reengineering factor VIIa analogue.Blood advances · 2019Article
- Structural and Dynamic Properties of Allergen and Non-Allergen Forms of Tropomyosin.Structure (London, England : 1993) · 2018Article
- Anti-Drug Antibodies: Emerging Approaches to Predict, Reduce or Reverse Biotherapeutic Immunogenicity.Antibodies (Basel, Switzerland) · 2018Review
- FoldX as Protein Engineering Tool: Better Than Random Based Approaches?Computational and structural biotechnology journal · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Immunogenicity is a major problem during the development of biotherapeutics since it can lead to rapid clearance of the drug and adverse reactions. The challenge for biotherapeutic design is therefore to identify mutants of the protein sequence that minimize immunogenicity in a target population whilst retaining pharmaceutical activity and protein function. Current approaches are moderately successful in designing sequences with reduced immunogenicity, but do not account for the varying frequencies of different human leucocyte antigen alleles in a specific population and in addition, since many designs are non-functional, require costly experimental post-screening. Here, we report a new method for de-immunization design using multi-objective combinatorial optimization. The method simultaneously optimizes the likelihood of a functional protein sequence at the same time as minimizing its immunogenicity tailored to a target population. We bypass the need for three-dimensional protein structure or molecular simulations to identify functional designs by automatically generating sequences using probabilistic models that have been used previously for mutation effect prediction and structure prediction. As proof-of-principle we designed sequences of the C2 domain of Factor VIII and tested them experimentally, resulting in a good correlation with the predicted immunogenicity of our model.
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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.