ArticleAntibody therapeutics2023
AB-Amy: machine learning aided amyloidogenic risk prediction of therapeutic antibody light chains.
Article in Antibody therapeutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.
What it found
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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.
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.
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Who cites it
9 citing papers in PubMed, 16 citations in OpenAlex.
- Enhancing polyreactivity prediction of preclinical antibodies through fine-tuned protein language models.Journal of pharmaceutical analysis · 2025Article
- Investigating Local Sequence-Structural Attributes of Amyloidogenic Light Chain Variable Domains.Proteins · 2025Article
- An updated AL-base reveals ranked enrichment of immunoglobulin light chain variable genes in AL amyloidosis.Amyloid : the international journal of experimental and clinical investigation : the official journal of the International Society of Amyloidosis · 2025Article
- Clone-specific residue changes at multiple positions are associated with amyloid formation by antibody light chains.Frontiers in immunology · 2025Article
- Molecular dynamics and machine learning stratify motion-dependent activity profiles of S-layer destabilizing nanobodies.PNAS nexus · 2024Article
- An updated AL-Base reveals ranked enrichment of immunoglobulin light chain variable genes in AL amyloidosis.bioRxiv : the preprint server for biology · 2024Article
- DOTAD: A Database of Therapeutic Antibody Developability.Interdisciplinary sciences, computational life sciences · 2024Article
- Review
- ACPPfel: Explainable deep ensemble learning for anticancer peptides prediction based on feature optimization.Frontiers in genetics · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Over 120 FDA-approved antibody-based therapeutics are used to treat a variety of diseases.However, many candidates could fail because of unfavorable physicochemical properties. Light-chain amyloidosis is one form of aggregation that can lead to severe safety risks in clinical development. Therefore, screening candidates with a less amyloidosis risk at the early stage can not only save the time and cost of antibody development but also improve the safety of antibody drugs. In this study, based on the dipeptide composition of 742 amyloidogenic and 712 non-amyloidogenic antibody light chains, a support vector machine-based model, AB-Amy, was trained to predict the light-chain amyloidogenic risk. The AUC of AB-Amy reaches 0.9651. The excellent performance of AB-Amy indicates that it can be a useful tool for the
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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.