2023/04/12 by Yuwei Zhou, Ziru Huang, Yushu Gou +5 · 1 voice
Medicine · Biochemistry, Genetics and Molecular Biology · #Monoclonal and Polyclonal Antibodies Research #Protein purification and stability #vaccines and immunoinformatics approaches
paper · pdf · doi:10.1093/abt/tbad007
openalex publication_date 2023/04/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/05/21
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 in silico evaluation of the light-chain amyloidogenic risk to ensure the safety of antibody therapeutics under clinical development. A web server is freely available at http://i.uestc.edu.cn/AB-Amy/.