ArticleBriefings in bioinformatics2026
An intrinsic sequence-structural profile for mRNA-delivered therapeutic antibodies.
Article in Briefings in bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
4 authors.
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Abstract
The mRNA technology represents a paradigm shift for the biopharmaceutical industry because in vivo delivery of antibody-based therapeutics can expand their clinical applications. Moreover, the mRNA delivery shifts the burden of assuring CMC (chemistry, manufacturing, and control) to the mRNA molecule. However, in vivo developability issues such as intracellular expression, proper protein folding, secretion into extracellular milieu, degradation in physiological conditions, poly-specificity, immunogenicity, safety, efficacy, and pharmacology can still pose significant barriers to the success of these products. Here, we have leveraged insights from the sequence-structural properties of the variable regions (Fvs) from the marketed biotherapeutics to build a medicine-likeness profile for the mRNA-delivered biotherapeutics. Our dataset consists of 122 unique Fvs from 117 marketed biotherapeutics (as of February 2024) and was systematically evaluated using 9 nonredundant sequence and structural parameters to capture a holistic view of developability attributes relevant to in vivo performance of mRNA-delivered antibody therapeutics. To ensure robustness, 25 antibodies that failed to reach approval due to developability issues, as well as those withdrawn from the market post approval, were included as controls. Our findings highlight a complementary relationship between sequence- and structure-based characteristics, leading us to develop a combined scoring system. This integrated "medicine-likeness" profile enables early-stage in silico assessments of mRNA-delivered therapeutic antibody candidates, offering a valuable tool for researchers to predict and optimize their in vivo developability.
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