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Remediating agitation-induced antibody aggregation by eradicating exposed hydrophobic motifs
Therapeutic antibodies must encompass drug product suitable attributes to be commercially marketed. An undesirable antibody characteristic is the propensity to aggregate. Although there are computational algorithms that predict the propensity of a protein to aggregate from sequence information alone...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4622659/ https://www.ncbi.nlm.nih.gov/pubmed/25484048 http://dx.doi.org/10.4161/mabs.36252 |
Sumario: | Therapeutic antibodies must encompass drug product suitable attributes to be commercially marketed. An undesirable antibody characteristic is the propensity to aggregate. Although there are computational algorithms that predict the propensity of a protein to aggregate from sequence information alone, few consider the relevance of the native structure. The Spatial Aggregation Propensity (SAP) algorithm developed by Chennamsetty et. al. incorporates structural and sequence information to identify motifs that contribute to protein aggregation. We have utilized the algorithm to design variants of a highly aggregation prone IgG(2). All variants were tested in a variety of high-throughput, small-scale assays to assess the utility of the method described herein. Many variants exhibited improved aggregation stability whether induced by agitation or thermal stress while still retaining bioactivity. |
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