Literature DB >> 30476509

Models for Antibody Behavior in Hydrophobic Interaction Chromatography and in Self-Association.

Max Hebditch1, Aisling Roche2, Robin A Curtis2, Jim Warwicker3.   

Abstract

Monoclonal antibodies (mAbs) form an increasingly important sector of the pharmaceutical market, and their behavior in production, processing, and formulation is a key factor in development. With data sets of solution properties for mAbs becoming available, and with amino acid sequences, and structures for many Fabs, it is timely to examine what features correlate with measured data. Here, previously published data for hydrophobic interaction chromatography and the formation of high molecular weight species are studied. Unsurprisingly, aromatic sidechain content of complementarity-determining regions (CDRs), underpins much of the variability in hydrophobic interaction chromatography data. However, this is not reflected in nonpolar solvent accessible surface enrichment at the antigen-combining site, consistent with a view in which hydrophobic interaction strength is dependent on curvature as well as on the extent of an interface. Sequence properties are also superior to surface-based structural properties in correlations with the high molecular weight species data. Combined length of CDRs is the most important factor, which could be an indication of flexibility that facilitates CDR-CDR interactions in mAb self-association. These observations couple to our understanding of protein physicochemical properties, laying the groundwork for improved developability models.
Copyright © 2019 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Keywords:  IgG antibody; biophysical model; biotechnology; computational biology; interactions; molecular modeling; physicochemical properties; protein aggregation; proteins; self-association

Mesh:

Substances:

Year:  2018        PMID: 30476509     DOI: 10.1016/j.xphs.2018.11.035

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  13 in total

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