Neeraj J. Agrawal and Sandeep Kumar contributed equally to this work.
Aggregation in protein-based biotherapeutics: Computational studies and tools to identify aggregation-prone regions†
Article first published online: 24 JUL 2011
Copyright © 2011 Wiley-Liss, Inc.
Journal of Pharmaceutical Sciences
Volume 100, Issue 12, pages 5081–5095, December 2011
Total views since publication: 2033
How to Cite
Agrawal, N. J., Kumar, S., Wang, X., Helk, B., Singh, S. K. and Trout, B. L. (2011), Aggregation in protein-based biotherapeutics: Computational studies and tools to identify aggregation-prone regions. J. Pharm. Sci., 100: 5081–5095. doi: 10.1002/jps.22705
- Issue published online: 24 OCT 2011
- Article first published online: 24 JUL 2011
- Manuscript Accepted: 24 JUN 2011
- Manuscript Revised: 10 JUN 2011
- Manuscript Received: 14 APR 2011
- biophysical models;
Because of their large, complex, and conformationally heterogeneous structures, biotherapeutics are vulnerable to several physicochemical stresses faced during the various processing steps from production to administration. In particular, formation of protein aggregates is a major concern. The greatest risk with aggregates arises from their potential to give rise to immunogenic reactions. Hence, it is desirable to bring forward biotherapeutic drug candidates that show low propensity for aggregation and, thus, improved developability. Here, we present a comprehensive review of computational studies into the sequence and structural factors that underpin protein and peptide aggregation. A number of computational approaches have been applied including coarse grain models, atomistic molecular simulations, and bioinformatic approaches. These studies have focused on both the mechanism of aggregation and the identification of potential aggregation-prone sequence and structural motifs. We also survey the computational tools available to predict aggregation in therapeutic proteins. The findings communicated here provide insights that could be potentially useful in the rational design of therapeutic candidates with not only high potency and specificity but also improved stability and solubility. These sequence–structure-based approaches can be applied to both novel as well as follow-on biotherapeutics. © 2011 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 100:5081–5095, 2011