Design of therapeutic proteins with enhanced stability

By Naresh Chennamsetty, V. Voynov, Veysel Kayser, B. Helk, B. Trout. 2009

553 citations recorded by the source corpus.

Therapeutic proteins such as antibodies constitute the most rapidly growing class of pharmaceuticals for use in diverse clinical settings including cancer, chronic inflammatory diseases, kidney transplantation, cardiovascular medicine, and infectious diseases. Unfortunately, they tend to aggregate when stored under the concentrated conditions required in their usage. Aggregation leads to a decrease in antibody activity and could elicit an immunological response. Using full antibody atomistic molecular dynamics simulations, we identify the antibody regions prone to aggregation by using a technology that we developed called spatial aggregation propensity (SAP). SAP identifies the location and size of these aggregation prone regions, and allows us to perform target mutations of those regions to engineer antibodies for stability. We apply this method to therapeutic antibodies and demonstrate the significantly enhanced stability of our mutants compared with the wild type. The technology described here could be used to incorporate developability in a rational way during the screening of antibodies in the discovery phase for several diseases.

Subfields: Molecular Biology, Radiology, Nuclear Medicine and Imaging

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Citations in the corpus

RosettaAntibodyDesign (RAbD): A general framework for computational antibody design (2017, methodology): “General protein design methods have been applied to affinity maturation[29-31], improving stability[32-34], humanization[35,36], and the design of phage/yeast display libraries[37-40].”
The CamSol method of rational design of protein mutants with enhanced solubility. (2015, methodology): “In this work, we build on recent advances in understanding the fundamental principles of protein aggregation [35–37] and of protein solubility [38–41], in particular of antibodies [9,33,34,42,43], to develop the CamSol method to design rationally protein variants with enhanced solubility.”
Computational Protein Design with Explicit Consideration of Surface Hydrophobic Patches (2011, background): “Chennamsetty et al 42 recently used a spatial aggregation propensity score that gives positions with exposed hydrophobic neighbors a high score to increase the solubility of two antibodies.”