Predictive tools for stabilization of therapeutic proteins.
Monoclonal antibodies represent the fastest growing class of pharmaceuticals. A major problem, however, is that the proteins are susceptible to aggregation at the high concentration commonly used during manufacturing and storage. Our recent publication describes a technology based on molecular simulations to identify aggregation-prone regions of proteins in silico. The technology, called spatial aggregation propensity (SAP), identifies hot-spots for aggregation based on the dynamic exposure of spatially-adjacent hydrophobic amino acids. Monoclonal antibodies (mAbs) in which patches with high-SAP scores are changed to patches with significantly reduced SAP scores via a single mutation are more stable than wild type, thus validating the SAP method for mapping aggregation-prone regions on proteins. We propose that the SAP technology will be useful for protein stabilization, and as a screening tool to bridge discovery and development of protein-based therapeutics by a rational assessment of the developability of candidate protein drugs.
Voynov
Vladimir
V
Massachusetts Institute of Technology, Chemical Engineering, Cambridge, MA, USA.
Chennamsetty
Naresh
N
Kayser
Veysel
V
Helk
Bernhard
B
Trout
Bernhardt L
BL
D000465:Algorithms; D020816:Amino Acid Motifs / Q000235:genetics*; D000818:Animals; D000911:Antibodies, Monoclonal / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism; D001499:Bayes Theorem; D019295:Computational Biology; D006801:Humans; D007128:Immunoglobulin Fragments / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism; D055503:Protein Multimerization / Q000235:genetics; D055550:Protein Stability; D017433:Protein Structure, Secondary; D012984:Software
D000911:Antibodies, Monoclonal; D007128:Immunoglobulin Fragments