Investigating Protein Aggregation Mechanism and Evaluating Mutational Strategies to Reduce Aggregate Formation
Costanzo, Joseph, Chemical Engineering - School of Engineering and Applied Science, University of Virginia
Fernandez, Erik, Department of Chemical Engineering, University of Virginia
Non-native protein aggregation is a critical problem for biopharmaceuticals as it can compromise the biological activity and/or elicit an undesired immune response. Also, non-native aggregation can lead to amyloidosis, commonly associated with several neurodegenerative diseases. Thus, understanding the cause(s) of aggregation and developing tools or strategies to prevent aggregation are critical to improving human health.
A theoretical evaluation of mutational strategies that were intended to reduce protein aggregation by 1) conformationally stabilizing a single domain, 2) a domain interface, or 3) reducing the intrinsic aggregation propensity (IAP) of sub-sequences was conducted using the multi-domain protein, human γD crystallin (γD-crys). The IAP is defined here as the reactivity of sub-sequences to form intermolecular contacts that stabilize an aggregated state. The protein design program, RosettaDesign, and several empirical, sequence-based aggregation predictors were implemented to identify candidate variants, and nine variants were characterized experimentally. Afterwards, the effectiveness of the mutational strategies and computational design algorithms was assessed.
Given that only a small fraction of protein sequences are capable of folding, the observation that 3 of 9 candidate variants proved to be less aggregation-prone than wild type demonstrates promise for this general approach. The results suggested the IAP is another molecular property beyond conformational stability that needs to be considered in such protein design efforts. Further, each mutational strategy showed potential for deterring aggregation, and the computational algorithms demonstrated an a priori ability to identify aggregation-resistant variants for experimental evaluation. Improved success rates could make such design tools central to development of new biopharmaceuticals.
This work also utilized experimental and computational approaches to investigate the aggregation mechanism of γD-crys and A4V-human superoxide dismutase-1 (A4V-hSOD1), an hSOD1 variant associated with amyotrophic lateral sclerosis (ALS). For γD-crys, the aggregation of three variants displaying different aggregation behavior were examined relative to wild type using hydrogen-deuterium exchange with mass spectrometry (HX-MS). The more aggregation-resistant variants, H22T and S130P, formed flexible, less-structured aggregates; however, a more aggregation-prone variant, S130T, and wild type formed well-structured, amyloid-like aggregates. A potential aggregation contact within residues N125-L133 was identified both computationally and experimentally for all γD-crys species tested.
RosettaDesign was also utilized to investigate the aggregation mechanism of A4V-hSOD1 by identifying residues that could abolish much of the aggregation induced by the A4V variant. An intra-domain steric clash between residue F20 and V4 was observed in crystal structures of A4V-hSOD1, and was hypothesized to destabilize the protein and thereby instigate aggregation. RosettaDesign and the aggregation predictors identified F20G and F20A as candidate variants that could prevent the clash, and improve the conformational stability and/or the aggregation propensity of A4V-hSOD1. Experimental results showed F20A and F20G variants could indeed restabilize A4V-hSOD1 and reduce its aggregation. This result shows that eliminating the intra-domain steric clash is effective in reducing A4V-hSOD1 aggregation. Further, the correlation between computational design and experimental results demonstrates the potential of using these design algorithms to investigate protein aggregation mechanisms.
PHD (Doctor of Philosophy)
Biochemical engineering, Protein engineering, Protein thermodynamic stability, Protein aggregation, Protein computational design
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