Generate Biomedicines Demonstrates a Novel Method of Reducing Immunogenicity through Protein Re-surfacing
Generate Biomedicines has announced that it has published data in the peer-reviewed journal Frontiers in Immunology that demonstrates the power of the company’s technology platform to generate re-surfaced proteins, which may provide a means to creating novel therapies for diseases with limited therapeutic options.
The study showed that the company’s approach to computational protein design was able to generate highly engineered E. coli L-Asparaginase (ASN) variants that maintain enzymatic function while significantly reducing binding to anti-drug antibodies and alleviating hypersensitivity responses in an animal model. By re-surfacing proteins, Generate Biomedicines may be able to reduce the effects of pre-existing immunity to protein-based therapies.
“Proteins are the machines of biology – the motors, the sensors – that make everything go. We are now engineering these machines to drive a desired biological task, potentially to treat a host of diseases,” noted Mike Nally, Generate’s Chief Executive Officer. “These data are further testament to the value of our integrated machine learning and wet-lab approach. This study highlights the potential of protein design in creating novel therapeutics and is part of our effort to design therapeutics with reduced immune response.”
“The optimal use of many biotherapeutics is restricted by anti-drug antibodies and hypersensitivity responses, which can affect potency and the ability to administer treatment for patients in need. Our ability to re-surface proteins represents an approach to help prevent the negative effects of anti-drug antibodies; we believe the resurfacing approach will be generalizable and may facilitate the development of new treatments for which additional options are urgently needed,” commented Alex Snyder, M.D., Generate’s Chief Medical Officer.
In the past, protein engineering has been costly as well as time- and labor-intensive and had limited capacity. The efficient and effective computational design of therapeutic proteins in this study has recently become feasible due to simultaneous innovations in computational processing power, machine learning approaches, and high-throughput methods for producing and evaluating novel proteins. Previous attempts to modify ASN using traditional approaches resulted in mutants with up to eight modifications, according to a 2014 article in The Journal of Biological Chemistry. In this study, however, the authors demonstrate the generation of functional ASNs with up to 58 mutations. These high levels of mutations represent a significant advancement in our ability to design complex proteins to meet multiple objectives, such as maintenance of function and reduction in immunogenicity.
Because protein re-surfacing has many potential applications in oncology, ASN, used in standard-of-care regimens for Acute Lymphoblastic Leukemia (ALL), was selected as a clinically relevant biotherapeutic. Its use is critical to achieving an optimal clinical response, but is often limited due to the body’s immune response against it in the form of anti-drug antibodies (ADAs). Generate partnered with researchers at Dana-Farber Cancer Institute to assess the impact of re-surfacing on ADAs from ALL patients and demonstrated significantly reduced binding. This re-surfacing approach could be used to develop other novel protein treatment options for proteins hindered by these unwanted immune responses in patients.
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