Periodic Reporting for period 4 - AutoCAb (Automated computational design of site-targeted repertoires of camelid antibodies)
Periodo di rendicontazione: 2023-07-01 al 2023-12-31
Dozens of antibodies are in routine clinical use for treating life-threatening diseases. The conventional route to antibody discovery and optimization relies on animal immunization and optimisation of improved variants. These methods are powerful, and yet, they are costly, time consuming, and ultimately rely on trial-and-error. The reason we still rely on inefficient processes despite their low scalability is a lack of control over biomolecular structure and function. The AutoCAb project is dedicated to developing a new computational strategy for designing effective antibodies while increasing our understanding and control over biomolecular recognition, which is one of the most fundamental aspects of protein activity. The AutoCAb project develops cutting-edge computational and experimental methods that allow designing, for the first time, millions of antibodies or other functional proteins, and synthesizing all of these antibodies accurately and economically. Finally, selection experiments followed by next-generation sequencing allow us to monitor which designs bind their targets and to use advanced machine-learning methods to infer rules that would improve the chances of success in the next round of experiments. The major goals of AutoCAb have been achieved including several papers and patent filings that describe the envisioned approaches and their application to antibodies, enzymes, and fluorescent proteins. The methods developed in AutoCAb enable, for the first time, the design of large and very effective libraries of functional proteins. These libraries comprise protein variants that exhibit superior stability and activity to the natural (or engineered) starting point protein and enable efficient and effective optimisation of biomedically and biotechnologicallly important proteins, such as enzymes and antibodies.
AutoCAb is a highly interdisciplinary project developing new computational and experimental methods for effective design and implementation of protein libraries. The main results of the project have been published over the past year, including a new method for designing and synthesising vast libraries of functional proteins, applied to enzymes and fluorescent proteins (Lipsh-Sokolik Science 2023; Weinstein Nature Commun 2023), economical design and implementation of protein variant libraries (Hoch bioRxiv 2023) and a reliable method for co-optimising antibody stability and humanness (Tennenhouse Nature Biomed Eng 2023). These methods take us a major step towards the ultimate goal of protein design of a high level of control over protein activity. We have also implemented these methods as web servers or in freely accessible source code, enabling other researchers to use them. Using these methods, we and others can quickly and effectively optimise enzymes for applications in green chemistry, therapeutic antibodies and vaccine immunogens.
Several methods developed as part of AutoCAb have raised significant interest from pharmaceutical and chemical industries, and the lab has licensed the methods to two start up companies, Scala Biodesign and Plantae Biosciences, to commercialise the methods.
Several methods developed as part of AutoCAb have raised significant interest from pharmaceutical and chemical industries, and the lab has licensed the methods to two start up companies, Scala Biodesign and Plantae Biosciences, to commercialise the methods.
The AutoCAb project is the first of its kind to design massive repertoires comprising millions of functional proteins. The papers published within the context of the project allow us and others to quickly and effectively optimise different types of proteins with uses in green chemistry and biomedical applications. In addition, we developed a reliable and general method for co-optimising antibody stability and humanness (Tennenhouse Nature Biomed Eng 2023), which has been one of the longest-standing challenges in antibody engineering (since the early 1980's). In short, the AutoCAb project has advanced us an important step towards reliable and entirely rational control over biomolecular function.