Sarel Fleischman, PhD, Associate Professor, Department of Biomolecular Science, The Weizmann Institute
Sarel Fleischman, Ph.D., discusses the complexities associated with designing proteins. He explains that, in the past, the most reliable methods for designing optimal variances of proteins required vast amounts of previous experimentation data. He notes that obtaining the experimental data is labor intensive.
Dr. Fleischman's presentation details the opportunities for computation design strategies applied to antibodies. It is possible to use the structure of the target protein or an old model of the target protein towards optimization, which would eliminate the need for experimental data.
Evolution-Guided Atomistic Designs
The scope of research presented reveals a shared truth finding that atomistic calculations are not always reliable. To design and optimize complex large protein structures, the introduction of a newer hybrid strategy came into fruition. It uses experimental backbone conformations from the protein databank and sequence statistics to guide the evolution design process leading to the development of PROSS.
PROSS Stability Design (One Shot Design – Previously Used Mostly for Enzymes)
PROSS is a one-shot computational design methodology developed and was used primarily for enzymes before testing possible protein sequencing applications.
PROSS showcases its potential in establishing application values for some proteins, even some difficult-to-express proteins. Computational design can be highly instrumental for antibody engineers and may be able to address several problems within the process of sequencing proteins.
The researchers involved in the project noted that the stability design algorithms showcase possible uses towards many diverse non-industry applications. Consequently, the computational stability designs are now available via web portals designated for public access. The decision to provide public-acess to our stability design algorithms resulted in numerous mentions in trusted scientific publications.
Computational design technology in impressive applications studies including:
AbLIft: Improving Affinity and Stability Through v/L v/H Optimization
AbLIFT aims to optimize the specific interfaces formed by the light and heavy chains in the variable domain of antibodies. The researchers involved in the project chose this CDR domain region because:
These domain attributes make it very hard to optimize. In non-natural selection, achieving optimization is difficult, even with traditional methods. Subsequently, it was idealized that if we could unpack the methodology here, we could apply it to other variable domains. The results revealed a new network of high-density interactions, such as hydrogen bonding, which was previously inaccessible to conventional affinity maturation.
Conclusion
The focal point of the presentation, computation design, offers a full scope of possibilities in many diverse industries, including antibody engineering. AbLIFT, a method to optimize light and heavy chain interface designs, shows the potential for dramatic improvements in protein specification.
AbLIFT demonstrates the potential for new interaction networks which improve expression and affinity. AbLIFT also may hold opportunities for replacing the existing framework with alternative human ones leading to enhanced stability and expression.
Additional future directions for a one-shot boutique-style CDR library may harbor the potential for affinity maturation and improving antibody breadth. In addition, it can also be as merged with other relevant platforms. To conclude, computational antibody design is a forward-direction alternative to traditional antibody engineering methods, proving one-shot methodologies holds promise and viability.
