Montader (Monty) Ali, ma986@cam.ac.uk
Canada
Chemistry, Downing College
PhD Thesis: De novo computational design of pH-dependent antibodies
Research interests:
1. Computational design of antibodies
2. Evaluating and improving binding of antibodies
3. Generating antibodies that are highly specific to their target of interest
4. Understanding the nature of biomolecular interactions
My PhD will focus on addressing the most pressing challenges that rational antibody design must overcome to become a fully competitive technology of antibody discovery and optimisation. My lab, the Sormanni group, has recently developed a state-of-the-art design technology that produced six stable antibodies with good binding against pre-selected targets.
The objectives I hope to complete by the end of my project is to further develop this technology to obtain antibodies with great binding against therapeutically relevant targets (i.e., beta-2 microglobulin) and to evaluate these antibodies experimentally. Furthermore, to expand the design strategy to generate antibodies against any target of interest, currently limited to targets available in databases. Finally, to develop a new approach to accurately predict and manipulate the effect of key formulation properties, such as pH and ionic strength, on antibody solubility, stability, and binding.
Who or what inspired you to pursue your research interests?
The inspirations for my research interests began when I first took introduction to organic chemistry during my undergraduate degree under Professor Peter Buist, a key source of my inspiration. Understanding molecular reactions and their associated mechanisms encouraged me to explore and study molecular interactions in the world around me (i.e., photosynthesis, enzymes, etc.). Naturally, I wanted to apply my knowledge in a field where I can have a more tangible, short-term impact. I felt the Sormanni group was the perfect fit for my research interests, with the aim of generating antibodies for therapeutic, research, and diagnostic purposes.