Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.06.28.546839v1?rss=1
Authors: Raybould, M. I. J., Turnbull, O. M., Suter, A., Guloglu, B., Deane, C. M.
Abstract: Antibodies with lambda light chains (lambda-antibodies) are generally considered to be less developable than those with kappa light chains (kappa-antibodies), leading to substantial systematic biases in drug discovery pipelines. This has contributed to kappa dominance amongst clinical-stage therapeutics. However, the identification of increasing numbers of epitopes preferentially engaged by lambda-dash antibodies shows there is a functional cost to neglecting them as potential lead candidates during discovery campaigns. Here, we update our Therapeutic Antibody Profiler (TAP) tool to use the latest data and machine learning-based structure prediction methods, and apply this new protocol to evaluate developability risk profiles for kappa-dash antibodies and lambda-dash antibodies based on their surface physicochemical properties. We find that lambda-dash antibodies are on average at a higher risk of poor developability - as an indication, over 40% of single-cell sequenced human lambda-antibodies are flagged by TAP for risk-prone patches of surface hydrophobicity (PSH), compared to around 11% of human kappa-antibodies. Nonetheless, a substantial proportion of natural lambda-antibodies are assigned more moderate risk profiles by TAP and should therefore represent more tractable candidates for therapeutic development. We also analyse the populations of high and low risk antibodies, highlighting opportunities for strategic design that TAP suggests would enrich for more developable lambda-based candidates. Overall, we provide context to the differing developability of kappa- and lambda-antibodies, enabling a rational approach to incorporate more diversity into the initial pool of immunotherapeutic candidates.
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