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Novel in silico prediction algorithms for the design of stable biologics

Understanding the effects of mutation on protein stability and protein binding affinity is an important component of successful protein design, especially in the area of protein therapeutics. In silico approaches to predict the effects of amino acid mutations can be used to guide experimental design and help reduce the cost of bringing therapeutics to market. A number of novel methods for fast computational mutagenesis of proteins have been developed and can be applied to calculate the energy effect of mutation on protein stability, and on protein-protein binding affinity with an optional pH dependency calculation. Here, we will present those methods and associated validation results. Furthermore, we will provide a case study using a set of engineered antibodies that have altered pH-selective binding. These demonstrate how binding to either neonatal receptor (FcRn) or to their target antigens can be modified to tune their half-life in the host system

Presented by Lisa Yan, Senior Manager, BIOVIA

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