Boosting antibody developability through rational sequence optimization

MAbs
Daniel SeeligerAnne R Karow

Abstract

The application of monoclonal antibodies as commercial therapeutics poses substantial demands on stability and properties of an antibody. Therapeutic molecules that exhibit favorable properties increase the success rate in development. However, it is not yet fully understood how the protein sequences of an antibody translates into favorable in vitro molecule properties. In this work, computational design strategies based on heuristic sequence analysis were used to systematically modify an antibody that exhibited a tendency to precipitation in vitro. The resulting series of closely related antibodies showed improved stability as assessed by biophysical methods and long-term stability experiments. As a notable observation, expression levels also improved in comparison with the wild-type candidate. The methods employed to optimize the protein sequences, as well as the biophysical data used to determine the effect on stability under conditions commonly used in the formulation of therapeutic proteins, are described. Together, the experimental and computational data led to consistent conclusions regarding the effect of the introduced mutations. Our approach exemplifies how computational methods can be used to guide antibody optimizat...Continue Reading

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Methods Mentioned

BETA
light scattering
deamidation
differential scanning calorimetry
Fluorescence
size-exclusion chromatography
size exclusion chromatography
affinity measurements
surface plasmon resonance
targeted mutations
protein folding

Software Mentioned

Origin
autoBUSTER
PHASER
SCALA
XDS
MOSFLM
MOLPROBITY
autoPROC
POINTLESS

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