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In-depth analysis of subclass-specific conformational preferences of IgG antibodies.


ABSTRACT: IgG subclass-specific differences in biological function and in vitro stability are often referred to variations in the conformational flexibility, while this flexibility has rarely been characterized. Here, small-angle X-ray scattering data from IgG1, IgG2 and IgG4 antibodies, which were designed with identical variable regions, were thoroughly analysed by the ensemble optimization method. The extended analysis of the optimized ensembles through shape clustering reveals distinct subclass-specific conformational preferences, which provide new insights for understanding the variations in physical/chemical stability and biological function of therapeutic antibodies. Importantly, the way that specific differences in the linker region correlate with the solution structure of intact antibodies is revealed, thereby visualizing future potential for the rational design of antibodies with designated physicochemical properties and tailored effector functions. In addition, this advanced computational approach is applicable to other flexible multi-domain systems and extends the potential for investigating flexibility in solutions of macromolecules by small-angle X-ray scattering.

SUBMITTER: Tian X 

PROVIDER: S-EPMC4285876 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

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In-depth analysis of subclass-specific conformational preferences of IgG antibodies.

Tian Xinsheng X   Vestergaard Bente B   Thorolfsson Matthias M   Yang Zhiru Z   Rasmussen Hanne B HB   Langkilde Annette E AE  

IUCrJ 20150101 Pt 1


IgG subclass-specific differences in biological function and in vitro stability are often referred to variations in the conformational flexibility, while this flexibility has rarely been characterized. Here, small-angle X-ray scattering data from IgG1, IgG2 and IgG4 antibodies, which were designed with identical variable regions, were thoroughly analysed by the ensemble optimization method. The extended analysis of the optimized ensembles through shape clustering reveals distinct subclass-specif  ...[more]

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