3D Antibody Modeling 

 

Thsuccess of antibody-based drugs has spurred the refinement of methods to engineer more efficacious, safer and developable therapeutic antibodies. An important component of the antibody engineering process is the availability of high quality three-dimensional (3D) structures of the potential antibody-based drug. Such information is useful to guide humanization, assist the design of libraries of mutants for optimization of binding properties such as kon and koff, and engineer variants with improved solubility, less aggregation and increased stability.
Antibody structure determination by x-ray crystallography is relatively robust, but it is resource intensive and in some cases the turnaround time is unpredictable, relative to computational modeling methods. Thus, the question is how an antibody 3D model compares to an experimentally determined high resolution structure of the antibody and therefore how reliable predictions and designs made based on models turn out to be.
This webserver compiles the information of two Antibody Modeling Assessments (AMA’s) conducted in recent years to determine the State of the Art in Antibody Modeling. For the first assessment (AMA-I) nine unpublished high-resolution x-ray Fab crystal structures covering a wide range of antigen-binding site conformations were used as benchmark to compare Fv models generated by four structure prediction methodologies. For AMA-II of a more diverse set of eleven unpublished high-resolution x-ray Fab crystal were used as benchmark to compare seven structure prediction methodologies.

The success of antibody-based drugs has spurred the refinement of methods to engineer more efficacious, safer and developable therapeutic antibodies. An important component of the antibody engineering process is the availability of high quality three-dimensional (3D) structures of the potential antibody-based drug. Such information is useful to guide humanization, assist the design of libraries of mutants for optimization of binding properties such as kon and koff, and engineer variants with improved solubility, less aggregation and increased stability.

Antibody structure determination by x-ray crystallography is relatively robust, but it is resource intensive and in some cases the turnaround time is unpredictable, relative to computational modeling methods. Thus, the question is how an antibody 3D model compares to an experimentally determined high resolution structure of the antibody and therefore how reliable predictions and designs made based on models turn out to be.

To address this question we have conducted two Antibody Modeling Assessments (AMA’s). For the first assessment (AMA-I) nine unpublished high-resolution x-ray Fab crystal structures covering a wide range of antigen-binding site conformations were used as benchmark to compare Fv models generated by four structure prediction methodologies. For the second assessment (AMA-II) a more diverse and larger set (eleven unpublished structures) was used as benchmark to compare seven structure prediction methodologies.

This webserver compiles information of the assessments, including the benchmark structures, models generated by the participants and highlights of AMA's, together with resources and literature on Antibody modeling.