Characterizing Epitope Binding Regions of Entire Antibody Panels by Combining Experimental and Computational Analysis of Antibody: Antigen Binding Competition.

Benjamin D Brooks,Chris Bailey-Kellogg,Gary H Cohen,Juechen Yang,Adam Closmore,Michael Holland,Tina Cairns

doi:10.3390/molecules25163659

Abstract

Vaccines and immunotherapies depend on the ability of antibodies to sensitively and specifically recognize particular antigens and specific epitopes on those antigens. As such, detailed characterization of antibody–antigen binding provides important information to guide development. Due to the time and expense required, high-resolution structural characterization techniques are typically used sparingly and late in a development process. Here, we show that antibody–antigen binding can be characterized early in a process for whole panels of antibodies by combining experimental and computational analyses of competition between monoclonal antibodies for binding to an antigen. Experimental “epitope binning” of monoclonal antibodies uses high-throughput surface plasmon resonance to reveal which antibodies compete, while a new complementary computational analysis that we call “dock binning” evaluates antibody–antigen docking models to identify why and where they might compete, in terms of possible binding sites on the antigen. Experimental and computational characterization of the identified antigenic hotspots then enables the refinement of the competitors and their associated epitope binding regions on the antigen. While not performed at atomic resolution, this approach allows for the group-level identification of functionally related monoclonal antibodies (i.e., communities) and identification of their general binding regions on the antigen. By leveraging extensive epitope characterization data that can be readily generated both experimentally and computationally, researchers can gain broad insights into the basis for antibody–antigen recognition in wide-ranging vaccine and immunotherapy discovery and development programs.

Highlights

The utility of antibodies (Abs) for treatment of disease has been recognized for over a century and the clinical realization of this vision in a host of broad therapeutic indications has begun to Molecules 2020, 25, 3659; doi:10.3390/molecules25163659 www.mdpi.com/journal/moleculesMolecules 2020, 25, 3659 come to fruition [1,2]
We demonstrate the power of experimental and computational binning in glycoprotein application an important target with a wealth of combined data available for our use: herpes simplex virus (HSV)
GD is a fusion protein found in HSV that has served as the standard by which all other(HSV)

Summary

Introduction

The utility of antibodies (Abs) for treatment of disease has been recognized for over a century and the clinical realization of this vision in a host of broad therapeutic indications has begun to Molecules 2020, 25, 3659; doi:10.3390/molecules25163659 www.mdpi.com/journal/moleculesMolecules 2020, 25, 3659 come to fruition [1,2]. Even Abs targeting the same Ag have demonstrated variable efficacy depending on their epitope specificities [3,4]. Combination immunotherapies with diverse epitopes have demonstrated synergistic efficacy and have reduced the ability of cancer and infectious disease to develop resistance [12,13]. The use of immune repertoire B cell sequencing is supporting expanded clinical applications in immunotherapy, and in the development of vaccines for emergent infectious diseases, both viral and bacterial [14]. The specificity of Abs in vaccine applications reveals various levels of protection depending on which epitopes are targeted by the immune response [12,13,15,16,17,18,19]

Methods

Results

Conclusion