A Pharmacophore-Based Method for Rapid and Accurate Virtual Screening of Antibody Libraries against Antigens.

Antibody-based biotherapeutics make up an important class of biopharmaceuticals. However, their discovery requires resource- and time-consuming laboratory processes. To ameliorate this situation, several computational methods were used to predict the structures of antibody:antigen complexes (Ab:Ag) and identify potential binders, in-silico. However, there is still a general lack of rapid virtual screening methods capable of screening large antibody libraries against a given antigen or group of antigens. In this work, we explore the application of a successful small-molecule drug discovery strategy and adapt pharmacophore-based virtual screening to the world of antibody discovery. Using a nonredundant data set of 874 Ab:Ag complexes, we have developed an automated method to create pharmacophores from the antibody complementarity determining regions. Our method is 98.6% (862 out of 874) successful at reproducing the ground truth, i.e., it can recapitulate the parental antibody:antigen complexes. In a benchmarking comparison with cognate docking, using 33 Ab:Ag complexes of therapeutic interest, the pharmacophore method was not only much faster than cognate docking but also recovered all the native interfacial contacts. In addition, it can also find additional putative antibody binders to a given antigen within clusters of Ab:Ag complexes with similar interfacial structures. Our method has significant implications toward accelerating biotherapeutic drug discovery as well as drug repurposing research. This method was implemented in MOE 2024 and is available to the scientific community.