SnugDock: Paratope Structural Optimization during Antibody-Antigen Docking Compensates for Errors in Antibody Homology Models

Abstract

High resolution structures of antibody-antigen complexes are useful for analyzing the binding interface and to make rational choices for antibody engineering. When a crystallographic structure of a complex is unavailable, the structure must be predicted using computational tools. In this work, we illustrate a novel approach, named SnugDock, to predict high-resolution antibody-antigen complex structures by simultaneously structurally optimizing the antibody-antigen rigid-body positions, the relative orientation of the antibody light and heavy chains, and the conformations of the six complementarity determining region loops. This approach is especially useful when the crystal structure of the antibody is not available, requiring allowances for inaccuracies in an antibody homology model which would otherwise frustrate rigid-backbone docking predictions. Local docking using SnugDock with the lowest-energy RosettaAntibody homology model produced more accurate predictions than standard rigid-body docking. SnugDock can be combined with ensemble docking to mimic conformer selection and induced fit resulting in increased sampling of diverse antibody conformations. The combined algorithm produced four medium (Critical Assessment of PRediction of Interactions-CAPRI rating) and seven acceptable lowest-interface-energy predictions in a test set of fifteen complexes. Structural analysis shows that diverse paratope conformations are sampled, but docked paratope backbones are not necessarily closer to the crystal structure conformations than the starting homology models. The accuracy of SnugDock predictions suggests a new genre of general docking algorithms with flexible binding interfaces targeted towards making homology models useful for further high-resolution predictions.

Peptides Designed To Spatially Depict the Epstein-Barr Virus Major Virion Glycoprotein gp350 Neutralization Epitope Elicit Antibodies That Block Virus-Neutralizing Antibody 72A1 Interaction with the Native gp350 Molecule

“…Following computer modeling of the 72A1 antibody variable-region peptide sequences, in silico identification of the gp350/ 220 interaction with the 72A1 antibody was performed by spatially aligning the 72A1 variable-region peptide sequences with the amino-terminal portion of gp350 using the SnugDock algorithm (13). The SnugDock molecular docking program predicts the optimal alignment for close coupling of the 72A1 variable region with the gp350 molecule by identifying the lowest-energy structure between two molecules and lists the interfacing residues and types of interactions (24). The SnugDock alignment indicated that the gp350 amino terminus couples to the 72A1 variable region through four gp350 interfacing peptide sequences, namely, 14 281 .…”

Modeling and docking of antibody structures with Rosetta

“…The Rosetta SnugDock algorithm leverages the information about the flexible and/or uncertain regions of the antibody to perform robust Ab–Ag docking 8 . SnugDock simulates the induced-fit mechanism through simultaneous optimization of several degrees of freedom.…”

A Systematic Comparison of Free and Bound Antibodies Reveals Binding-Related Conformational Changes

“…However, although the existence of conformational changes in the Ag binding site has been widely recognized, their role in the adaptive immune system has not been structurally elucidated. Furthermore, understanding these conformational changes should help to improve Ab modeling, docking, and engineering (5)(6)(7)(8)(9).…”