Development and Evaluation of GlycanDock: A Protein–Glycoligand Docking Refinement Algorithm in Rosetta

Carbohydrate chains are ubiquitous
in the complex molecular processes
of life. These highly diverse chains are recognized by a variety of
protein receptors, enabling glycans to regulate many biological functions.
High-resolution structures of protein–glycoligand complexes
reveal the atomic details necessary to understand this level of molecular
recognition and inform application-focused scientific and engineering
pursuits. When experimental challenges hinder high-throughput determination
of quality structures, computational tools can, in principle, fill
the gap. In this work, we introduce GlycanDock, a
residue-centric protein–glycoligand docking refinement algorithm
developed within the Rosetta macromolecular modeling and design software
suite. We performed a benchmark docking assessment using a set of
109 experimentally determined protein–glycoligand complexes
as well as 62 unbound protein structures. The GlycanDock algorithm can sample and discriminate among protein–glycoligand
models of native-like structural accuracy with statistical reliability
from starting structures of up to 7 Å root-mean-square deviation
in the glycoligand ring atoms. We show that GlycanDock-refined models qualitatively replicated the known binding specificity
of a bacterial carbohydrate-binding module. Finally, we present a
protein–glycoligand docking pipeline for generating putative
protein–glycoligand complexes when only the glycoligand sequence
and unbound protein structure are known. In combination with other
carbohydrate modeling tools, the GlycanDock docking
refinement algorithm will accelerate research in the glycosciences.