AlphaSpace 2.0: Representing Concave Biomolecular Surfaces Using β‑Clusters

Modern rational modulator
design and structure–function
characterization often concentrate on concave regions of biomolecular
surfaces, ranging from well-defined small-molecule binding sites to
large protein–protein interaction interfaces. Here, we introduce
a β-cluster as a pseudomolecular representation of fragment-centric
pockets detected by AlphaSpace [J. Chem. Inf. Model. 2015, 55, 1585], a recently developed
computational analysis tool for topographical mapping of biomolecular
concavities. By mimicking the shape as well as atomic details of potential
molecular binders, this new β-cluster representation allows
direct pocket-to-ligand shape comparison and can be used to guide
ligand optimization. Furthermore, we defined the β-score, the
optimal Vina score of the β-cluster, as an indicator of pocket
ligandability and developed an ensemble β-cluster approach,
which allows one-to-one pocket mapping and comparison among aligned
protein structures. We demonstrated the utility of β-cluster
representation by applying the approach to a wide variety of problems
including binding site detection and comparison, characterization
of protein–protein interactions, and fragment-based ligand
optimization. These new β-cluster functionalities have been
implemented in AlphaSpace 2.0, which is freely available on the web
at http://www.nyu.edu/projects/yzhang/AlphaSpace2.