AlphaSpace 2.0: Representing Concave Biomolecular Surfaces Using β-Clusters

Joseph Katigbak, Haotian Li, David Rooklin, Yingkai Zhang

Research output: Contribution to journalArticlepeer-review


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

Original languageEnglish (US)
Pages (from-to)1494-1508
Number of pages15
JournalJournal of Chemical Information and Modeling
Issue number3
StatePublished - Mar 23 2020

ASJC Scopus subject areas

  • General Chemistry
  • General Chemical Engineering
  • Computer Science Applications
  • Library and Information Sciences


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