Dominick Mobilio

A family of ring system-based structural fragments for use in structure-activity studies: database mining and recursive partitioning.

In earlier work from our laboratory, we have described the use of the ring system and ring scaffold as descriptors. We showed that these descriptors could be used for fast compound clustering, novelty determination, compound acquisition, and combinatorial library design. Here we extend the concept to a whole family of structural descriptors with the ring system as the centerpiece. We show how this simple idea can be used to build powerful search tools for mining chemical databases in useful ways. We have also built recursive partition trees using these fragments as descriptors. We will discuss how these trees can help in analyzing complex structure-activity data.

A structural informatics approach to mine kinase knowledge bases

In this paper, we describe a combination of structural informatics approaches developed to mine data extracted from existing structure knowledge bases (Protein Data Bank and the GVK database) with a focus on kinase ATP-binding site data. In contrast to existing systems that retrieve and analyze protein structures, our techniques are centered on a database of ligand-bound geometries in relation to residues lining the binding site and transparent access to ligand-based SAR data. We illustrate the systems in the context of the Abelson kinase and related inhibitor structures.

A Protein Relational Database and Protein Family Knowledge Bases to Facilitate Structure-Based Design Analyses

The Protein Data Bank is the most comprehensive source of experimental macromolecular structures. It can, however, be difficult at times to locate relevant structures with the Protein Data Bank search interface. This is particularly true when searching for complexes containing specific interactions between protein and ligand atoms. Moreover, searching within a family of proteins can be tedious. For example, one cannot search for some conserved residue as residue numbers vary across structures. We describe herein three databases, Protein Relational Database, Kinase Knowledge Base, and Matrix Metalloproteinase Knowledge Base, containing protein structures from the Protein Data Bank. In Protein Relational Database, atom–atom distances between protein and ligand have been precalculated allowing for millisecond retrieval based on atom identity and distance constraints. Ring centroids, centroid–centroid and centroid–atom distances and angles have also been included permitting queries for π‐stacking interactions and other structural motifs involving rings. Other geometric features can be searched through the inclusion of residue pair and triplet distances. In Kinase Knowledge Base and Matrix Metalloproteinase Knowledge Base, the catalytic domains have been aligned into common residue numbering schemes. Thus, by searching across Protein Relational Database and Kinase Knowledge Base, one can easily retrieve structures wherein, for example, a ligand of interest is making contact with the gatekeeper residue.