Francesca Stanzione Abstract

Effective use of small molecule and protein structural data in drug discovery using CSD-CrossMiner

Francesca Stanzione1, Jason Cole1, Ilenia Giangreco1

1The Cambridge Crystallographic Data Centre
Which structural motifs bind similar protein binding sites? Which ligand motifs have similar protein interaction patterns? Which ligand modifications and scaffold hops are tolerated in a protein binding site? These are some of the most frequent questions encountered in drug discovery. Structural databases of proteins and small molecules represent an invaluable source of information for the drug discovery process, allowing not only to characterise protein-ligand interactions but also to design novel molecular motifs that mimic established ligands. Therefore, with an effective use of these structural databases, it should be possible to answer these and other key questions in drug design projects.
CSD-CrossMiner(1) provides the ability to search structural databases, including two of the most important databases, the Cambridge Structural Database (CSD) and the Protein Data Bank (PDB), in terms of pharmacophore queries.
The ability to concurrently and interactively search protein-ligand binding sites extracted from the PDB and small organic molecules from the CSD using a single pharmacophore query, allows to shed some light on the cross-pharmacology between protein targets, as well as on the selectivity of bioactive small molecules, with a view to identify new patentable structures or to improve molecular properties. Pharmacophores are intuitive, as the essential functional group can be specified relative to a 3D structure and whose location and nature can be easily refined. More important, pharmacophores are flexible feature definitions and they can be redefined in order to control the degree of abstraction of the pharmacophore feature.
In CSD-CrossMiner, a pharmacophore query is created to describe the features that are essential for a small molecule to carry out its function and/or for a protein to interact with a ligand. All the structures matching the pharmacophore query are immediately overlaid onto the original query allowing an easy analysis of the results on the fly. CSD-CrossMiner can help identify new possible lead compounds by mining the small molecule structural database and/or to identify similar protein-ligand interactions in the protein-ligand structural database.
In this poster we will provide an introduction to CSD-CrossMiner and, using some example cases, we will provide an overview of the tool and of its applications in drug discovery workflows.1) O. Korb et al. (2016) J. Med. Chem., 59, 4257-4266. DOI: 10.1021/acs.jmedchem.5b01756