Dataset Information

AnchorQuery: Rapid online virtual screening for small-molecule protein-protein interaction inhibitors.

ABSTRACT: AnchorQuery (http://anchorquery.csb.pitt.edu) is a web application for rational structure-based design of protein-protein interaction (PPI) inhibitors. A specialized variant of pharmacophore search is used to rapidly screen libraries consisting of more than 31 million synthesizable compounds biased by design to preferentially target PPIs. Every library compound is accessible through one-step multi-component reaction (MCR) chemistry and contains an anchor motif that is bioisosteric to an amino acid residue. The inclusion of this anchor not only biases the compounds to interact with proteins, it also enables a rapid, sublinear time pharmacophore search algorithm. AnchorQuery provides all the tools necessary for users to perform online interactive virtual screens of millions of compounds, including pharmacophore elucidation and search, and enrichment analysis. Accessibility: AnchorQuery is freely accessible at http://anchorquery.csb.pitt.edu.

SUBMITTER: Koes DR

PROVIDER: S-EPMC5734307 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Publications

AnchorQuery: Rapid online virtual screening for small-molecule protein-protein interaction inhibitors.

Koes David R DR Dömling Alexander A Camacho Carlos J CJ

Protein science : a publication of the Protein Society 20171024 1

AnchorQuery (http://anchorquery.csb.pitt.edu) is a web application for rational structure-based design of protein-protein interaction (PPI) inhibitors. A specialized variant of pharmacophore search is used to rapidly screen libraries consisting of more than 31 million synthesizable compounds biased by design to preferentially target PPIs. Every library compound is accessible through one-step multi-component reaction (MCR) chemistry and contains an anchor motif that is bioisosteric to an amino ac ...[more]

PMID: 28921842

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Project description:Protein-protein interactions play important roles in virtually all cellular processes, making them enticing targets for modulation by small-molecule therapeutics: specific examples have been well validated in diseases ranging from cancer and autoimmune disorders, to bacterial and viral infections. Despite several notable successes, however, overall these remain a very challenging target class. Protein interaction sites are especially challenging for computational approaches, because the target protein surface often undergoes a conformational change to enable ligand binding: this confounds traditional approaches for virtual screening. Through previous studies, we demonstrated that biased "pocket optimization" simulations could be used to build collections of low-energy pocket-containing conformations, starting from an unbound protein structure. Here, we demonstrate that these pockets can further be used to identify ligands that complement the protein surface. To do so, we first build from a given pocket its "exemplar": a perfect, but nonphysical, pseudoligand that would optimally match the shape and chemical features of the pocket. In our previous studies, we used these exemplars to quantitatively compare protein surface pockets to one another. Here, we now introduce this exemplar as a template for pharmacophore-based screening of chemical libraries. Through a series of benchmark experiments, we demonstrate that this approach exhibits comparable performance as traditional docking methods for identifying known inhibitors acting at protein interaction sites. However, because this approach is predicated on ligand/exemplar overlays, and thus does not require explicit calculation of protein-ligand interactions, exemplar screening provides a tremendous speed advantage over docking: 6 million compounds can be screened in about 15 min on a single 16-core, dual-GPU computer. The extreme speed at which large compound libraries can be traversed easily enables screening against a "pocket-optimized" ensemble of protein conformations, which in turn facilitates identification of more diverse classes of active compounds for a given protein target.

Dataset Information

AnchorQuery: Rapid online virtual screening for small-molecule protein-protein interaction inhibitors.

Publications

AnchorQuery: Rapid online virtual screening for small-molecule protein-protein interaction inhibitors.

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