Realtime Discovery of Inhibitors among Billion Compounds for Preview and Download Current drug discovery collaborations are mainly centered on the high-throughput screening of large libraries of commercially available or proprietary compounds. This rigid modality is inaccessible to most individual researchers, providing little opportunity for leveraging the large number of small-scale assays available in biology research labs. On the other hand, in silico screening methods of an expanding chemical space that is inaccessible to high-throughput approaches are credible and efficient alternatives for developing novel chemical probes of protein function, yet they are not readily accessible to biologists. Our ultimate goal is to empower researchers around the world to use their own in-house small-scale screening assays to validate compounds that they, as experts on their own targets, rationally designed using structure-based pharmacophore methods and large virtual libraries of both commercially accessible and novel, chemically accessible, small molecular weight drug-like compounds that are biased to target protein interactions. In the previous funding period, we have developed open access structure-based platforms that successfully potentiate real time iterative exact pharmacophore matching, model modification and fast database query for a given target. These technologies, AnchorQuery and ZincPharmer, presently screen over 55 million compounds readily synthesizable by multi-component reaction (MCR) or commercially available at the press of a ?click?, supporting drug discovery efforts worldwide. Building on these robust platforms, we plan to improve and significantly expand the design capabilities of our tools for rational drug design. Specifically, our aims are to: (a) expand the chemical space and targets covered by our libraries with novel MCR-accessible virtual compounds biased to target protein-protein and protein-RNA/DNA interactions, as well as natural products; (b) develop new virtual screening technologies for disrupting protein-RNA/DNA interactions and for leveraging natural product chemistry; (c) develop a new in silico hit-to-lead optimization tool to perform on the fly virtual structure activity relationship analysis of a billion size MCR chemical space; (d) improve the ranking, optimization and other analytical capabilities of our virtual screening technology; and (e) actively engage worldwide research groups with in vitro and/or in vivo assays with the goal of developing small molecular weight (ant)agonists.
These aims will deliver cutting edge open access, interactive, user-friendly technologies for virtual screening of billion size libraries for preview and download to any biomedical researcher in the world.

Public Health Relevance

Drug discovery today is no longer just a medicinal chemistry field; it is interdisciplinary, expensive and time-consuming. Innovations in computational techniques have enabled us to advance interactive virtual screening platforms to speed up the identification of hits. We are also expanding chemical space for screening including new scaffolds as an essential step in the challenge for identifying new chemical probes for new targets. We propose to continue the development of open access technologies that have the potential to invigorate world-wide collaborations aimed at the discovery of novel chemical probes for difficult targets. We are further developing a novel platform to perform hit-to-lead optimization in silico that will leverage the designability of MCR products to screen billions of different compounds. As a step towards addressing polypharmacology issues, we plan to apply our methods to build efficient tools to perform compound-centric virtual screening of human proteins. This initiative should help repurposing or identifying ?off-target? hits for a given compound.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Special Emphasis Panel (ZRG1)
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Smith, Ward
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University of Pittsburgh
Schools of Medicine
United States
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