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Hsp90 inhibitors, part 2: combining ligand-based and structure-based approaches for virtual screening application.
Department of Physics, Sapienza Universita ̀ di Roma, P.le Aldo Moro 5, 00185, Roma, Italy.
Rome Center for Molecular Design, Dipartimento di Chimica e Tecnologie del Farmaco, Sapienza Universita ̀ di Roma, P. le A. Moro 5, 00185 Roma, Italy.ORCID iD: 0000-0002-4831-3423
Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis School of Medicine, 700 South Euclid Avenue, St. Louis, Missouri 63110, United States; Rome Center for Molecular Design, Dipartimento di Chimica e Tecnologie del Farmaco, Sapienza Universita ̀ di Roma, P. le A. Moro 5, 00185 Roma, Italy .
Dipartimento Farmaco Chimico Tecnologico, Universita ̀ degli Studi di Siena, via A. Moro, I-53100 Siena, Italy.
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2014 (English)In: Journal of Chemical Information and Modeling, ISSN 1549-9596, E-ISSN 1549-960X, Vol. 54, no 3, 970-7 p.Article in journal (Refereed) Published
Abstract [en]

Hsp90 continues to be an important target for pharmaceutical discovery. In this project, virtual screening (VS) for novel Hsp90 inhibitors was performed using a combination of Autodock and Surflex-Sim (LB) scoring functions with the predictive ability of 3-D QSAR models, previously generated with the 3-D QSAutogrid/R procedure. Extensive validation of both structure-based (SB) and ligand-based (LB), through realignments and cross-alignments, allowed the definition of LB and SB alignment rules. The mixed LB/SB protocol was applied to virtually screen potential Hsp90 inhibitors from the NCI Diversity Set composed of 1785 compounds. A selected ensemble of 80 compounds were biologically tested. Among these molecules, preliminary data yielded four derivatives exhibiting IC50 values ranging between 18 and 63 μM as hits for a subsequent medicinal chemistry optimization procedure.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2014. Vol. 54, no 3, 970-7 p.
Keyword [en]
HSP90, Virtual Screening, Molecular Docking, 3D QSAR, Structure Based Drug Design, Ligand Based Drug Design, in vitro Assays
National Category
Medicinal Chemistry Biological Sciences Chemical Sciences Computer and Information Science
Identifiers
URN: urn:nbn:se:uu:diva-321303DOI: 10.1021/ci400760aPubMedID: 24555544OAI: oai:DiVA.org:uu-321303DiVA: diva2:1094965
Available from: 2017-05-11 Created: 2017-05-11 Last updated: 2017-05-11

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