Your browser doesn't support javascript.
loading
An open-source drug discovery platform enables ultra-large virtual screens.
Gorgulla, Christoph; Boeszoermenyi, Andras; Wang, Zi-Fu; Fischer, Patrick D; Coote, Paul W; Padmanabha Das, Krishna M; Malets, Yehor S; Radchenko, Dmytro S; Moroz, Yurii S; Scott, David A; Fackeldey, Konstantin; Hoffmann, Moritz; Iavniuk, Iryna; Wagner, Gerhard; Arthanari, Haribabu.
Afiliación
  • Gorgulla C; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Harvard University, Boston, MA, USA. cgorgulla@g.harvard.edu.
  • Boeszoermenyi A; Department of Physics, Faculty of Arts and Sciences, Harvard University, Cambridge, MA, USA. cgorgulla@g.harvard.edu.
  • Wang ZF; Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA. cgorgulla@g.harvard.edu.
  • Fischer PD; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Harvard University, Boston, MA, USA.
  • Coote PW; Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • Padmanabha Das KM; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Harvard University, Boston, MA, USA.
  • Malets YS; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Harvard University, Boston, MA, USA.
  • Radchenko DS; Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • Moroz YS; Department of Pharmacy, Pharmaceutical and Medicinal Chemistry, Saarland University, Saarbrücken, Germany.
  • Scott DA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Harvard University, Boston, MA, USA.
  • Fackeldey K; Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • Hoffmann M; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Harvard University, Boston, MA, USA.
  • Iavniuk I; Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • Wagner G; Enamine, Kyiv, Ukraine.
  • Arthanari H; National Taras Shevchenko University of Kyiv, Kyiv, Ukraine.
Nature ; 580(7805): 663-668, 2020 04.
Article en En | MEDLINE | ID: mdl-32152607
On average, an approved drug currently costs US$2-3 billion and takes more than 10 years to develop1. In part, this is due to expensive and time-consuming wet-laboratory experiments, poor initial hit compounds and the high attrition rates in the (pre-)clinical phases. Structure-based virtual screening has the potential to mitigate these problems. With structure-based virtual screening, the quality of the hits improves with the number of compounds screened2. However, despite the fact that large databases of compounds exist, the ability to carry out large-scale structure-based virtual screening on computer clusters in an accessible, efficient and flexible manner has remained difficult. Here we describe VirtualFlow, a highly automated and versatile open-source platform with perfect scaling behaviour that is able to prepare and efficiently screen ultra-large libraries of compounds. VirtualFlow is able to use a variety of the most powerful docking programs. Using VirtualFlow, we prepared one of the largest and freely available ready-to-dock ligand libraries, with more than 1.4 billion commercially available molecules. To demonstrate the power of VirtualFlow, we screened more than 1 billion compounds and identified a set of structurally diverse molecules that bind to KEAP1 with submicromolar affinity. One of the lead inhibitors (iKeap1) engages KEAP1 with nanomolar affinity (dissociation constant (Kd) = 114 nM) and disrupts the interaction between KEAP1 and the transcription factor NRF2. This illustrates the potential of VirtualFlow to access vast regions of the chemical space and identify molecules that bind with high affinity to target proteins.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Interfaz Usuario-Computador / Programas Informáticos / Evaluación Preclínica de Medicamentos / Descubrimiento de Drogas / Simulación del Acoplamiento Molecular Tipo de estudio: Prognostic_studies Idioma: En Revista: Nature Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Interfaz Usuario-Computador / Programas Informáticos / Evaluación Preclínica de Medicamentos / Descubrimiento de Drogas / Simulación del Acoplamiento Molecular Tipo de estudio: Prognostic_studies Idioma: En Revista: Nature Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos