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Predicting the target landscape of kinase inhibitors using 3D convolutional neural networks.
Kanev, Georgi K; Zhang, Yaran; Kooistra, Albert J; Bender, Andreas; Leurs, Rob; Bailey, David; Würdinger, Thomas; de Graaf, Chris; de Esch, Iwan J P; Westerman, Bart A.
Afiliación
  • Kanev GK; Division of Medicinal Chemistry, Amsterdam Institute of Molecular and Life Sciences (AIMMS), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
  • Zhang Y; Department of Neurosurgery, Amsterdam University Medical Centers, Cancer Center Amsterdam, Brain Tumor Center Amsterdam, Amsterdam, The Netherlands.
  • Kooistra AJ; Department of Neurosurgery, Amsterdam University Medical Centers, Cancer Center Amsterdam, Brain Tumor Center Amsterdam, Amsterdam, The Netherlands.
  • Bender A; Division of Medicinal Chemistry, Amsterdam Institute of Molecular and Life Sciences (AIMMS), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
  • Leurs R; Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark.
  • Bailey D; Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Cambridge, United Kingdom.
  • Würdinger T; Division of Medicinal Chemistry, Amsterdam Institute of Molecular and Life Sciences (AIMMS), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
  • de Graaf C; The WINDOW consortium, www.window-consortium.org.
  • de Esch IJP; IOTA Pharmaceuticals Ltd, St Johns Innovation Centre, Cambridge, United Kingdom.
  • Westerman BA; Department of Neurosurgery, Amsterdam University Medical Centers, Cancer Center Amsterdam, Brain Tumor Center Amsterdam, Amsterdam, The Netherlands.
PLoS Comput Biol ; 19(9): e1011301, 2023 09.
Article en En | MEDLINE | ID: mdl-37669273
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Sistemas de Liberación de Medicamentos / Aprendizaje Automático Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Sistemas de Liberación de Medicamentos / Aprendizaje Automático Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Estados Unidos