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Chemical Space Mimicry for Drug Discovery.
Yuan, William; Jiang, Dadi; Nambiar, Dhanya K; Liew, Lydia P; Hay, Michael P; Bloomstein, Joshua; Lu, Peter; Turner, Brandon; Le, Quynh-Thu; Tibshirani, Robert; Khatri, Purvesh; Moloney, Mark G; Koong, Albert C.
Afiliação
  • Yuan W; Trinity College, University of Oxford , Oxford OX1 3BH, United Kingdom.
  • Jiang D; Department of Radiation Oncology, Stanford University School of Medicine , Stanford, California 94305, United States.
  • Nambiar DK; Department of Radiation Oncology, Stanford University School of Medicine , Stanford, California 94305, United States.
  • Liew LP; Department of Radiation Oncology, Stanford University School of Medicine , Stanford, California 94305, United States.
  • Hay MP; Auckland Cancer Society Research Centre, Faculty of Medical and Health Sciences, The University of Auckland , Auckland, New Zealand.
  • Bloomstein J; Auckland Cancer Society Research Centre, Faculty of Medical and Health Sciences, The University of Auckland , Auckland, New Zealand.
  • Lu P; Department of Radiation Oncology, Stanford University School of Medicine , Stanford, California 94305, United States.
  • Turner B; Department of Radiation Oncology, Stanford University School of Medicine , Stanford, California 94305, United States.
  • Le QT; Department of Radiation Oncology, Stanford University School of Medicine , Stanford, California 94305, United States.
  • Tibshirani R; Department of Radiation Oncology, Stanford University School of Medicine , Stanford, California 94305, United States.
  • Khatri P; Department of Statistics, Stanford University , Stanford, California 94305, United States.
  • Moloney MG; Department of Radiation Oncology, Stanford University School of Medicine , Stanford, California 94305, United States.
  • Koong AC; Institute for Immunity, Transplantation, and Infection & Division of Biomedical Informatics Research, Department of Medicine, Stanford University School of Medicine , Stanford, California 94305, United States.
J Chem Inf Model ; 57(4): 875-882, 2017 04 24.
Article em En | MEDLINE | ID: mdl-28257191
We describe a new library generation method, Machine-based Identification of Molecules Inside Characterized Space (MIMICS), that generates sets of molecules inspired by a text-based input. MIMICS-generated libraries were found to preserve distributions of properties while simultaneously increasing structural diversity. Newly identified MIMICS-generated compounds were found to be bioactive as inhibitors of specific components of the unfolded protein response (UPR) and the VEGFR2 pathway in cell-based assays, thus confirming the applicability of this methodology toward drug design applications. Wider application of MIMICS could facilitate the efficient utilization of chemical space.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Descoberta de Drogas Tipo de estudo: Prognostic_studies Idioma: En Revista: J Chem Inf Model Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Descoberta de Drogas Tipo de estudo: Prognostic_studies Idioma: En Revista: J Chem Inf Model Ano de publicação: 2017 Tipo de documento: Article