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Evaluation and Characterization of Trk Kinase Inhibitors for the Treatment of Pain: Reliable Binding Affinity Predictions from Theory and Computation.
Wan, Shunzhou; Bhati, Agastya P; Skerratt, Sarah; Omoto, Kiyoyuki; Shanmugasundaram, Veerabahu; Bagal, Sharan K; Coveney, Peter V.
Afiliação
  • Wan S; Centre for Computational Science, Department of Chemistry, University College London , London WC1H 0AJ, United Kingdom.
  • Bhati AP; Centre for Computational Science, Department of Chemistry, University College London , London WC1H 0AJ, United Kingdom.
  • Skerratt S; Pfizer Global R&D , The Portway Building, Granta Park, Cambridge CB21 6GS, United Kingdom.
  • Omoto K; Pfizer Worldwide Research and Development , 610 Main Street, Cambridge, Massachusetts 02139, United States.
  • Shanmugasundaram V; Pfizer Worldwide Research and Development , Groton Laboratories, Groton, Connecticut 06340, United States.
  • Bagal SK; Pfizer Global R&D , The Portway Building, Granta Park, Cambridge CB21 6GS, United Kingdom.
  • Coveney PV; Centre for Computational Science, Department of Chemistry, University College London , London WC1H 0AJ, United Kingdom.
J Chem Inf Model ; 57(4): 897-909, 2017 04 24.
Article em En | MEDLINE | ID: mdl-28319380
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Dor / Desenho de Fármacos / Receptor trkA / Inibidores de Proteínas Quinases Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Chem Inf Model Assunto da revista: INFORMATICA MEDICA / QUIMICA Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Reino Unido
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Dor / Desenho de Fármacos / Receptor trkA / Inibidores de Proteínas Quinases Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Chem Inf Model Assunto da revista: INFORMATICA MEDICA / QUIMICA Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Reino Unido