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Prediction of the permeability of neutral drugs inferred from their solvation properties.
Milanetti, Edoardo; Raimondo, Domenico; Tramontano, Anna.
Afiliação
  • Milanetti E; Department of Physics, Sapienza Università di Roma, Rome 00185, Italy.
  • Raimondo D; Department of Physics, Sapienza Università di Roma, Rome 00185, Italy.
  • Tramontano A; Department of Physics, Sapienza Università di Roma, Rome 00185, Italy Institute Pasteur - Fondazione Cenci Bolognetti, Rome, 00161, Italy Center for Life Nano Science @Sapienza, Istituto Italiano di Tecnologia, Sapienza Università di Roma, Rome, 00185, Italy.
Bioinformatics ; 32(8): 1163-9, 2016 04 15.
Article em En | MEDLINE | ID: mdl-26656568
ABSTRACT
MOTIVATION Determination of drug absorption is an important component of the drug discovery and development process in that it plays a key role in the decision to promote drug candidates to clinical trials. We have developed a method that, on the basis of an analysis of the dynamic distribution of water molecules around a compound obtained by molecular dynamics simulations, can compute a parameter-free value that correlates very well with the compound permeability measured using the human colon adenocarcinoma (Caco-2) cell line assay.

RESULTS:

The method has been tested on twenty-three neutral drugs for which a consistent set of experimental data is available. We show here that our method reproduces the experimental data better than other existing tools. Furthermore it provides a detailed view of the relationship between the hydration and the permeability properties of molecules. CONTACT anna.tramontano@uniroma1.it SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Descoberta de Drogas Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Descoberta de Drogas Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2016 Tipo de documento: Article