Neural computational prediction of oral drug absorption based on CODES 2D descriptors.
Eur J Med Chem
; 45(3): 930-40, 2010 Mar.
Article
en En
| MEDLINE
| ID: mdl-20022146
ABSTRACT
A neural model based on a numerical molecular representation using CODES program to predict oral absorption of any structure is described. This model predicts both high and low-absorbed compounds with a global accuracy level of 74%. CODES/ANN methodology shows promising utilities not only as a conventional in silico tool in high-throughput screening or improvement of absorption capabilities procedures but also the improvement of in vitro-in vivo correlation could be addressed.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Tecnología Farmacéutica
/
Modelos Químicos
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Eur J Med Chem
Año:
2010
Tipo del documento:
Article
País de afiliación:
España