Monte carlo method-based QSAR modeling of penicillins binding to human serum proteins.
Arch Pharm (Weinheim)
; 348(1): 62-7, 2015 Jan.
Article
en En
| MEDLINE
| ID: mdl-25408278
ABSTRACT
The binding of penicillins to human serum proteins was modeled with optimal descriptors based on the Simplified Molecular Input-Line Entry System (SMILES). The concentrations of protein-bound drug for 87 penicillins expressed as percentage of the total plasma concentration were used as experimental data. The Monte Carlo method was used as a computational tool to build up the quantitative structure-activity relationship (QSAR) model for penicillins binding to plasma proteins. One random data split into training, test and validation set was examined. The calculated QSAR model had the following statistical parameters r(2) = 0.8760, q(2) = 0.8665, s = 8.94 for the training set and r(2) = 0.9812, q(2) = 0.9753, s = 7.31 for the test set. For the validation set, the statistical parameters were r(2) = 0.727 and s = 12.52, but after removing the three worst outliers, the statistical parameters improved to r(2) = 0.921 and s = 7.18. SMILES-based molecular fragments (structural indicators) responsible for the increase and decrease of penicillins binding to plasma proteins were identified. The possibility of using these results for the computer-aided design of new penicillins with desired binding properties is presented.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Penicilinas
/
Simulación por Computador
/
Proteínas Sanguíneas
/
Antibacterianos
Tipo de estudio:
Health_economic_evaluation
Límite:
Humans
Idioma:
En
Año:
2015
Tipo del documento:
Article