<abstract xmlns="http://www.w3.org/1999/xhtml"><p>In this study, a quantitative structure-pharmacokinetic relationship (QSPkR) model for the volume of distribution (<italic>V</italic>d) values of 126 anti-infective drugs in humans was developed employing multiple linear regression (MLR), artificial neural network (ANN) and support vector regression (SVM) using theoretical molecular structural descriptors. A correlation-based feature selection (CFS) was employed to select the relevant descriptors for modeling. The model results show that the main factors governing <italic>V</italic>d of anti-infective drugs are 3D molecular representations of atomic van der Waals volumes and Sanderson electronegativities, number of aliphatic and aromatic amino groups, number of beta-lactam rings and topological 2D shape of the molecule. Model predictivity was evaluated by external validation, using a variety of statistical tests and the SVM model demonstrated better performance compared to other models. The developed models can be used to predict the <italic>V</italic>d values of anti-infective drugs.</p></abstract>

In this study, a quantitative structure-pharmacokinetic relationship (QSPkR) model for the volume of distribution (Vd) values of 126 anti-infective drugs in humans was developed employing multiple linear regression (MLR), artificial neural network (ANN) and support vector regression (SVM) using theoretical molecular structural descriptors. A correlation-based feature selection (CFS) was employed to select the relevant descriptors for modeling. The model results show that the main factors governing Vd of anti-infective drugs are 3D molecular representations of atomic van der Waals volumes and Sanderson electronegativities, number of aliphatic and aromatic amino groups, number of beta-lactam rings and topological 2D shape of the molecule. Model predictivity was evaluated by external validation, using a variety of statistical tests and the SVM model demonstrated better performance compared to other models. The developed models can be used to predict the Vd values of anti-infective drugs.

Quantitative structure-pharmacokinetic relationship (QSPkP) analysis of the volume of distribution values of anti-infective agents from j group of the ATC classification in humans

Department of Pharmacy, Sultan Qaboos University Hospital PO Box 38, Al Khod, Muscat 123 Oman

QSAR and Computer Chemical Laboratories, A.P.S. University Rewa-486003, India Present address: National Institute of Technical Teachers’ Training and Research (NITTTR) Shamla Hills, Bhopal-462 002, India.

Acta Pharmaceutica

In this study, a quantitative structure-pharmacokinetic relationship (QSPkR) model for the volume of distribution (Vd) values of 126 anti-infective drugs in...

Quantitative structure-pharmacokinetic relationship (QSPkP) analysis of the volume of distribution values of anti-infective agents from j group of the ATC classification in humans

Online veröffentlicht: 06. Nov. 2012

Seitenbereich: 305 - 323

DOI: https://doi.org/10.2478/v10007-012-0024-z

Schlüsselwörter
QSPkR, QSPR, structure pharmacokinetic relationship, volume of distribution, ANN, SVM, CFS

This content is open access.

Quantitative structure-pharmacokinetic relationship (QSPkP) analysis of the volume of distribution values of anti-infective agents from j group of the ATC classification in humans

Online veröffentlicht: 06. Nov. 2012

Seitenbereich: 305 - 323

DOI: https://doi.org/10.2478/v10007-012-0024-z

SchlüsselwörterQSPkR, QSPR, structure pharmacokinetic relationship, volume of distribution, ANN, SVM, CFS

This content is open access.

Schlüsselwörter
QSPkR, QSPR, structure pharmacokinetic relationship, volume of distribution, ANN, SVM, CFS