Quantitative structure/activity relationship modelling of pharmacokinetic properties using genetic algorithm-combined partial least squares method.
Quantitative structure/activity relationship (QSAR) approaches have widely been applied to gain deeper understandings of the relationships between ADME parameters and molecular structure and properties. QSAR models for predicting ADME properties are required to cover structurally diverse compounds. In the present investigation, we describe application of genetic algorithm-combined partial least squares (GA-PLS) method to QSAR modelling of various ADME properties. By selecting an appropriate set of molecular descriptors automatically by the use of genetic algorithm, many ADME properties could be well-explained by simple molecular descriptors derived from 2-dimensional chemical structure.
Yamashita
Fumiyoshi
F
Department of Drug Delivery Research, Graduate School of Pharmaceutical Sciences, Kyoto University, Sakyo-ku, Kyoto, 606-8501, Japan.
Fujiwara
Shin-Ichi
S
Wanchana
Suchada
S
Hashida
Mitsuru
M
D000465:Algorithms; D001692:Biological Transport; D018938:Caco-2 Cells; D002434:Cefadroxil / Q000737:chemistry / Q000378:metabolism / Q000493:pharmacokinetics; D051544:Cytochrome P-450 CYP3A; D003577:Cytochrome P-450 Enzyme System / Q000378:metabolism; D006801:Humans; D016018:Least-Squares Analysis; D008957:Models, Genetic; D008958:Models, Molecular; D008968:Molecular Conformation; D004364:Pharmaceutical Preparations / Q000737:chemistry / Q000378:metabolism; D010599:Pharmacokinetics; D021281:Quantitative Structure-Activity Relationship; D012995:Solubility
D004364:Pharmaceutical Preparations; D002434:Cefadroxil; D003577:Cytochrome P-450 Enzyme System; D051544:Cytochrome P-450 CYP3A; C510163:CYP3A4 protein, human