Prediction of drug intestinal absorption by new linear and non-linear QSPR.
In order to minimize the high attrition rate that usually characterizes drug research and development projects, current medicinal chemists aim to characterize both pharmacological and ADME profiles at the beginning of drug R&D initiatives. Thus, the development of ADME High-Throughput Screening in vitro and in silico ADME models has become an important growing research area. Here we present new linear and non-linear predictive QSPR models to predict the human intestinal absorption rate, which are derived from a medium sized, balanced and diverse training set of organic compounds. The structure-property relationships so obtained involve only 4 molecular descriptors, and display an excellent ratio of number of cases to number of descriptors. Their adjustment of the training set data together with the performance achieved during the internal and external validation procedures are comparable to previously reported modeling efforts.
Medicinal Chemistry, Department of Biological Sciences, Faculty of Exact Sciences, National University of La Plata (UNLP), 47 y 115, 1900 La Plata, Argentina.
Alan
A
Talevi
Mohammad
M
Goodarzi
Erlinda V
EV
Ortiz
Pablo R
PR
Duchowicz
Carolina L
CL
Bellera
Guido
G
Pesce
Eduardo A
EA
Castro
Luis E
LE
Bruno-Blanch
D006801:Humans; D007408:Intestinal Absorption; D016014:Linear Models; D008968:Molecular Conformation; D017711:Nonlinear Dynamics; D010539:Permeability; D004364:Pharmaceutical Preparations / Q000737:chemistry / Q000378:metabolism*; D011336:Probability; D021281:Quantitative Structure-Activity Relationship; D013816:Thermodynamics
D004364:Pharmaceutical Preparations