A simplified model to predict P-glycoprotein interacting drugs from 3D molecular interaction field

• Published in: International journal of pharmaceutics Vol. 309; no. 1; pp. 109 - 114
• Main Authors: Zhuang, Xiao-Mei, Xiao, Jun-Hai, Li, Jin-Tong, Zhang, Zhen-Qing, Ruan, Jin-Xiu
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 17.02.2006; Elsevier
• Subjects: Adenosine Triphosphatases - chemistry; ATP-Binding Cassette, Sub-Family B, Member 1 - chemistry; Biological and medical sciences; General pharmacology; Medical sciences; Models, Molecular; Molecular interaction field; P-glycoprotein; Pharmaceutical Preparations - chemistry; Pharmaceutical technology. Pharmaceutical industry; Pharmacology. Drug treatments; QSAR; Structure-Activity Relationship; VolSurf; P-glycoprotein; VolSurf; Molecular interaction field; QSAR; Drug; Pharmaceutical technology; Structure activity relation; P Glycoprotein; Molecular interaction
• ISSN: 0378-5173; 1873-3476
• DOI: 10.1016/j.ijpharm.2005.11.009

A new two components partial least squares discriminant analysis (PLS) model for the prediction of P-glycoprotein-associated ATPase activity of drugs by using VolSurf compute theoretical molecular descriptors derived from 3D molecular interaction field was reported in the present study. By using 27 diverse drugs from literature, two models were constructed ( R 2 = 0.9003, 0.8150; Q 2 = 0.7165, 0.7630) in this paper, which were similar to models that utilized MolSurf parametrization ( R 2 = 0.7760, 0.7180; Q 2 = 0.7420, 0.6950) by using 22 drugs reported in the same literature. The results investigated VolSurf software was superior to MolSurf in its simplicity. Properties associated with the volume, polarizability, and hydrogen bond could have important impact on the P-glycoprotein-associated ATPase activity.