Quantitative structure-activity relationships studies of CCR5 inhibitors and toxicity of aromatic compounds using gene expression programming.
Quantitative structure-activity relationship (QSAR) study of chemokine receptor 5 (CCR5) binding affinity of substituted 1-(3,3-diphenylpropyl)-piperidinyl amides and ureas and toxicity of aromatic compounds have been performed. The gene expression programming (GEP) was used to select variables and produce nonlinear QSAR models simultaneously using the selected variables. In our GEP implementation, a simple and convenient method was proposed to infer the K-expression from the number of arguments of the function in a gene, without building the expression tree. The results were compared to those obtained by artificial neural network (ANN) and support vector machine (SVM). It has been demonstrated that the GEP is a useful tool for QSAR modeling.
Shi
Weimin
W
Department of Chemistry, Zhengzhou University, Zhengzhou 450052, China.
Zhang
Xiaoya
X
Shen
Qi
Q
D000465:Algorithms; D000577:Amides / Q000737:chemistry / Q000378:metabolism; D000818:Animals; D001185:Artificial Intelligence; D065100:CCR5 Receptor Antagonists; D016466:CHO Cells; D006224:Cricetinae; D003412:Cricetulus; D019143:Evolution, Molecular; D006801:Humans; D016571:Neural Networks, Computer; D009930:Organic Chemicals / Q000494:pharmacology* / Q000633:toxicity*; D021281:Quantitative Structure-Activity Relationship; D019713:Receptors, CCR5 / Q000235:genetics* / Q000378:metabolism; D014508:Urea / Q000737:chemistry / Q000378:metabolism
D000577:Amides; D065100:CCR5 Receptor Antagonists; D009930:Organic Chemicals; D019713:Receptors, CCR5; D014508:Urea