title: Prediction of Activities of BRAF (V600E) Inhibitors by SW-MLR and GA-MLR Methods.
abstract: BACKGROUND
  Quantitative structure-activity relationship (QSAR) models could provide both statistical significance and useful chemical insights for drug design. The QSAR method has found applications for predicting diverse properties of organic compounds, including antiviral activities, toxicities and biological activities. In this work, a quantitative structure-activity relationship was utilized for the prediction of allosteric BRAF (V600E) inhibitory activities.
  
  
  METHODS
  A data set which contains 54 molecules was classified into training and test sets. Stepwise (SW) and genetic algorithm (GA) methods were employed for feature selection. The models were validated using the cross-validation and external test set.
  
  
  RESULTS
  Results showed that the GA approach is a more powerful technique than SW for the selection of suitable descriptors. The squared cross-validated correlation coefficient for leave-one-out of 0.702 and squared correlation coefficient of 0.793 was obtained for the training set compounds by GA-MLR model.
  
  
  CONCLUSIONS
  The obtained GA-MLR model could be applied as a worthwhile model for designing similar groups of the mentioned inhibitors.
authors.affiliation: Department of Chemistry, Payame Noor University (PNU)Tehran 19395-3697, Iran.
authors.forename: Parinaz
authors.initials: P
authors.lastname: Pargolghasemi
authors.affiliation: Young Researchers and Elite Club, Ardabil Branch Islamic Azad University, Ardabil, Iran.
authors.forename: Mir Saleh
authors.initials: MS
authors.lastname: Hoseininezhad-Namin
authors.affiliation: Department of Chemistry, Ardabil Branch Islamic Azad University, Ardabi, Iran.
authors.forename: Aiyoub Parchehbaf
authors.initials: AP
authors.lastname: Jadid
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D017076:Computer-Aided Design; D055808:Drug Discovery / Q000379:methods; D006801:Humans; D016014:Linear Models; D008954:Models, Biological; D047428:Protein Kinase Inhibitors / Q000737:chemistry* / Q000494:pharmacology*; D048493:Proto-Oncogene Proteins B-raf / Q000037:antagonists & inhibitors* / Q000378:metabolism; D021281:Quantitative Structure-Activity Relationship; D054852:Small Molecule Libraries / Q000737:chemistry / Q000494:pharmacology
chemical_list: D047428:Protein Kinase Inhibitors; D054852:Small Molecule Libraries; C482119:BRAF protein, human; D048493:Proto-Oncogene Proteins B-raf
keywords: BRAF (V600E) inhibitors; QSAR; genetic algorithm; inhibitory activity.; multiple linear regression; stepwise