Pharmacophore modelling and 4D-QSAR study of ruthenium(II) arene complexes as anticancer agents (inhibitors) by electron conformational-genetic algorithm method


Yavuz S., Sabancı N., SARIPINAR E.

Current Computer-Aided Drug Design, cilt.14, sa.1, ss.79-94, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 14 Sayı: 1
  • Basım Tarihi: 2018
  • Doi Numarası: 10.2174/1573409913666170529103206
  • Dergi Adı: Current Computer-Aided Drug Design
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.79-94
  • Anahtar Kelimeler: 4D-QSAR, Electron conformational-genetic algorithm method, Pharmacophore, Ruthenium(ii) arene complexes
  • Erzincan Binali Yıldırım Üniversitesi Adresli: Hayır

Özet

© 2018 Bentham Science Publishers.Objective: The EC-GA method was employed in this study as a 4D-QSAR method, for the identification of the pharmacophore (Pha) of ruthenium(II) arene complex derivatives and quantitative prediction of activity. Methods: The arrangement of the computed geometric and electronic parameters for atoms and bonds of each compound occurring in a matrix is known as the electron-conformational matrix of congruity (ECMC). It contains the data from HF/3-21G level calculations. Compounds were represented by a group of conformers for each compound rather than a single conformation, known as fourth dimension to generate the model. ECMCs were compared within a certain range of tolerance values by using the EMRE program and the responsible pharmacophore group for ruthenium(II) arene complex derivatives was found. For selecting the sub-parameter which had the most effect on activity in the series and the calculation of theoretical activity values, the non-linear least square method and genetic algorithm which are included in the EMRE program were used. In addition, compounds were classified as the training and test set and the accuracy of the models was tested by cross-validation statistically. Results: The model for training and test sets attained by the optimum 10 parameters gave highly satisfactory results with R2 training= 0.817, q2=0.718 and SEtraining=0.066, q2 ext1 = 0.867, q2 ext2 = 0.849, q2 ext3 =0.895, ccctr = 0.895, ccctest = 0.930 and cccall = 0.905. Conclusion: Since there is no 4D-QSAR research on metal based organic complexes in the literature, this study is original and gives a powerful tool to the design of novel and selective ruthenium(II) arene complexes.