Molecular docking and 4D-QSAR studies of metastatic cancer inhibitor thiazoles

Turkmenoglu B., Güzel Y.

Computational Biology and Chemistry, cilt.76, ss.327-337, 2018 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 76
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1016/j.compbiolchem.2018.07.003
  • Dergi Adı: Computational Biology and Chemistry
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.327-337
  • Anahtar Kelimeler: Thiazole derivatives, Molecular docking, 4D-QSAR, MCET, CYTOTOXICITY DATA CC50, WATER MARINE SPONGES, C-13 CHEMICAL-SHIFTS, GROWTH-FACTOR-BETA, ANTI-HIV, PHARMACOPHORE, DERIVATIVES, CONSTRUCTION, SIMILARITY, ALKALOIDS
  • Erzincan Binali Yıldırım Üniversitesi Adresli: Hayır

Özet

By using the molecular docking and 4D-QSAR analysis, it is aimed to find the interaction points in the receptor binding site of transforming growth factor-beta (TGF-beta) used to inhibit invasion and metastasis. To elucidate the interaction points of receptor, different types of local reactive descriptor (LRD) of ligands have been used. Activity values related to interaction energy between the ligand-receptor (L-R) were determined by nonlinear least squares (NLLS) using the Levenberg-Marquardt (LM) algorithm. Using the Molecule Comparative Electron Topology (MCET) method, the 3D pharmacophore model (3D-PhaM) was obtained after alignment and superimposition of the molecules, and also confirmed by molecular docking method. With the leave one out-cross validation (LOO-CV) method, the best predictions are q(2) or r(CV)(2) = 0.789 for the 51 compounds in the internal training set and r(2) = 0.785 for the 13 compounds in the external test set. Furthermore, the predictive capability of the advanced QSAR model is more precisely calculated with the r(m)(2) metric (r(m)(2) = 0.769).