12 research outputs found
Ligand-based determination of the 3D pharmacophore model of the receptor by non-linear least squares (NLLS) in the MCET method
Östrojen-Bağımlı Meme Kanserine Karşı Güçlü Aromataz İnhibitörleri Olarak Flavonoidlerin MCET Metoduyla 4D-QSAR İncelenmesi
Potansiyel Antitümör Ajanları Olarak Kumarin Türevlerinin 4D-QSAR ve Moleküler Docking Çalışmaları
4D-QSAR and Molecular Docking Studies on Thiosemicarbazones and 1,3-thiazoles with Antitumor Activity
Investigation of inhibitory activity of monoamine oxidase A with 4D-QSAR using Fukui indices identifier
© 2020 Elsevier LtdThe inhibitory activity of monoamine oxidase A (MAO-A) was investigated as 4D- Quantitative Structure-Activity Relationship (4D-QSAR) using Molecular Conformer Electron Topological (MCET), a ligand-based method. The activity of MAO-A according to a 3D interaction was explained by a descriptor with the Fukui indices, which represents the hard-soft acid / base reactivity of atoms. The Fukui indices of atoms in clusters was used as the Local Reactive Descriptor (LRD) of the ligand side. Stochastic approaches were made for each sub-cluster proposed by the Genetic Algorithm (GA). The parameters at receptor side of pharmacophore (Pha) were calculated based on the Fukui indices used as descriptors on the ligand side. Pha was determined based on ligand of synthetic derivatives that are MAO-A inhibitors. Molecular conformers with the most suitable atoms with the template conformer can be selected as one of the most suitable spatial structures for interaction with the receptor. This serves to determine the LRD values of the atoms in the conformer Pha. Depending on the values of the descriptors of the ligand at the points of interaction, it may be either an activity-increasing auxiliary groups (AG) or anti-pharmacophore shielding groups (APS). The model was developed with Leave One Out-Cross Validation (LOO-CV), for the 24 molecules in the training set, and was validated for 8 molecules in the test set. Inhibitory activities determined from the established model were compared with experimental results. For the training set and the external cross validation test set compounds, the Q2 (0.829) and R2 (0.818) of the statistical parameters were calculated, respectively