APPLICATION OF EC-GA METHOD TO PHTHALAZINE ANALOGUES AS GABAA RECEPTOR ANTAGONISTS


Köprü S. , Sarıpınar E.

3rd Mediterranean Symposium on Medicinal and Aromatic Plants (MESMAP-3), 2017 Cyprus, Girne, Kıbrıs (Kktc), 13 - 16 Nisan 2017, ss.274-275

  • Basıldığı Şehir: Girne
  • Basıldığı Ülke: Kıbrıs (Kktc)
  • Sayfa Sayıları: ss.274-275

Özet

ɤ-Aminobutyric acid (GABA) is a major inhibitory aminoacid neurotransmitter receptor in the central nervous system and play important role regulation of brain excitability, many drugs such as benzodiazepines, barbiturates, neurosteroids [1]. The aim of this study was construct a 4D-QSAR model for 98 phthalazine analogues using Electron Conformational-Genetic Algorithm method [2]. EC-GA consist of three main step. At first conformational analysis and quantum chemical calculations of compounds were performed Spartan 10 software at Hartree Fock 6-31 G* level and water was used as solvent. The second step ECMC matrix was prepared all the conformers of all compounds that contains distances between atoms and mulliken charges for pharmacophore estimation. After the pharmacophore analysis, C1, C4, C7, C8, O1, C18, N5 atoms were dedected the pharmacophore group for explain drug-receptor mechanism in phthalazine derivatives. The last step merges with GA and cross validation tecnique for to predict the theoretical activity and select the best subset of descriptors. The data set of 98 molecules was randomly divided training and test set. In this model 70 molecules training, 28 molecules test set was used. Due to predictive capabilities best subset of descriptors were calculated for a range of 1-14 parameters at MATLAB software. Hence the model attains a stable situation as optimum 10 parameter number. LOO-CV method was evaluated for the predictive ability of 4D-QSAR model and E-statistical method was carried out to determination of the effect selected parameters. R2training, R2test, q2, q2ext1, q2ext2, q2ext3 and con1, con2, con3 values are given respectively 0.796, 0.732, 0.720, 0.757, 0.726, 0.751, 0.887, 0.852, 0.881.

 

This work was supported by the Research Fund of Erciyes University under [grant number FBD-40-1215]

Keywords: QSAR, EC-GA, Phthalazine, Pharmacophore, Genetic Algorithm  

References:

[1] Russell  M. G. N., Carling R. W., Atack R. J., Bromidge A. F., Cook M. S., Hunt P., Isted C., , Lucas M., McKernan M. R., Mitchinson A., Moore W. K., Narquizian R.,  Macaulay J. A., Thomas D., Thompson A. S., Wafford A. K.. and Castro L. J., (2005). Discovery of Functionally Selective 7,8,9,10-Tetrahydro-7,10-ethano-1,2,4-triazolo [3,4-α] phthalazines as GABAA Receptor Agonists at the α3 Subunit, J. Med. Chem., 48, 1367-1383.

[2] Sarıpınar E., Geçen N., Şahin K., Yanmaz E. (2010). Pharmacophore Identification and Bioactivity Prediction For Triaminotriazine Derivatives by Electron Conformational-Genetic Algorithm Qsar Method, European Journal of Medicinal Chemistry, 45, 4157-4168.