Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/29513
Title: A DFT-based QSAR study on inhibition of human dihydrofolate reductase
Authors: Karabulut, Sedat
Sizochenko, Natalia
Leszczynski, Jerzy
Uludağ Üniversitesi/Tıp Fakültesi/Kadın Hastalıkları ve Doğum Anabilim Dalı.
0000-0002-7558-8166
Orhan, Adnan
V-5292-2019
56671094200
Keywords: Biochemistry & molecular biology
Computer science
Crystallography
Mathematical & computational biology
Dihydrofolate reductase
Diaminopyrimidine
DFT
Descriptors
QSAR
QSARins
Neural-networks
Pneumocystis-carinii
Potent inhibitors
Derivatives
Triazines
Analogs
Complex
Future
Model
Chemical bonds
Electronegativity
Patient treatment
Viruses
Computational chemistry
Issue Date: 5-Sep-2016
Publisher: Elsevier
Citation: Karabulut, S. vd. (2016). "A DFT-based QSAR study on inhibition of human dihydrofolate reductase". Journal of Molecular Graphics and Modelling, 70, 23-29.
Abstract: Diaminopyrimidine derivatives are frequently used as inhibitors of human dihydrofolate reductase, for example in treatment of patients whose immune system are affected by human immunodeficiency virus. Forty-seven dicyclic and tricyclic potential inhibitors of human dihydrofolate reductase were analyzed using the quantitative structure-activity analysis supported by DFT-based and DRAGON-based descriptors. The developed model yielded an RMSE deviation of 1.1 a correlation coefficient of 0.81. The prediction set was characterized by R-2 = 0.60 and RMSE = 3.59. Factors responsible for inhibition process were identified and discussed. The resulting model was validated via cross validation and Y-scrambling procedure. From the best model, we found several mass-related descriptors and Sanderson electronegativity-related descriptors that have the best correlations with the investigated inhibitory concentration. These descriptors reflect results from QSAR studies based on characteristics of human dihydrofolate reductase inhibitors.
URI: https://doi.org/10.1016/j.jmgm.2016.09.005
https://www.sciencedirect.com/science/article/pii/S109332631630170X
http://hdl.handle.net/11452/29513
ISSN: 1093-3263
1873-4243
Appears in Collections:Scopus
Web of Science

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