A DFT-based QSAR study on inhibition of human dihydrofolate reductase

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Date

2016-09-05

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Elsevier

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.

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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

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.