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Theoretical models to predict the inhibitory effect of ligands of sphingosine kinase 1 using QTAIM calculations and hydrogen bond dynamic propensity analysis.

Authors :
Vettorazzi, Marcela
Menéndez, Cintia
Gutiérrez, Lucas
Andujar, Sebastián
Appignanesi, Gustavo
Enriz, Ricardo D.
Source :
Journal of Computer-Aided Molecular Design. Jul2018, Vol. 32 Issue 7, p781-791. 11p.
Publication Year :
2018

Abstract

We report here the results of two theoretical models to predict the inhibitory effect of inhibitors of sphingosine kinase 1 that stand on different computational basis. The active site of SphK1 is a complex system and the ligands under the study possess a significant conformational flexibility; therefore for our study we performed extended simulations and proper clusterization process. The two theoretical approaches used here, hydrogen bond dynamics propensity analysis and Quantum Theory of Atoms in Molecules (QTAIM) calculations, exhibit excellent correlations with the experimental data. In the case of the hydrogen bond dynamics propensity analysis, it is remarkable that a rather simple methodology with low computational requirements yields results in excellent accord with experimental data. In turn QTAIM calculations are much more computational demanding and are also more complex and tedious for data analysis than the hydrogen bond dynamic propensity analysis. However, this greater computational effort is justified because the QTAIM study, in addition to giving an excellent correlation with the experimental data, also gives us valuable information about which parts or functional groups of the different ligands are those that should be replaced in order to improve the interactions and thereby to increase the affinity for SphK1. Our results indicate that both approaches can be very useful in order to predict the inhibiting effect of new compounds before they are synthesized. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0920654X
Volume :
32
Issue :
7
Database :
Academic Search Index
Journal :
Journal of Computer-Aided Molecular Design
Publication Type :
Academic Journal
Accession number :
131115318
Full Text :
https://doi.org/10.1007/s10822-018-0129-7