Abstract
An intriguing question in 3D-QSAR lies on which conformation(s) to use when generating molecular descriptors (MD) for correlation with bioactivity values. This is not a simple task because the bioactive conformation in molecule data sets is usually unknown and, therefore, optimized structures in a receptor-free environment are often used to generate the MD´s. In this case, a wrong conformational choice can cause misinterpretation of the QSAR model. The present computational work reports the conformational analysis of the volatile anesthetic isoflurane (2-chloro-2-(difluoromethoxy)-1,1,1-trifluoroethane) in the gas phase and also in polar and nonpolar implicit and explicit solvents to show that stable minima (ruled by intramolecular interactions) do not necessarily coincide with the bioconformation (ruled by enzyme induced fit). Consequently, a QSAR model based on two-dimensional chemical structures was built and exhibited satisfactory modeling/prediction capability and interpretability, then suggesting that these 2D MD´s can be advantageous over some three-dimensional descriptors.
Highlights
Quantitative structure–activity relationship (QSAR) studies try to find a correlation between chemical structures and the corresponding bioactivities by means of molecular descriptors (MDs)
While molecular conformation in vacuum is governed by intramolecular interactions, the bioconformation is ruled by enzyme induced-fit; optimized and bioactive geometries are probably different to each other and, to obtain insight on the action mechanism of a drug and substituent effects, MDs should not be generated over geometries optimized in a receptor-free environment
Receptor-dependent QSAR methods have been developed [9], but these are mostly complementary and are aimed at corroborating and/or rationalizing the results provided by the regression models, since the docking methodology itself provides intermolecular energies and docking scores that correlate with bioactivity
Summary
Quantitative structure–activity relationship (QSAR) studies try to find a correlation between chemical structures and the corresponding bioactivities by means of molecular descriptors (MDs) In this way, molecular architecture and substitution patterns in a series of congeneric molecules are described by calculable or empirical data having some relationship with biological activity, becoming the technique useful for understanding the action mechanism of related drugs, as well as to drive the synthesis of new drug like compounds. Despite not encoding conformational information, 2D-QSAR can incorporate other stereochemical properties and account for group sizes, substituent type and 2D shape of molecules These have shown to be sufficient parameters to obtain satisfactory correlation with bioactivity data and valuable understanding on structural requirements for drug development. The suitability of applying 3D information obtained from high level calculations (in a receptor-free environment) in QSAR modelling was evaluated using a comparative study of the optimized and bioactive conformations of the fluorinated anesthetic isoflurane, which binds to a 4-helix bundle protein (apoferritin) [12] and to the integrin LFA1 enzyme [13]
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