Probability-driven 3D pharmacophore mapping of antimycobacterial potential of hybrid molecules combining phenylcarbamoyloxy and N-arylpiperazine fragments

ABSTRACT

The current study examines in silico characterization of the structure-inhibitory potency for a set of phenylcarbamic acid derivatives containing an N-arylpiperazine scaffold, considering the electronic, steric and lipophilic properties. The main objective of the ligand-based modelling was the systematic study of classical comparative molecular field analysis (CoMFA)/comparative molecular surface analysis (CoMSA) performance for the modelling of in vitro efficiency observed for these phenylcarbamates, revealing their inhibitory activities against a virulent Mycobacterium tuberculosis H₃₇R_v strain. We compared the findings of efficiency modelling produced by a standard 3D methodology (CoMFA) and its neural counterparts (CoMSA) regarding multiple training/test subsets and variables used. Moreover, systematic space inspection, splitting values into the analysed training/test subsets, was performed to monitor statistical estimator performance while mapping the probability-driven pharmacophore pattern. Consequently, a ‘pseudo-consensus’ 3D-quantitative structure-activity relationship (3D-QSAR) approach was applied to retrieve an ‘average’ pharmacophore hypothesis by the investigation of the most densely populated training/test subpopulations to specify the potentially important factors contributing to the inhibitory activity of phenylcarbamic acid analogues. In addition, examination of descriptor-based similarity with a principal component analysis (PCA) procedure was employed to visualize noticeable variations in the performance of these molecules with respect to their structure and activity profiles.

KEYWORDS:

• CoMFA
• CoMSA
• pharmacophore mapping
• variable elimination
• phenylcarbamic acids

Acknowledgements

The authors thank Professor Johann Gasteiger for facilitating access to the scientific programs. We would like to acknowledge OpenEye and OpenBabel Scientific Software for the free academic license. This study was also partially supported by SANOFI-AVENTIS Pharma Slovakia.

Conflict of Interest

The authors declare no conflict of interest.

Supplemental data

Supplemental data for this article can be accessed at: https://doi.org/10.1080/1062936X.2018.1517278