Abstract
We have recently reported the development and validation of quantum mechanical (QM)-based hydrophobic descriptors derived from the parametrized IEF/PCM-MST continuum solvation model for 3D-QSAR studies within the framework of the Hydrophobic Pharmacophore (HyPhar) method. In this study we explore the applicability of these descriptors to the analysis of selectivity fields. To this end, we have examined a series of 88 compounds with inhibitory activities against thrombin, trypsin and factor Xa, and the HyPhar results have been compared with 3D-QSAR models reported in the literature. The quantitative models obtained by combining the electrostatic and non-electrostatic components of the octanol/water partition coefficient yield results that compare well with the predictive potential of standard CoMFA and CoMSIA techniques. The results also highlight the potential of HyPhar descriptors to discriminate the selectivity of the compounds against thrombin, trypsin, and factor Xa. Moreover, the graphical representation of the hydrophobic maps provides a direct linkage with the pattern of interactions found in crystallographic structures. Overall, the results support the usefulness of the QM/MST-based hydrophobic descriptors as a complementary approach for disclosing structure-activity relationships in drug design and for gaining insight into the molecular determinants of ligand selectivity.
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Acknowledgments
We thank the financial support from Ministerio de Economía y Competitividad (SAF2014-57094-R) and the Generalitat de Catalunya (2014-SGR-1189). We are grateful to the Consorci de Serveis Universitaris de Catalunya (CSUC) for computational resources. FJL acknowledges the support from ICREA Academia.
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This paper belongs to Topical Collection MIB 2015 (Modeling Interaction in Biomolecules VII)
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Histograms of molecular properties (Figure S1), structural comparison of targets (Figure S2), comparison of electrostatic and non-electrostatic components of the octanol/water partition coefficient (Figure S3), and tables reporting the experimental and predicted (H2 model) activities (Table S1-S3) and selectivities (Tables S4-S6) models.
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Ginex, T., Muñoz-Muriedas, J., Herrero, E. et al. Application of the quantum mechanical IEF/PCM-MST hydrophobic descriptors to selectivity in ligand binding. J Mol Model 22, 136 (2016). https://doi.org/10.1007/s00894-016-2991-3
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DOI: https://doi.org/10.1007/s00894-016-2991-3