**4. Conclusion**

In this study, 2D- and 3D-QSRR analyses were used to predict the linear retention indices of a set of alkylated phenols. The multidimensional-QSRR models gave good statistical results in terms of rCV and r values. The stepwise MLR and CoMFA models showed high internal and external consistency; this is verified using different validation methods to evaluate their statistical quality. External validation using a test series verified the capacity of these models to estimate with appropriate precision the linear retention indices of alkylated phenols. In addition, the stepwise MLR equation and CoMFA contour plots can identify that physicochemical properties, organic functional groups, and chemical molecular fragments strongly correlated with the linear retention indices of this studied compounds. The highlighted features are important information for delineating the chemical space, which can be used to design new volatile alkylated phenols. This study consists of the first step explored to code a particular odor of this group of molecules, followed by docking molecular study that allows understand the mechanism of activation of olfactory receptor present in the nasal cavity by this kind of chemical compounds.

### **Acknowledgements**

We are grateful to the "Association Marocaine des Chimistes Théoriciens" (AMCT) for its pertinent help concerning the programs.
