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The complex process to develop a successful therapeutic drug is lengthy and costly. In order to accelerate this process, molecular modeling has become a key component of drug design. Methods used in computational chemistry vary from Ab initio quantum chemistry methods, to semi-empirical calculations and molecular mechanics. A study of the anticancer activity of a series of 7-aryl- and 7-hetaryl-7-deazaadenosines published by Bourderioux (2011) showed that nucleosides with 5-member heterocycles at the position 7 were more potent in vitro cytostatic agents against hematological and solid tumor cell lines than molecules with 6-member heterocycles. We decided to conduct a quantitative structure–activity relationship (QSAR) analysis of these chemical moieties in order to have a better understanding of their structural properties and identify their molecular descriptors explaining their biological activities. We found that 5-member cyclic structures have three energy molecular descriptors that were negatively correlated to their biological activity, in particular, compounds with higher energies had higher biological potency represented by lower IC50 values. CLogP, a parameter of lipophilicity, was also found to be positively correlated to their biological activity, i.e. compounds with lower CLogP values had higher biological potency represented by lower concentrations inhibiting the growth of cancer cells by 50 %. Qualitatively, 5-member-ring heterocycles of 7-deazaadenosine had lower steric hindrance, i.e. were structurally smaller, than their 6-member counterparts. In this context, a QSAR analysis could be extraordinarily helpful in studying the mode of action of molecules with potential pharmacological relevance.