A series of naphthalene and non-naphthalene derivatives (n=42) having cytochrome P450 2A6 and 2A5 inhibitory activities, reported by Rahnasto et al., were subjected to QSAR and QAAR studies. The analyses were performed using electronic, spatial, shape and thermodynamic descriptors to develop quantitative models for prediction of the inhibitory activities and to explore importance of different descriptors for the responses. The data set was divided into training and test sets (with test set size being approximately 25% of the full data set size) based on K-means clustering applied on the standardized descriptor matrix. Genetic function approximation (GFA) and genetic partial least-squares (G/PLS) were used as chemometric tools for modeling, and the derived equations were of acceptable statistical and prediction (both internal and external) qualities although different equations varied in quality in a wide range (R(2): 0.561-0.898, R(a)(2): 0.508-0.870, Q(2): 0.495-0.814, R(pred)(2): 0.615-0.914, r(2): 0.679-0.905, r(0)(2): 0.639-0.904, r(m)(2): 0.494-0.876). In the case of CYP2A5 inhibition, the GFA derived QSAR model is better than the G/PLS derived model considering both internal and external validations. In the case of CYP2A6 inhibitory potency data, the GFA derived QSAR model is better than the G/PLS model considering internal validation whereas the latter is better in external validation (which is more important) than the former. The model development process was subjected to randomization test at 90% confidence level by taking into account the whole pool of descriptors, while the developed models were also subjected to randomization test (99% confidence level) for validation. Based on the randomization test results, GFA models are found to be superior to the G/PLS models. Among the parameters, which were found important in modeling both the responses, were different Jurs descriptors, electronic descriptors (like Sr, Apol), steric descriptors (like shadow indices, Molref), shape descriptors (like COSV, Fo) and lipophilicity descriptors. This indicates that the CYP2A5 and CYP2A6 inhibition of these compounds is related to charge distribution, surface area, electronic, hydrophobic and spatial properties of the molecules.