The hypotheses are generated with cost functions and correlation values by which they are estimated. The fixed cost, total cost and null cost values are calculated by HypoGen module during the hypotheses generation. The fixed cost is the lowest possible cost representing a hypothetically simplest model that fits all data perfectly, whereas the null cost value is equal to the maximum occurring error cost. For a more statistically significant hypothesis, there should be greater difference between these two cost values. The possibility of correlating the experimental and estimated activity data enhances to 75-90% with a cost difference of 40-60 bits between the total and null cost values [57, 58] . In the present work, the null cost value of the top 10 hypotheses is 182.366 and the fixed cost value is 75.791. Thus, a difference of 106.575 bits between fixed cost and null cost consigns to a meaningful pharmacophore model. Moreover, the total cost of the generated hypothesis should be closer to the fixed cost. All ten generated hypotheses scored a total cost closer to the fixed cost which leads to a good model. Statistically significant factors which include cost values, correlation coefficients (r), pharmacophore features, and root mean square deviations (RMSDs) of all 10 hypotheses are listed in Table 1 . The configuration cost enumerates the entropy of the hypothetical space and its value should not exceed a maximum value of 17 for a significant pharmacophore model [59, 60] . The configuration cost value of 16.601 was obtained for this pharmacophore generation calculation.