In our QSAR study, pharmacophore identification and biological activity estimation of 80 methanone derivatives were performed with the Electron Conformation Genetic Algorithm approach. Using the geometric, thermodynamic and topological properties of molecules from the data obtained from quantum chemical calculations in the HF/3-21 G basis set, the Electron Conformational Matrices of Congruity were generated by the EMRE software. Taking into account the pharmacophores atoms, 804 parameters were prepared. The nonlinear least squares optimization technique and genetic algorithm were used to determine the variables affecting the biological activity values for the calculation of the biological activity values of the studied molecules. 4D-QSAR approach the EC-GA method, that ensures pharmacophore detection, variable selection and quantitative bioactivity prediction, is used to calculate biological activity values of methanone derivatives. The model for the training and test sets attained by the optimum 8 parameters gave highly satisfactory results with Rtraining2 = 0.834, q(2) = 0.768 and SEtraining = 0.075, qext12 = 0.875, qext22 = 0.839, qext32 = 0.764, ccc(tr) = 0.908, ccc(test) = 0.929 and ccc(all) = 0.920. The interaction between the studied molecules and the live cancer protein which ID is 2H80 at DockingServer was examined to find the activity of the molecules examined in molecular placement calculations.