The resistance of weeds is a problem which can be overcome by finding new herbicides. For this purpose, beyond the experimental methods, in silico approaches can be helpful, as a starting point. In this regard, pharmacophore mapping and 3D-QSAR studies were carried out on several series of herbicide, already known to act on the Photosystem II (PS II) D1 protein. Using PHASE software, three pharmacophore features, H-bond acceptor (A), hydrophobic (H) and aromatic ring (R) were taken into account to be the best hypothesis. For this hypothesis an atom-based 3D-QSAR model was generated with statistically significant parameters (the correlation coefficient of regression (R²) of 0.839, the standard error of estimates (SD) of 0.370, the Fisher test (F) of 53.7 for the training set, the external explained variance Q² = 0.640, the Pearson-R = 0.916 and Root Mean Square Error (RMSE) = 0.572, for the test set). This hypothesis, validated by the 3D atom-based QSAR approach, assures the selection of novel scaffolds of herbicide derivatives and can be used for the design of new chemical entities active on the PS II D1 protein.