Motivated by the fact that aforementioned approaches have only an intrinsic knowledge of the similarity between molecules, given by the way the molecular pairs are constructed, we propose in this paper a novel framework to systematically sample target molecules that are simultaneously associated to precedented transformations and are similar to the source molecule. We stress the fact that similarity alone is not enough as there exist target molecules similar to a source molecule that should be associated to low precedented transformations, for example chemically unstable target molecules or target molecules containing an unusual atomic element not represented in the training set.