The Superposing Significant Interaction Rules (SSIR) method is revised and implemented. The method is a simple combinatorial procedure, which deals with in situ generated rules among a dichotomized congeneric molecular family, selecting the most probabilistically relevant ones. The mere counting of the number of relevant rules attached to new compounds generates a molecular ranking useful for database filtering, refinement and prediction. The algorithm only needs for a symbolic molecular representation and this allows for mining the database in a confidential manner. Third parties will not know the real compounds that are on the way to be worked out. The procedure is tested for a complete series of substituted amino acids. Areas under the receiver operating characteristic (AU-ROC) are always greater than 0.9 for all the following tried protocols: training, leave-one out, balanced leave-two-out and 5-fold cross validations and, finally, a stochastic series of calculations combined with a randomization test.