The effect of the diversity of molecules in sets and similarity of sets on the quality of prediction in QSAR studies

We report here: (a) formulas/procedures for calculating the similarity of molecules, considering their chemical structure, size, shape and hydrophilicity (b) a procedure for clusterization of the sets of molecules, according to similarity (c) formulas/procedures for calculating the diversity of molecules in clusterized sets as well as similarity of clusterized sets, based on Shannon Entropy formalism The paper analyses the influence of the diversity of molecules and similarity of calibration/prediction sets on the quality of prediction for prediction set molecules. The calculated influence of certain molecular feature (chemical structure, size, shape and hydrophilicity) on toxicity depends on the structure of the database, specifically the number of molecules and diversity of molecules having analyzed molecular feature. A QSAR analysis of 49 phenol derivatives revealed the effect of the diversity of molecules in sets and of the similarity of sets on the quality of prediction for prediction set molecules: (a) a direct correlation with the similarity of sets, regardless of analyzed molecular feature (b) an inverse correlation with the diversity of molecules in the calibration set, from the point of view of chemical structure, size and shape (c) a direct correlation with the diversity of molecules in calibration set, from the point of view of hydrophilicity (d) a direct correlation with the diversity of molecules in prediction set, regardless of analyzed feature.