Abstract
Similarity-based virtual screening is used in drug discovery by using computational model for rapid evaluation of large number of chemical molecules. Similarity searches use 2D or 3D fingerprints and similarity coefficient to calculate the structural resemblance between each molecule in a chemical database and a target structure. The objective of this work is to determine the best coefficient to be used in similarity searching to get the optimal results. This paper will describe the experiment to perform the molecular similarity searching using different similarity coefficients, which focus on 2D UNITY or ECFP4 fingerprint on 5 activity classes. We will also highlight the different similarity values and the optimal results of similarity measures. All this could depend on what type of fingerprint. As a conclusion, we found that every combination measure has its own advantage. But to look for the best possible results, the nature of molecular activity class could also play an important role.