Abstract: A system and method for exploring a chemical space during molecular design for at least one top hit molecule using a machine learning (ML) model are provided. The method includes (i) representing the at least one molecule stored in a drug library into at least one vector; (ii) clustering the at least one vector to obtain at least one cluster of molecules into one or more clusters; (iii) uniformly sampling a first subset of molecules from each cluster of molecules; (vi) determining a docking score for sampled subset of molecules; (iv) training the ML model by correlating sampled subset of molecules with docking score; (viii) computing acquisition function values for a second subset of molecules from each cluster; and (ix) determining at least one top hit molecule based on the computed acquisition function values, thereby exploring the chemical space for the at least one top hit molecule.