Two-step hierarchical assignments on molecular graphs
Andreas Jahn, Nikolas Fechner, Georg Hinselmann, Andreas Zell · Chemistry Central Journal · 2009
Measures for the similarity of molecules are of interest for several in silico based tasks like virtual screening or de novo structure design. The Optimal Assignment Kernel (OAK) [1] is a successful similarity measure, although it is not a valid kernel, since the function is not positive definite [2]. Careful investigations of the assignment on the atom level disclose that the optimal assignment with the Hungarian algorithm may result in topological errors. These errors are mappings of atoms from chemical substructures like ring systems to atoms of the other molecule, which belong to different substructures or even can be scattered among the molecule. This yields an overall higher similarity score but is problematic from a chemical point of view. To avoid these topological errors we developed a two-step hierarchical assignment method and compared it with the OAK.