Although the inclusion of additional descriptors has the potential to improve model performance, a particular challenge emerges when integrating atom features that need to satisfy constraints on their summative value across an entire molecule, for the learned molecular representation is aggregated from atom representations (Equation ). In the current Chemprop framework, the aggregation functions, whether they involve averaging, summing, or normalizing by a constant, can lead to information loss in this scenario. To overcome this limitation, we transformed relevant QM atom and bond features from continuous values to expanded vectors by radial basis function (RBF) expansion 7 before incorporating these descriptors into D-MPNN as follows (this step is not automatically done in Chemprop):