The goal of the Flexible Topology method is to model a set of atoms that can continuously transform between different molecules. To implement this method, we use MD simulations that are coupled with an ML-based external force (MLForce ) that slowly nudges a set of ghost particles to become a drug-like molecule (Figure ). MLForce consists of three components: a molecular representation model, an assignment algorithm and a loss function. The molecular representation model defines a set of symmetry-invariant atomic environment vectors (AEVs) using functions introduced by Behler and Parrinello . The AEVs, concatenated with the ghost particle attributes, determine the set of features for each atom that describe both its environment and its identity. We discuss these in detail in Section .