Implementation Details. We take the publicly available pre-trained models from the GitHub Repository for HierVAE and MoFlow , respectively. All the molecular properties are calculated by RDKit and . We (1) Our proposed method, ChemSpacE, as the first attempt for molecule manipulation, achieves excellent performance in manipulating both single and multi-properties of molecules with two stateof-the-art molecule generative models (VAE-based and Flow-based). For some important molecular properties (e.g., QED), we (with MoFlow) achieve 52% manipulation strict success rate in ZINC dataset. We outperform the baseline methods 6× on average.