Multi-Property Constrained Optimization. As this is not reported by previous work on molecule optimization, we propose to optimize QED and penalized logP as a multi-property constrained optimization task. We also propose two simple baselines: (1) we add up the two properties (QED and penalized logP) to be optimized as a new objective and runs single-property constrained optimization on it, (2) we take into account the two gradient directions on the two properties and each step we move to both directions for gradient ascent. As shown in Appendix (Table ), we demonstrate the capability of ChemSpacE for efficient multi-objective optimization. Our method improves both QED and penalized logP more than the two gradient-based methods. We showcase two examples in Fig. that demonstrates ChemSpacE can optimize molecules with high structure perseverance and desired properties.