Discovering new drug molecules is a pivotal yet challenging process due to the near-infinitely large chemical space and notorious demands on time and resources. Numerous generative models have recently been introduced to accelerate the drug discovery process, but their progression to experimental validation remains limited, largely due to a lack of consideration for synthetic accessibility in practical settings. In this work, we introduce a novel framework that is able to generate new chemical structures while ensuring synthetic accessibility. Specifically, we introduce a postfix notation of synthetic pathways to represent molecules in chemical space and design a model to project molecular graphs to postfix notations. We demonstrate the model's generalization capacity by its compatibility with novel chemical building blocks, and we highlight the model's ability to: (a) generate structurally similar, synthesizable analogs for unsynthesizable molecules, thereby preserving their properties, and (b) explore the local synthesizable chemical space around hit molecules.