Fragment-based methods offer an alternative, by assembling larger structures incrementally from smaller, pre-defined components. This approach has gained traction in automated de novo molecule design frameworks like FRAME and MolSLEPA , which focus on ligand design and material sciences, respectively. Beyond automated frameworks, fragment-based assembly empowers expert-driven, manual molecule creation. Users have control at each fragment addition, ensuring the resulting structure aligns with specific requirements at any intermediate stage of the building process. This approach not only be useful for manual design but also for refining predictions from deep learning models by providing more control over the final structure.