Drug discovery is a notoriously time-consuming and expensive process. The effectiveness of exploring vast chemical spaces during the initial phases of the process is crucial, as it lays the groundwork for identifying promising candidate molecules . In recent years, deep neural network architectures tailored to generative tasks have emerged as promising tools for accelerating early drug discovery, reducing time and financial investments .