SGPT-RL , a model composed of a generative pre-trained transformer (a decoder-only version) augmented with the Reinforcement Learning (RL) strategy. SGPT-RL aimed to optimize binding affinities of molecules with their targets, the optimization was focused on two prerequisites; molecular docking and Quantitative Structure Activity Relationship (QSAR). The model has been evaluated on three measures; Moses distribution learning, and affinity towards Dopamine Receptor D2 (DRD2), and Angiotensin-Converting Enzyme 2 (ACE2). SGPT-RL generated notably valid and novel molecules in all tasks and outperformed the benchmark in molecular docking results. Moreover, SPGT-RL has learned conserved scaffold patterns on its own.