In this study, we developed a data-driven molecular design pipeline that leverages both the structural and bioactivity information of known ligands to generate de novo bespoke molecules. We pretrained two CLMs, each with a distinct pretraining strategy, on a large set of patented compound structures (one for molecular generation and one for classification). Both CLMs were fine-tuned on inhibitors of phosphoinositide 3-kinase gamma (PI3Kγ), which is an anticancer, anti-inflammatory, and immunomodulatory drug target . For rapid validation, commercially available compounds from the set of de novo generated molecules were tested, as opposed to synthesizing them. A new nanomolar ligand of phosphoinositide 3-kinase gamma (PI3Kγ) was identified.