Structured State-Space Sequence Models (S4), engineered by , with an architecture combining a Long Short-Term Memory (LSTM) and a transformer. The uniqueness of this architecture is that it combines the fast-generation capabilities of the LSTM with its element-by-element strategy along with the all-at-once molecular processing by the transformer, avoiding the extensive computational power transformers require. This dual model has shown success when tested and benchmarked in its ability to learn the bioactivity of compounds, chemical space exploration, the design of natural products, and was preferred when long sequences were present. S4's ability in generating molecules with suitable Molecular Dynamic (MD) properties and potencies was validated by testing the Mitogen-Activated Protein Kinase 1 inhibitors (MAPK1inhibitors) it produced.