There are several milestones for AI for drug discovery. For example, AlphaFold2 accurately predicted protein structure , considered one of the most challenging tasks in computational biology. Segler et al. utilized Monte Carlo tree search (MCTS) to combine three distinct neural networks trained on all available published reactions. This approach was employed to forecast the optimal retrosynthetic pathways for a given molecule. Zhavoronkov et al. used a rein forcement learning model to design new DDR1 kinase inhibitors and test activity in wet lab. LinearDesign is capable of effectively drug research and development has emerged as a hotspot in contemporary cutting-edge medical pharmaceutical research and entrepreneurship.