In the drug discovery field, the current problems are sluggish drug development due to the depletion of target molecules and other factors, and rising development costs. In silico drug discovery is expected to be a drug discovery support technology that will lead to the discovery of novel drug target molecules, active sites, lead compounds to more efficient development processes. In silico drug discovery can be broadly classified into methods directed by ligand information(ligand-based drug design: LBDD)and methods based on the 3-dimensional structure of target proteins(structure-based drug design: SBDD). LBDD method is based on similar structural and physicochemical properties in overall structure, or substructures and pharmacophore, using known ligands information, and has the advantage that it can be applied even when the 3-dimensional structure of the target protein is unknown. On the other hand, SBDD is a method to discovery and design compounds directed to the 3-dimensional structure of the target protein based on the'lock and key'theory, in which the target protein selects and binds to specific ligands, and has the advantage of leading to the discovery of diversity compounds. This paper outlines the basics of LBDD and SBDD, and the latest topics using AI and large-scale simulations. Furthermore, as an example of in-silico drug discovery support, in-silico drug discovery support research for the discovery of protein-protein interaction inhibitors targeting early-stage lung adenocarcinoma is also introduced.