Similarity methods require a representation method for compounds, such as the Simplified Molecular Input Line Entry System (SMILES). SMILES is the most common method to represent and compare the compounds in 1D ( ). It converts a compound into a string, using symbols such as C, c, N, O for atoms and =, # for bonds (www.daylight.com/dayhtml/doc/theory/theory.smiles.html). SMILES are available in quantity structure-activity (QSAR), virtual screening, and toxicity prediction. An example of a similarity search algorithm is the fingerprint Similarity Search Algorithm (MuS-SeL), which can provide IC50 or Ki values for ligands ( ). Finally, other compound similarity methods exist in the literature, such as 2D-based compound similarity kernels (Figure ). Using data from known ligands that attach to target proteins to identify or synthesise new compounds with equivalent functionality, ligand-based drug discovery is necessary in developing new medicines. Atombased modelling is one method used in this approach whereby one may understand the interaction of the ligand with the target by analysing its spatial arrangement of atoms. By focussing on the precise arrangement of every atom, researchers may estimate likely binding affinities and create more potent molecules. Moreover, atom-based + atom type modelling considers the spatial organisation as well as the particular atom types-hydrogen, carbon, or nitrogen. This method helps one to understand more fully how different atomic interactions support the intensity and specificity of binding. The major functional groups of a ligand causing its biological effect are investigated using pharmacophore sites. This work finds and models these groups on a more abstract level. The pharmacophore sites identify key features such as hydrophobic regions and hydrogen bond donors or acceptors. These properties enable the synthesis of new ligands capable of strong interaction with the target protein. These methods let ligand-based drug development effectively speed up the identification and improvement of strong therapeutic prospects.