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The development of computer science and technology has propelled global drug research and development along a path of rapid growth. Computer-aided drug design techniques, which enable the rapid screening of thousands of molecules, play a vital role in this process. Based on computational chemistry, these techniques use computer simulations, calculations, and analyses to determine the relationships between drugs and biological macromolecules such as receptors, thereby facilitating the optimization and design of lead compounds. When applied to new drug research, this technology not only reduces the costs associated with drug development but also **shortens the time it takes for new drugs to reach the market. It is an important method in computer-aided drug design, which relies on ligands. The kinetic properties of the binding between drug molecules and target molecules are strongly correlated with their pharmacological efficacy in the body; therefore, molecular design aimed at improving these binding kinetic properties offers a new approach for drug development. Molecular model construction can provide insights for subsequent research. Ligand-based drug design involves the development of drugs by analyzing the structures of known ligands that bind to receptors; it is also known as indirect drug design, and includes pharmacophore modeling and quantitative structure-activity relationship models (QSAR). (1) In terms of the pharmacophore model, if researchers employ receptor-based drug design methods, they examine the selection of histone deacetylase (HDAC) target proteins as well as molecular docking techniques, thereby establishing reliable molecular docking models. The constructed model was used in combination to screen the Drugbank database, yielding two candidate compounds with novel scaffolds. Molecular dynamics simulations were used to study the interactions between the candidate compounds and the reference molecule Trichostatin A with proteins, and it was found that both could bind stably to HDACs. Among them, compound DB03889 exhibited a stronger binding ability than Trichostatin A. This study provides potential lead compounds for the discovery of new HDAC inhibitors. Lead compounds refer to chemical structures that possess certain biological activities; through the optimization of these lead compounds, by making structural changes and modifications to them, drugs with excellent pharmacological effects can be developed. Medici can provide clients with drug development services covering a wide range of targets and disease areas, including everything from the discovery of active compounds, target validation, and optimization of lead compounds to the selection of preclinical candidate drugs. A pharmacophore is a set of elements that characterize the biological activity of a compound; it represents the structural features necessary to maintain that compound’s activity. It reflects certain common atomic, genetic, or chemical functional structures as well as spatial orientations in the three-dimensional structure of these compounds, and it is often these factors that determine the activity of a ligand. By analyzing the common pharmacophoric characteristics of known ligands that bind to receptors, drugs can be screened out. If any researchers carry out ligand-based computer-aided drug design to construct a pharmacophore model for small-molecule inhibitors of (1,3)-β-D-glucan synthase. The researchers selected 6 small molecules with diverse structures and good enzyme-inhibiting activity to form a training set. They used the HipHop algorithm from Catalyst’s pharmacophore generation module to construct pharmacophore models, and evaluated these models using the established Decoyset3D database. The research findings indicate that the development of GS small-molecule inhibitors based on active ligands for this project provides certain guidance for the design and discovery of novel small-molecule GS inhibitors. (2) QSAR models: The anticancer activity of coumarin derivatives is attracting increasing attention and research. Some researchers have used quantitative structure-activity relationship (QSAR) methods to study the relationship between the structure of these compounds and their anticancer activity, and to analyze the key factors that influence this activity. Furthermore, studies have utilized QSAR analysis of marine substances to identify molecular descriptors with statistically significant anti-tumor activity and to analyze their theoretical significance, thereby providing a theoretical basis for the development of new drugs and guiding the synthesis of new compounds. QSAR relies on the three-dimensional structures of ligands and targets; by taking into account changes in internal molecular energy as well as energy changes resulting from intermolecular interactions, it establishes quantitative relationships between a range of known physicochemical properties and three-dimensional structural parameters of drugs. These relationships are then used for optimization and modification. Thus, QSAR can not only simulate the structural characteristics of ligands that bind to receptors but also predict the activity of drugs. However, ligand-based drug design only analyzes the structural characteristics of the ligands, ignoring the impact of receptor structure on the interaction between the drug and the target, which often leads to false positives. The difficulty in defining a practical pharmacophore model lies in the fact that such a model includes only the key pharmacophore elements necessary for binding to the target. During the interaction process, the spatial configurations of the receptor and ligand must continuously change to facilitate binding between them; moreover, proteins are not stationary, and their functions are governed by their internal dynamics, so it is also very important to understand their dynamic properties. Molecular model construction and application study of HDAC and PP1 inhibitors. Construction of pharmacophore models for small molecule inhibitors of (1,3)-β-D-glucan synthase.