Introduction
The emergence of computer-aided drug design (CADD) has greatly accelerated the process of drug research. After nearly 40 years of development, this technology has gradually matured and resulted in many successful cases. Additionally, computer-aided drug design technology is also renowned for its most intuitive model that greatly promotes the development of novel drugs.
1 What is CADD?
Computer-aided drug design (CADD) is a drug design method that uses the basic principles of computational chemistry to rationally design lead compounds with new structures by simulating the interaction between drugs and receptor biomacromolecules or by analyzing the internal relationship between the structure and activity of known drugs. The receptor refers to a biological macromolecule in the cell or on the cell membrane, which displays special functions in combination with exogenous drugs or endogenous hormones. Since the structure-activity relationship method was proposed in the 1960s, CADD technology has increasingly become an indispensable and powerful tool for modern drug research along with the rapid development of bioinformatics, chemical biology, molecular biology, and computer technology.
2 Principles of CADD
The gradual maturity of structural biology measurement technologies such as theoretical calculation technology, X-ray crystallography, and nuclear magnetic resonance, have boosted the acquirement of three-dimensional structural information of the research object. The three-dimensional structure of drugs, biomacromolecules, and drug-biomacromolecule complexes can be measured by experimental methods, obtained by theoretical calculation methods, or simulated by computer. Computer-aided drug design employs molecular simulation software to analyze the structural properties of receptor macromolecule binding sites, such as electrostatic field, hydrophobic field, hydrogen bonding site distribution, and other information. It includes three methods: drug design methods based on small molecules, drug molecule design methods based on receptor structure, and computational combination methods.
3 Commonly used computer-aided drug design methods
3.1 Direct drug design
The principle of direct drug design is based on the three-dimensional structure search of the target. There are mainly four common methods: template positioning method, atomic growth method, molecular fragmentation method, and kinetic algorithm. Once the three-dimensional structure of the receptor or the complex formed by the combination of the receptor and the ligand is known, new drugs can be designed according to the three-dimensional requirements of the receptor. Besides, if you only know the amino acid sequence of the receptor protein but not its spatial arrangement, you can simulate its hierarchical structure based on the homologous protein.
3.2 Indirect drug design
The principle of indirect drug design is based on the three-dimensional structure search of the pharmacophore model. Common methods for indirect drug design contain active analog method, pharmacophore model method, molecular shape analysis, and so on. Since the structure of most receptors has not been elucidated, the conformational study has to be carried out based on the structure of a series of ligands by the active congeners. First, search for the lower energy conformation of each compound, and then perform conformation overlap in line with certain rules to find the conformation that can be overlapped in this series of compounds.
4 Application of computer-aided drug design
4.1 Application in the discovery and confirmation of drug targets
The application of computer-aided drug design can speed up target discovery, improve accuracy, and promote the development of new drugs. It mainly includes the application of bioinformatics and reverse molecular docking technology. Bioinformatics technology refers to the collection, storage, analysis, and processing of data resources such as proteomics through computers and some practical bioinformatics software. Reverse molecular docking is a technique for docking the same active molecule to the active sites of multiple proteins to determine the potential drug targets of the molecule. This technology can efficiently achieve large-scale target determination and verification, and predict targets related to toxicity.
4.2 Application in the discovery and optimization of lead compounds
The discovery and optimization of lead compounds are key to the success of innovative drug research. For a long time, the discovery of lead compounds has relied on medicinal chemists to synthesize a large number of compounds and pharmacologists to use various models for dozens of screenings. The applications of computer-aided drug design in the discovery and optimization of lead compounds mainly include structure-based drug design, ligand-based drug design, and high-throughput virtual screening. Structure-based drug design is a technology to study the interaction between receptors and small molecules based on the structure of the drug target, design new molecules complementary to the active pocket, or find new lead compounds. Ligand-based drug design starts from the structure of existing active small molecules and predicts the activity of new compounds or guides the structural improvement of original compounds by establishing pharmacophore models or quantitative structure-activity relationships. Ligand-based drug design methods mainly include pharmacophore model construction and quantitative structure-activity relationship analysis. High-throughput virtual screening aims at the three-dimensional structure of the target or the established pharmacophore model, QSAR model, and selects qualified small molecules from the compound database for biological activity testing, which is an important means for the discovery of lead compounds and lead optimization.
5 Conclusion
As a source of analysis tools and new ideas, computer-aided drug design provides an important basis and support for drug discovery. This design method is completely simulated and calculated by software on a computer, which has become a new way of drug discovery. It completely changed the traditional drug discovery and design method that relied on a large scale of experimental screening and parallel chemical synthesis. Through drug design software, it is possible to interpret experimental results from theoretical depth, verify the reliability of experimental data, obtain microscopic data unavailable by other methods, and make the optimal decisions based on research conclusions. In short, computer-aided drug design can not only simulate the interaction between drugs and biological macromolecules, provide solutions for the structural modification of known drugs to enhance the efficacy, but also directly design new lead compounds with a broad prospect.