Computer-aided drug design

Posted by beauty33 on August 7th, 2019

Computer aided drug design is a method of designing and optimizing lead compounds, based on computer chemistry, through computer simulation, calculation and budget of the relationship between drugs and receptor macromolecules. In fact, computer-aided drug design is to optimize and design lead compounds by simulating and calculating the interaction between receptor and ligand. Computer-aided drug design generally includes active site analysis, database search, and novel drug design.

Receptors are biological macromolecules with specific functions on or within the cell membrane of an organism. When combined with endogenous hormones, transmitters or exogenous drugs, it has certain specific functions, such as opening ion channels on the cell membrane or activating special enzymes, leading to specific physiological changes. Ligand is a kind of biological active substance which can specifically bind to receptor. Ligand and receptor binding can produce physiological activity similar to hormones or neurotransmitters, called agonists. If it prevents endogenous substances from binding to the receptor and blocks its physiological effects, it is called an antagonist. Computer-aided drug design actually simulates and computes this receptor-ligand interaction. Optimize and design lead compounds.

Classification

Computer-aided drug design can be divided into direct drug design and indirect drug design according to whether the structure of the receptor is known or not.

Computer-aided drug design began in the early 1980s. With the completion of the human genome project, the rapid development of proteomics, and the discovery of a large number of genes related to human diseases, the target molecules for drug action increased significantly. At the same time, computer aided drug design has made great progress in recent years.

Active site analysis

This method can be used to detect atoms or groups that interact well with the active sites of biological macromolecules. The probes used for analysis can be simple molecules or fragments, such as water or benzene rings. By analyzing the interaction between the probe and the active site, the possible binding sites of these molecules or fragments in the active site were finally found. The receptor binding information obtained from active site analysis is of guiding significance for the design of new drugs. Active field analysis software includes DRID, GREEN, HSITE, and other software based on monte carlo and simulated annealing technologies, such as MCSS, HINT, BUCKES, etc.

The basic principle of the grid developed by the goodford team is to divide the active sites of receptor proteins into regular grid points, place probe molecules (such as water molecules or methyl groups) on the grid points, and calculate the positions of the active sites and receptors of each probe in the interaction energy by using the molecular field method. Therefore, the distribution of active sites in the interaction between probe molecules and receptors can find the best working sites. An initial example of mesh manipulation is the use of water molecules as probe molecules to search the active site of dihydrofolate reductase (DHFR) and the water binding site of the inhibitor hydrogen bond site. The software has successfully designed drugs including the anti-type A cold virus drug neu5ac2en. The compound has a strong ability to resist cold virus, overcomes the defect of resistance to cold virus drugs, and has a good market prospect. MCSS was developed by Miranker and Karplus based on the Charmm force field. In molecular dynamics simulation, the non - bonding interaction between solvent molecules can be eliminated by chalme force field. Thus, in the molecular dynamics simulation, the solvent overlaps together in the appropriate energy region, thus improving the efficiency of finding the binding region between the solvent molecule and the receptor molecule. Small molecular fragments (such as water and benzene molecules) can be used as solvent molecules. The above dynamic methods were used to find the binding region of molecular fragments and receptors, and 100-1000 fragments were selected in the binding region of low-energy fragments for energy optimization. Random sampling or grid point method can be used in the final energy search. In the search, each copy of each fragment can be rotated strictly, and finally, the binding energy of each copy of each fragment to the receptor can be directly compared to select the best action site of the fragment. In 2001, Adlington et al. conducted a detailed analysis of the active sites of prostate-specific immunosuppressant (PSA) using MCSS, so as to optimize the structure of existing PSA inhibitors and obtain the PSA inhibitors with the highest activity at present.