Virtual Screening and Structure Generation Applied to Drug Design

The methods of computer-aided drug design can be divided into two categories according to whether or not the structures of receptors are known1, corresponding to two principal strategies: (1) searching the bio-active ligands against virtual combinatorial libraries and calculating the affinity energy between ligand and receptor by docking ; (2) QSAR and 3D-structure data-mining. 3D-QSAR method is now applied widely to drug discovery, but this method is generally limited to refine the structu…

Virtual Screening and Structure Generation Applied to Drug Design

The methods of computer-aided drug design can be divided into two categories according to whether or not the structures of receptors are known1, corresponding to two principal strategies:(1) searching the bio-active ligands against virtual combinatorial libraries and calculating the affinity energy between ligand and receptor by docking ; (2) QSAR and 3D-structure data-mining.3D-QSAR method is now applied widely to drug discovery, but this method is generally limited to refine the structures of known bio-active compounds. During the process of drug design, we have usually the prejudice that certain groups or structural fragments will play or not important roles on the activity. This will sometimes be misleading, and prevent us from obtaining expected results.The method of generating firstly diverse structures, then screening out the promising structures by means of a computational method or QSAR model, is an efficient way for drug discovery. We developed an efficient virtual and rational drag design method. It combines virtual bioactive compound generation using genetic algorithms with 3D-QSAR model and docking. Using this method can generate a lot of highly diverse molecules and find virtual active lead compounds. The method was validated by the study on a set of anti-tumor drugs, colchicine analogs2. With the constraints of pharmacophore obtained determined by DISCO, 97 virtual bioactive compounds were generated,and their anti-tumor activities were predicted by CoMFA. 8 structures with high activity were selected and screened by 3D-QSAR model. The most active generated structure was further investigated by modifying its structure in order to increase the activity (see fig.1). This drug design method could also avoid the conflict between the insufficiency of active structures and the great quantity of compounds needed for high-throughput screening. This method has been also applied to anti-HIV drug design.We have developed equally another approach of virtual screening based on molecular diversity. In the case where the large databases are available, This method can be applied to high throughput screening.