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Drug discovery refers to the finding of specific small molecules that interact with larger molecules. The discovery of biologically active molecules is a complex and time-consuming process. The main technology for identifying new lead compounds in drug discovery is high-throughput screening. In recent years, another effective strategy-virtual screening (VS) has gradually emerged. Constant efforts are devoted to finding new tools to optimize the process. After years of accumulation, Creative Biolabs has become an expert in the field of virtual drug screening and we can provide high-quality VS services for your projects.
VS can complement the targets of known structures by computationally screening compounds in large chemical libraries and the VS method has expanded the possibilities to molecules. In the past decade, numerous different VS methods have emerged as promising ways to find new active compounds for many targets.
Fig.1 Virtual screening for new ligands. (Shoichet, 2014)
SBVS is based on determining potential ligand binding sites on target molecules. Identifying the structure of the target protein through a variety of methods such as NMR, homology modeling or X-ray crystallography is a key step in SBVS.
Molecular docking occupies an important position in the field of drug screening and design. This technique is widely used to predict the interaction of a protein with other molecules to assess the binding between two molecules. Molecular docking mainly depends on the spatial shape matching and energy matching of the ligand and the receptor.
Pharmacophore describes the molecular characteristics of biomolecules necessary to recognize ligands. Generally speaking, when a drug molecule interacts with a target molecule, it produces a specific active conformation. Different chemical groups in the drug molecule have different effects on the activity. The changes of some groups have a great influence on the interaction between the drug and the target, while others have little effect. In addition, it has been found that molecules with the same activity tend to have some of the same characteristics. In recent years, with the development of compound databases and computer technology, it has gradually become a trend for the pharmacophore model to perform VS on the database.
QSAR is closely related to the quantitative study of the interaction between small organic molecules and large biological molecules. When the receptor structure is unknown, the QSAR method is the most rapid and effective drug design method. Although with the accurate determination of the 3D structure of many biological macromolecules, structure-based drug design has gradually become the mainstream of drug design, the small computational load and good predictive ability of QSAR still play an important role in drug research.
In the LBVS process, the most effective biologically active lead molecule is detected using structure or pharmacodynamic similarity search. In addition, the cooperative use of LBVS and SBVS can increase the probability of finding a new target. The integration of the two strategies has shown great potential in identifying the first selective GPR30 agonist.
Machine learning technology is playing an increasingly important role in the field of VS. A large number of machine learning algorithms including recursive partitions, neural networks, and support vector machines have been successfully applied to VS strategies. These models can rank compounds based on their probability of being active, which helps reduce the number of redundant compounds synthesized. In this method, experimental data is very helpful for designing new compound models.
The combinatorial library can be independent of the target, and can also be designed for a specific pharmacophore. However, in many cases, the number of available compounds is too large to be physically synthesized. A direct and effective solution to this problem is to design a virtual combinatorial library and apply appropriate techniques to screen smaller sets of compounds in the library for physical synthesis. Therefore, the virtual combinatorial library has received more and more attention in the process of searching for new drugs.
In recent years, as VS has gradually become an important and substantial technology in the pharmaceutical industry, the method has been developed rapidly. Currently, VS plays an indispensable role in the drug discovery process. Creative Biolabs has been proficient in various VS technologies through unremitting efforts and will provide customers all over the world with high-quality, short-term, low-price drug VS services. Please contact us for more details.
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