The goal of any drug research and development work is to develop a chemical substance that combines with the target macromolecule known to play a key role in the disease state. Virtual high throughput screening (vHTS) aims to predict which compounds have the highest affinity for the target. As a leading service provider of drug development, Creative Biolabs provides computer-based vHTS services to rapidly generate a large number of virtual compounds and accelerate the drug development process.
High throughput screening (HTS) is often used in the early stages of the drug design process to test the potential activity of large collections of compounds against selected targets. With the continuous development of technology, various statistical, informatics and filtering methods have been introduced to promote the integration of experiments and screening, and maximize its output in drug discovery. Unfortunately, HTS is time-consuming and expensive. Therefore, with the exponential growth of the number of new drug targets, vHTS is increasingly used for large-scale in vitro screening analysis to help accelerate drug discovery. The purpose of vHTS is to use computational tools to prioritize those databases that are most likely to have some affinity with the target from the entire database of existing compounds (or compounds that can be manufactured).
Fig.1 Workflow of vHTS. (Subramaniam, 2008)
The success of vHTS requires the careful implementation of every stage from target preparation to hit recognition and lead optimization. vHTS technology is applied to electronic docking and ratio equivalence of large-scale virtual molecular databases to enrich bioactive compounds and obtain lead structure. At present, there are basically two approaches: ligand- and structure-based vHTS.
When the target structure is unknown, the pharmacophore model is constructed according to the known activity of the compound. Such a model can be used as a template to select the most promising candidates from the library, which includes the location of key features such as hydrogen bonds and hydrophobic groups. This strategy can also be used as a filter before the application of structure-based vHTS, so only 1-10% of the initial database needs to be docked finally.
Structure-based vHTS includes the use of molecular docking programs to determine binding patterns on protein targets across the entire database of existing or virtual compounds. The bound conformations are used to approximate the binding free energy or related affinity of the compound. The most promising compounds are then retained for further experimental testing. The most widely used docking programs of vHTS are DOCK, FlexX, Glide, GOLD, and AutoDock.
Fig.2 vHTS to identify novel activin antagonists. (Zhu, 2015)
vHTS has been successfully applied to the screening of a lot of compounds, which provides a possible and effective compound for the treatment of many diseases. For example, the discovery of activin antagonists of transforming growth factor β (TGF β) superfamily. A small ligand-binding groove was found at the interface between the two activin βA subunits, which was used for a vHTS of ZINC database to identify hits. Combined with experiments, our vHTS method found a kind of small molecule activin antagonists combined with activin-receptor-like kinase 4 (ALK4), which opened a new way to inhibit the activity of TGF β receptor superfamily members. In addition, the lead compounds can be used as a starting point of lead optimization to achieve the goal of possible effective compounds in activin-mediated diseases.
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References
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