Ligand-Based Virtual Drug Screening Services
Creative Biolabs offers ligand-based virtual drug screening service for targets without a solved 3D structure. We can build a 3D model of the target by exploiting the collective information contained in sets of ligands. Multiple similar ligand atoms in a spatially consistent location result in a strong pharmacophore signal in this location.
For lead discovery and optimization, ligand-based virtual drug screening methods rely on the information of known active ligands rather than the structure of a target protein. When there isn't a 3D structure of the target protein, ligand-based approaches are the sole option. In practice, even if you don't know the protein structure of the target of interest, you can usually tell that a group of ligands is active against it. As a result, ligand-based virtual techniques can be applied, such as identifying new ligands by comparing candidate ligands to known active molecules. The known active chemicals are collected using a ligand-based technique to select a query for virtual screening or alignment in ligand-based design.
Fig.1. Examples of pharmacophores used in ligand-based virtual screening. (Liao, 2011)
Ligand-based pharmacophore generation from a set of ligands entails two steps: 1) sampling the conformational space for each ligand to account for the ligand's conformational flexibility; 2) aligning the multiple ligands to determine the essential common chemical features needed to build a pharmacophore model. Pharmacophore models are divided into two categories. The first is 3D quantitative structure-activity relationship (QSAR)-like models, which may be created using a training set of ligands with biological activities spanning at least three orders of magnitude. The potencies of new compounds can be quantitatively predicted using such models by assessing how well each compound maps onto the model. The second type can be created using just active ligands as a training set. The potencies of new compounds can be qualitatively evaluated by comparing them to the model.
Case of Ligand-based Virtual Drug Screening
One known compound, Tyrosol-1-O-β-xylopyranosyl-(1→6)-O-β-glucopyranoside) (I), and one new compound, 5-O-(6-O-α-rhamnopyronosyl-β-glucopyronosyl) mevalonic acid (II), were obtained as a consequence of phytochemical research. The possible molecular target of compounds I and II were discovered using the ligand-based virtual screening approach. Protein-tyrosine kinase Syk was identified as the molecular target for compound I, and aldo-keto reductase family1 was identified as the molecular target for compound II. The binding affinity of the compounds with the targets acquired from ligand-based virtual screening was assessed using molecular docking.
Fig.2. 2D ligand interaction in the binding site: A) Compound I in complex with tyrosine protein kinase SYK. B) Compound II in complex with AKR1C3. (Bayazeid, 2019)
Creative Biolabs is committed to providing high-quality ligand-based virtual screening services to help global researchers identify promising candidates. The virtual screening protocol can be customizable according to the specific requirements of the customers. Please feel free to contact us for more information.
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References
- Liao, C., et al. Software and resources for computational medicinal chemistry. Future medicinal chemistry. 2011; 3(8): 1057-1085.
- Bayazeid, O., et al. Ligand-based virtual screening and molecular docking of two cytotoxic compounds isolated from Papaver lacerum. Phytochemistry Letters. 2019; 30: 26-30.
