Multiple-target Virtual Screening Service
In the field of drug development, single-target drugs often fall short in treating complex diseases. Multi-target drugs, which can modulate multiple relevant targets simultaneously, offer new solutions for the treatment of complex diseases. Leveraging its powerful computational platform and professional team, CD ComputaBio provides you with efficient multi-target virtual screening services.
Introduction to Multiple-target Virtual Screening
Multi-target virtual screening utilizes computer algorithms and models, including molecular docking, pharmacophore modeling, and network pharmacology, to predict and analyze potential drugs that can simultaneously act on multiple targets from large compound libraries. This method can rapidly assess and predict the interactions of compounds with multiple targets based on information such as target structure, properties, and compound characteristics. By combining network pharmacology and other methods to analyze the biological networks of drug interactions with multiple targets, it efficiently screens out promising multi-target drugs.
Fig.1 The principal triple-targeted fitness score analysis of compounds selected from the ZINC database. (Dai Y H, et al., 2021)
Drug Development for Approved Multi-target Drugs
Table. 1 Reported multi-target drugs, targeted diseases and multi-target mode of action. (Doostmohammadi A, et al., 2024)
| Drug |
Targeted Disease |
Multi-target Mode of Action |
| Dasatinib |
Myeloid leukemia, castration resistant prostate cancer, Ovarian cancer |
Inhibiting tyrosine kinases that regulate proliferation at different upstream points and crosstalk to each other that may act as back-up alternative for each other. |
| Lapatinib |
Breast cancer |
Inhibiting tyrosine kinase receptor ERBB family members that regulate proliferation and survival at different upstream points, and act as back-up alternative for each other. |
| Sorafenib |
Renal cell carcinoma, hepatocellular carcinoma |
Inhibiting kinases that regulate angiogenesis (VEGFR2) and proliferation (BRAF), and Src mediated alternative signalling (BRAF). |
| Sunitinib |
Gastrointestinal stromal tumor, renal cell carcinoma |
Inhibiting tyrosine kinase receptors that regulate angiogenesis (VEGFR2), proliferation (FLT3), and kinase level (KIT). |
Our Services
CD ComputaBio is committed to providing efficient multi-target virtual screening services. Our advanced computational tools and expertise in computational biology enable us to identify potential drug candidates that can interact with multiple targets, thereby increasing the likelihood of discovering effective therapies.
By Molecular Types
By Target Types
- Multi-target G Protein-Coupled Receptor (GPCR) Ligands
- Multi-target Kinase Inhibitors
Workflow of Multiple-target Virtual Screening
Obtain the three-dimensional structure of the target protein, prioritizing the use of high-resolution experimental data. If necessary, predict the target structure using methods such as homology modeling to ensure its accuracy and reliability.
Compound Library Preparation
Perform data cleaning, format conversion, and conformer generation on the compound library to ensure that the compounds meet the standards for virtual screening, thereby improving screening efficiency and accuracy.
Select an appropriate multi-target screening strategy based on the project requirements, using a combination of ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS), or individually applying either method.
Conduct detailed analysis of the screening results, including compounds' binding modes and scoring. Provide a comprehensive virtual screening report covering the screening methods, result analysis, and information on hit compounds.
Methods for Multiple-target Virtual Screening
Structure-based Virtual Screening (SBVS)
The method relies on the known information of the target binding site, performing receptor-based pharmacophore screening and molecular docking. In the docking process, compounds or fragments are docked into the binding site, followed by scoring and ranking. Post-processing operations, such as rescoring with different scoring functions, can also be carried out.
Network-based Approaches
Network-based approaches use algorithms to predict drug-target interactions (DTIs). They also utilize multi-omics data to analyze the target profiles of drugs, integrating multi-omics methods and systems biology to explore the basis of disease by studying protein networks and the effects of drugs on these networks.
Combination Methods
LBVS and SBVS can be combined using sequential, parallel, or hybrid methods. In sequential methods, ligands are often pre-filtered using LBVS, and SBVS is performed at the end. Parallel methods use both LBVS and SBVS independently, and the top-ranked compounds are selected for biological testing. Hybrid methods integrate LBVS and SBVS into a standalone approach.
Ready to accelerate your multi-target drug discovery project? Contact us today to learn more about our multi-target virtual screening service. Our dedicated team will provide you with detailed project consultations and technical support to ensure your success.
References:
- Doostmohammadi, A.; et al. Potentials and future perspectives of multi-target drugs in cancer treatment: the next generation anti-cancer agents[J]. Cell Communication and Signaling. 2024, 22(1): 228.
- Dai, Y H.; et al. Drug screening of potential multiple target inhibitors for estrogen receptor-α-positive breast cancer[J]. in vivo. 2021, 35(2): 761-777.
* For Research Use Only.
Related Services
