Natural Product Database Virtual Screening
Virtual Screening (VS), also known as computer-based screening, uses computer-based molecular docking software to simulate the interaction between a target and a natural drug candidate and calculate the affinity between the two to reduce the number of compounds actually screened while increasing the efficiency of lead compound discovery prior to conducting a bioactivity screen. BOC Sciences uses fast, accurate, and industry-leading software tools and calculations, and an experienced technical team to provide cost-effective services tailored to the needs of our clients, providing quality natural drug discovery services.
Background
Molecular docking is one of the most widely used and successful structure-based CADD computational methods, based on the simulation of the interaction of ≥2 molecules through geometric and energy matching. The advantages of molecular docking are the availability of software and the maturity of the algorithm; the disadvantages are the need for a well-defined receptor structure, the relatively large computational effort and the long screening time. Virtual screening for large compound databases generally uses rigid molecular docking methods, which can greatly save computational time.
Pharmacophore building is essentially a modeling process based on the experience of pharmacologists, i.e., the induction and extraction of specific spatial structural features shared by compounds with the same activity. Virtual screening using pharmacophores is fast and accurate, and is therefore often used in conjunction with other methods to pre-filter large databases.
Molecular similarity refers to the fact that structurally similar compounds have similar physical and chemical properties and biological activities. Molecular similarity methods are divided into local methods, which focus on comparing specific functional groups or important atomic arrangements, and global methods, which compare all structural features of a molecule. This method is usually used for activity prediction of small molecules with known structures.
The use of machine learning methods in virtual screening can lead to a more reasonable screening model than linear regression from known data, for purposes such as predicting unknown data properties. The advantage of using machine learning for virtual screening is that the model can be continuously optimized through learning, resulting in a high level of accuracy.
Our Services
Virtual Screening Process
- From a large number of natural product molecules, compounds with reasonable binding patterns and high prediction scores are selected for subsequent bioactivity testing.
- Ligand-based virtual screening generally involves using a natural product with known activity and searching the compound database for chemical molecular structures that can match it based on its shape similarity or pharmacophore model. Finally, these selected compounds are subjected to experimental screening studies.
Service contents
BOC Sciences offers a complete set of virtual screening services to clients with natural product virtual screening needs. All you need to do is provide biological information about your target, and we will screen the best active natural product for you, laying the foundation for further bioactivity evaluation.
Applications of Natural Products Virtual Screening
- Anti-tumor drugs
- Antiviral drugs
- Cardiovascular disease therapeutics
- Diabetes therapeutics
- Anti-plasmodium drugs
- Prevention of drug interactions and side effects in combination
If you have a requirement about our services, please contact us by phone or email, our colleagues will reply to you within three working days.
Related Links
For Research Use Only.
