Tumor necrosis factor alpha (TNF-α) is an adipokine and cytokine. TNF is a member of the TNF superfamily, which consists of various transmembrane proteins with homologous TNF domains. TNF-α is a cytokine with pleiotropic effects on various cell types. It has been identified as a master regulator of inflammatory responses and is known to be involved in the pathogenesis of several inflammatory and autoimmune diseases. Structurally, TNF-α is a homotrimeric protein consisting of 157 amino acids, mainly produced by activated macrophages, T lymphocytes, and natural killer cells. They are functionally known to trigger a diverse array of inflammatory molecules, including other cytokines and chemokines. Inhibition of TNF-α has been shown to be an effective treatment for patients with rheumatoid arthritis and other forms of inflammatory disease.
Our Services
- Target Analysis
CD ComputaBio scientists are able to apply a range of computational techniques to help you gain insight into your target and complement any biological validation. The target validation process involves the application of a range of techniques designed to demonstrate that a drug's effect on the target can provide an acceptable window of safety therapeutic benefit.
- Homology modeling of targets lacking specific structural information.
- Water assessment to understand the role of water in molecular interactions and its effect on binding affinity.
- Drug Discovery
The innovation is driven by virtual screening and fragment-based discovery, indexing more than 5 million test compound information to screen the possible hits that would be a good fit for the chosen target.
- Virtual screening
We use Schrödinger, MOE, Discovery Studio, and other software for virtual screening services.
- 3D pharmacophore screening
- Shape and feature constraints
- Small molecule docking
- 2D and 3D fingerprint screening
- Scaffold and fragment replacement
- Conformation databases
- Reaction-based library design
- Fragment-based discovery
Fragment-based drug design uses a structure-based approach to rapidly design and screen large virtual compound libraries so that a larger chemical space can be explored. Our team uses pharmacophore models and 2D/3D descriptors to guide the computational FBDD process.
- Scaffold hopping
- Fragment linking and growing
- Medicinal chemistry transformations
- Combinatorial library enumeration
- Multi-fragment search
- Ligand hybridization
- Custom fragment libraries
- Drug Repurposing
Our approach to drug repositioning services can give your new or existing molecules a second chance with new target proteins. This approach can accelerate the introduction of drug molecules to the market and the prediction of secondary effects. The program brings new drugs to market quickly and at a lower cost.
- Rule-based model and structure-based screening
- Drug-drug target-disease mapping
Our Capabilities
At CD ComputaBio, our computational drug design and discovery services consist of the following key platforms
- Hit discovery: this innovation is powered by virtual high-throughput screening that cross-reference more than 5 million test compound information to screen the possible chemical space that is a good fit for a selected target.
- Lead optimization: we filter out off-target effects. Pharmacophore mapping can be used for drug design; two approaches are used: structure-based and ligand-based
- Protein modeling and simulation: our protein modeling service integrates the bioinformatics literature, tools, and software to predict the 3D structure of proteins. It is validated in combination with molecular dynamics.
Our Strategies for Virtual Screening
CD ComputaBio's virtual screening includes initial screening using multiple methods, such as 2D, 3D, structure-based and ligand-based methods, followed by analysis of hits from each screen, integration and application of data fusion techniques to ensure and enhance hit-enrichment.
* For Research Use Only.
