Nuclear factor erythroid 2-related factor 2 (Nrf2) is an emerging regulator of cellular antioxidants. Nrf2 controls the basal and induced expression of a series of antioxidant response element-dependent genes to modulate the physiological and pathophysiological consequences of oxidant exposure. The impact of Nrf2 on cancer is complex, and it is persistently activated in some tumors, leading to a pro-survival phenotype to promote tumor growth and resistance to oxidants and anticancer drugs. The recognition that Nrf2 could potentially do more harm than good to cancer from the observation that some tumors have persistently elevated ARE gene expression suggests that cancer cells hijack the protective ability of Nrf2 to increase resistance to oxidants and anticancer agents, leading to the mechanisms of Nrf2 persistent activation are multifaceted[1]. CD ComputaBio now offers professional Nrf2 targeting services to meet your research needs.
Figure 1. Nrf2 activation model. (Szklarz G.2013)
Our Services
- Protein-Protein Interaction Network Prediction
- Protein-protein interactions (PPIs) are critical for nearly every process in a cell, so understanding PPIs is critical to understanding cellular physiology in both normal and disease states. CD ComputaBio provides our clients with the best service for predicting protein-protein interaction networks. Our services include:
- In silico protein-protein interactions prediction service
- Prediction of protein-protein interaction sites (ISPPIsSP)
- Replica Exchange Molecular Dynamics (REMD) Services
Molecular dynamics (MD) simulations have proven to be a powerful tool for studying protein aggregation. However, it is difficult for conventional MD simulations to sample the entire conformational space of complex protein systems within an acceptable simulation time. Many enhanced sampling methods have been developed. Of these, replication-exchange molecular dynamics (REMD) methods are particularly attractive. By combining MD simulations with Monte Carlo algorithms, CD ComputaBio can provide you with replication-exchange molecular dynamics simulations. In REMD, a series of non-interactive replication systems were reconstructed covering a wide temperature range. We can run separate molecular dynamics simulations for each replica, and the configurations of each replica that are temperature-adjacent can be interchanged. REMD simulations can sample in a larger configuration space than traditional dynamics.
Figure 2. Replica Exchange Molecular Dynamics (REMD). (Mlynsky, Vojtěch, Bussi G..2017)
Our Capabilities
CD ComputaBio provides professional Nrf2 targeting services to meet customers' scientific needs. CD ComputaBio relies on world-class technical expertise, we provide customers with the highest quality one-stop Nrf2 targeting services, including the development of experimental procedures according to different experimental needs. Please feel free to contact us for more details and our scientists will tailor the most reasonable plan for your project.
Our 3D-QSAR Service Targeting Nrf2
3D-QSAR is a method that introduces the three-dimensional structure information of drug molecules for quantitative structure-activity relationship research. This method indirectly reflects the non-bonding interaction characteristics between drug molecules and macromolecules in the process of interaction. Since the 2D QSAR has a clearer physical meaning and richer information, the most widely used 3D QSAR methods are CoMFA and CoMSIA, namely the comparative molecular field method and the comparative molecular similarity method.
Figure 3. 3D-QSAR modeling. (Jinhui Wang. et al.2020)
Our comprehensive solutions include:
- Data mining approach
Molecule mining approaches is a special case of structured data mining approaches. It applies a similarity matrix based prediction or an automatic fragmentation scheme into molecular substructures.
- Matched molecular pair analysis
There is a relatively new concept of matched molecular pair analysis or prediction driven MMPA that is coupled with QSAR model to identify activity cliffs.
References
- Mlynsky, Vojtěch, Bussi G. Exploring RNA structure and dynamics through enhanced sampling simulations. Current Opinion in Structural Biology, 2017, 49:63.
- Jinhui Wang. et al. Identification, Structure–Activity Relationships of Marine-Derived Indolocarbazoles, and a Dual PKCθ/δ Inhibitor with Potent Antipancreatic Cancer Efficacy. Journal of Medicinal Chemistry, 2020, 63(21):12978-12991.
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