AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for TNFAIP3-interacting protein 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our high-tech, dedicated method is applied to construct targeted libraries for protein-protein interfaces.

 Fig. 1. The sreening workflow of Receptor.AI

It includes extensive molecular simulations of the target alone and in complex with its most relevant partner proteins, followed by ensemble virtual screening that accounts for conformational mobility in free and bound forms. The tentative binding pockets are considered on the protein-protein interface itself and in remote allosteric locations in order to cover the whole spectrum of possible mechanisms of action.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q8NFZ5

UPID:

TNIP2_HUMAN

Alternative names:

A20-binding inhibitor of NF-kappa-B activation 2; Fetal liver LKB1-interacting protein

Alternative UPACC:

Q8NFZ5; B1AKS4; B3KTY8; D3DVQ9; Q7L5L2; Q9BQR6; Q9H682

Background:

TNFAIP3-interacting protein 2, also known as A20-binding inhibitor of NF-kappa-B activation 2 and Fetal liver LKB1-interacting protein, plays a crucial role in inhibiting NF-kappa-B activation. It blocks the interaction between RIPK1 and NEMO/IKBKG, forming a ternary complex with NFKB1 and MAP3K8. This protein is pivotal in the TLR4 signaling pathway, regulating MAP3K8 activation, and is involved in the MEK/ERK signaling pathway during the innate immune response. Additionally, it is essential for the stability of MAP3K8 and regulates apoptosis in endothelial cells.

Therapeutic significance:

Understanding the role of TNFAIP3-interacting protein 2 could open doors to potential therapeutic strategies.

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