Focused On-demand Library for TRAF-interacting protein with FHA domain-containing protein A

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

Our top-notch dedicated system is used to design specialised libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Key features that set our library apart include:

The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q96CG3

UPID:

TIFA_HUMAN

Alternative names:

Putative MAPK-activating protein PM14; Putative NF-kappa-B-activating protein 20; TRAF2-binding protein

Alternative UPACC:

Q96CG3

Background:

TRAF-interacting protein with FHA domain-containing protein A, also known as Putative MAPK-activating protein PM14 and Putative NF-kappa-B-activating protein 20, plays a pivotal role in the activation of pro-inflammatory NF-kappa-B signaling. This activation occurs upon the detection of bacterial pathogen-associated molecular pattern metabolites (PAMPs), leading to an innate immune response. The protein promotes the oligomerization and polyubiquitination of TRAF6, activating TAK1 and IKK through a proteasome-independent mechanism.

Therapeutic significance:

Understanding the role of TRAF-interacting protein with FHA domain-containing protein A could open doors to potential therapeutic strategies.