Focused On-demand Library for TRAF3-interacting protein 1

Focused On-demand Libraries - Receptor.AI 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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds 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
Receptor.AI
 
UPACC
Q8TDR0

UPID:
MIPT3_HUMAN

ALTERNATIVE NAMES:
Interleukin-13 receptor alpha 1-binding protein 1; Intraflagellar transport protein 54 homolog; Microtubule-interacting protein associated with TRAF3

ALTERNATIVE UPACC:
Q8TDR0; Q6PCT1; Q7L8N9; Q9NRD6; Q9Y4Q1

BACKGROUND:
The protein TRAF3-interacting protein 1, with aliases such as Microtubule-interacting protein associated with TRAF3, plays a critical role in cellular processes including IL13 signaling inhibition, kidney development, and ciliogenesis. It functions as a negative regulator of microtubule stability and is involved in the organization of the microtubule cytoskeleton.

THERAPEUTIC SIGNIFICANCE:
Given its association with Senior-Loken syndrome 9, a disorder affecting kidneys and eyes, the study of TRAF3-interacting protein 1 offers promising avenues for therapeutic development. Understanding the role of TRAF3-interacting protein 1 could open doors to potential therapeutic strategies.

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