AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for T-box transcription factor TBX21

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 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.

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.

 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.

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

Q9UL17

UPID:

TBX21_HUMAN

Alternative names:

T-cell-specific T-box transcription factor T-bet; Transcription factor TBLYM

Alternative UPACC:

Q9UL17

Background:

T-box transcription factor TBX21, also known as T-bet, plays a pivotal role in immune response regulation. It orchestrates Th1 lineage development from naive Th precursor cells by activating Th1 genetic programs and repressing Th2 and Th17 programs. TBX21's involvement in activating genes crucial for Th1 cell function, such as IFN-gamma and CXCR3, and its role in chromatin remodeling highlight its significance in immune system functionality.

Therapeutic significance:

TBX21's association with diseases like Asthma, with nasal polyps and aspirin intolerance, and Immunodeficiency 88, underscores its therapeutic potential. Understanding TBX21's role could pave the way for innovative treatments targeting these immune-related conditions.

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