AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Transcription intermediary factor 1-alpha

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.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

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

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

O15164

UPID:

TIF1A_HUMAN

Alternative names:

E3 ubiquitin-protein ligase TRIM24; RING finger protein 82; RING-type E3 ubiquitin transferase TIF1-alpha; Tripartite motif-containing protein 24

Alternative UPACC:

O15164; A4D1R7; A4D1R8; O95854

Background:

Transcription intermediary factor 1-alpha (TIF1-alpha), also known as E3 ubiquitin-protein ligase TRIM24, plays a pivotal role in cellular processes by interacting with nuclear receptors and coactivators to modulate gene transcription. It exhibits a unique affinity for chromatin modifications and possesses E3 ligase activity, crucial for DNA damage response and cell cycle regulation. Its interaction with TP53 and involvement in innate immunity highlight its multifunctionality.

Therapeutic significance:

Understanding the role of Transcription intermediary factor 1-alpha could open doors to potential therapeutic strategies. Its central role in regulating cell proliferation, apoptosis, and response to DNA damage, alongside its effects on p53/TP53 levels, positions it as a key target for cancer therapy and immune response modulation.

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