AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Tudor-interacting repair regulator protein

Available from Reaxense
Predicted by Alphafold

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.

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 our partner Reaxense.

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 high-tech, dedicated method is applied to construct targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

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

Q9BRJ7

UPID:

TIRR_HUMAN

Alternative names:

NUDT16-like protein 1; Protein syndesmos

Alternative UPACC:

Q9BRJ7; Q8NAI2

Background:

Tudor-interacting repair regulator protein (TIRR), also known as NUDT16-like protein 1 or Protein syndesmos, plays a pivotal role in DNA damage response. It regulates TP53BP1 by stabilizing it and controlling its chromatin recruitment. TIRR prevents TP53BP1 chromatin binding in the absence of DNA damage by interacting with TP53BP1's Tudor-like domain, thus keeping TP53BP1 in the nucleus. Upon DNA damage, TIRR's dissociation from TP53BP1, facilitated by ATM-induced TP53BP1 phosphorylation and RIF1 recruitment, allows TP53BP1 to bind to DNA double-strand breaks. Additionally, TIRR binds U8 snoRNA.

Therapeutic significance:

Understanding the role of Tudor-interacting repair regulator protein could open doors to potential therapeutic strategies.

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