Focused On-demand Library for Tudor domain-containing protein 7

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated 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.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive 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.







Alternative names:

PCTAIRE2-binding protein; Tudor repeat associator with PCTAIRE-2

Alternative UPACC:

Q8NHU6; A6NCI6; B2RBX3; B4DG99; B4DXF7; E7EQD4; Q5VV27; Q96JT1; Q9UFF0; Q9Y2M3


Tudor domain-containing protein 7, also known as PCTAIRE2-binding protein or Tudor repeat associator with PCTAIRE-2, plays a crucial role in post-transcriptional regulation of gene expression. It is involved in the formation of specific cytoplasmic RNA granules, binding to mRNAs to regulate their translation. This protein is essential for maintaining lens transparency during development by controlling the translation of key genes such as CRYBB3 and HSPB1.

Therapeutic significance:

Tudor domain-containing protein 7 is implicated in Cataract 36, a condition characterized by lens opacification leading to visual impairment or blindness. Understanding the role of Tudor domain-containing protein 7 could open doors to potential therapeutic strategies for treating or managing this eye condition.

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