Focused On-demand Library for CCR4-NOT transcription complex subunit 8

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.

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 for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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.







Alternative names:

CAF1-like protein; CAF2; CCR4-associated factor 8; Caf1b

Alternative UPACC:

Q9UFF9; B0AZS3; B2RAR8; B7Z8R1; D3DQI8; O95709; Q7Z521; Q9H6Y1


CCR4-NOT transcription complex subunit 8, known as CAF1-like protein, CAF2, CCR4-associated factor 8, or Caf1b, plays a crucial role in mRNA degradation, miRNA-mediated repression, and translational repression during initiation. It exhibits 3'-5' poly(A) exoribonuclease activity and works in tandem with CNOT7. As a part of the CCR4-NOT complex, it influences various cellular processes and mRNA expression, associating with BTG family members like TOB1 and BTG2 to exert anti-proliferative effects.

Therapeutic significance:

Understanding the role of CCR4-NOT transcription complex subunit 8 could open doors to potential therapeutic strategies.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.