Focused On-demand Library for CCR4-NOT transcription complex subunit 9

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 use our state-of-the-art dedicated workflow for designing focused 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.

Key features that set our library apart include:

The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q92600

UPID:

CNOT9_HUMAN

Alternative names:

Cell differentiation protein RQCD1 homolog

Alternative UPACC:

Q92600; B2RPI0; B5MDQ4; B7Z1E5; Q96IX4

Background:

CCR4-NOT transcription complex subunit 9, also known as Cell differentiation protein RQCD1 homolog, plays a pivotal role in mRNA deadenylation, a process crucial for mRNA degradation and regulation. It is a component of the CCR4-NOT complex, integral to mRNA degradation, miRNA-mediated repression, and transcription regulation. This protein's ability to bind oligonucleotides, albeit not poly-A, and its involvement in MYB- and JUN-dependent transcription down-regulation highlight its multifunctionality in cellular processes.

Therapeutic significance:

Understanding the role of CCR4-NOT transcription complex subunit 9 could open doors to potential therapeutic strategies. Its involvement in critical cellular processes such as mRNA degradation and transcription regulation makes it a promising target for drug discovery, aiming to modulate gene expression in various diseases.