Focused On-demand Library for T-complex protein 1 subunit eta

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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.

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

Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

Several key aspects differentiate our library:

Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q99832

UPID:

TCPH_HUMAN

Alternative names:

CCT-eta; HIV-1 Nef-interacting protein

Alternative UPACC:

Q99832; A8K7E6; A8MWI8; B7WNW9; B7Z4T9; B7Z4Z7; O14871; Q6FI26

Background:

T-complex protein 1 subunit eta, also known as CCT-eta and HIV-1 Nef-interacting protein, is a crucial component of the chaperonin-containing T-complex (TRiC). This molecular chaperone complex is instrumental in assisting the folding of proteins upon ATP hydrolysis. Notably, the TRiC complex is involved in the folding of WRAP53/TCAB1, which is essential for telomere maintenance, and plays a significant role in the folding of actin and tubulin.

Therapeutic significance:

Understanding the role of T-complex protein 1 subunit eta could open doors to potential therapeutic strategies. Its involvement in protein folding and telomere maintenance highlights its importance in cellular function and integrity, suggesting that targeting this protein could lead to novel treatments for diseases where protein misfolding or telomere dysfunction is a factor.