Focused On-demand Libraries - Receptor.AI 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. Reaxense aids in their synthesis and provision.


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 top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening 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.


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
Receptor.AI
 
UPACC
Q6NZY4

UPID:
ZCHC8_HUMAN

ALTERNATIVE NAMES:
TRAMP-like complex RNA-binding factor ZCCHC8

ALTERNATIVE UPACC:
Q6NZY4; Q7L2P6; Q8N2K5; Q96SK7; Q9NSS2; Q9NSS3

BACKGROUND:
The TRAMP-like complex RNA-binding factor ZCCHC8 is integral to the NEXT complex, targeting specific RNAs for exosomal degradation. Its function is essential for the 3'-end maturation of telomerase RNA component (TERC), implicating it in telomere maintenance and cellular longevity. ZCCHC8's role in RNA surveillance and turnover highlights its significance in maintaining genomic integrity.

THERAPEUTIC SIGNIFICANCE:
ZCCHC8's association with telomere-related diseases, particularly Pulmonary fibrosis, and/or bone marrow failure, telomere-related, 5, underscores its potential as a therapeutic target. Exploring ZCCHC8's mechanisms could lead to novel interventions for managing telomere length disorders, offering hope for treatments of related pulmonary and hematological conditions.

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