Focused On-demand Libraries - Receptor.AI 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.


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


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide 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
Q8NA56

UPID:
TTC29_HUMAN

ALTERNATIVE NAMES:
Protein TBPP2A; Testis development protein NYD-SP14

ALTERNATIVE UPACC:
Q8NA56; A4GU95; Q9BXB6

BACKGROUND:
The protein known as Tetratricopeptide repeat protein 29, with alternative names Protein TBPP2A and Testis development protein NYD-SP14, is implicated in the regulation of flagella assembly and beating. This regulation is crucial for ensuring proper sperm motility, highlighting the protein's significance in reproductive health.

THERAPEUTIC SIGNIFICANCE:
Tetratricopeptide repeat protein 29's involvement in Spermatogenic failure 42, characterized by impaired sperm motility, underscores its therapeutic potential. Targeting this protein could lead to innovative treatments for male infertility, emphasizing the importance of further research into its functions and mechanisms.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.