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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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 top-notch dedicated system is used to design specialised 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.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q96HJ3

UPID:
CCD34_HUMAN

ALTERNATIVE NAMES:
Renal carcinoma antigen NY-REN-41

ALTERNATIVE UPACC:
Q96HJ3; B2R8G2; Q8IX69; Q9H2A6; Q9Y599

BACKGROUND:
The Coiled-coil domain-containing protein 34, alternatively known as Renal carcinoma antigen NY-REN-41, is integral to the process of spermatogenesis. Its probable role in anterograde intraflagellar transport is essential for sperm flagella formation, highlighting its significance in reproductive biology.

THERAPEUTIC SIGNIFICANCE:
Linked to Spermatogenic failure 76, a disorder leading to male infertility due to defects in sperm morphology and motility, this protein's dysfunction underscores its potential as a target for therapeutic intervention. Exploring the functions of Coiled-coil domain-containing protein 34 offers promising avenues for developing treatments for infertility issues.

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.