AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Coiled-coil domain-containing protein 34

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We utilise our cutting-edge, exclusive workflow to develop 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

Q96HJ3

UPID:

CCD34_HUMAN

Alternative names:

Renal carcinoma antigen NY-REN-41

Alternative UPACC:

Q96HJ3; B2R8G2; Q8IX69; Q9H2A6; Q9Y599

Background:

Coiled-coil domain-containing protein 34, also known as Renal carcinoma antigen NY-REN-41, plays a crucial role in spermatogenesis. It is specifically involved in anterograde intraflagellar transport, a process vital for the formation of sperm flagella. This protein's function underscores its importance in the reproductive system, particularly in the development of spermatozoa.

Therapeutic significance:

Spermatogenic failure 76, a male infertility disorder characterized by oligoasthenoteratozoospermia and abnormally shaped spermatozoa, is associated with mutations affecting this protein. Understanding the role of Coiled-coil domain-containing protein 34 could open doors to potential therapeutic strategies for treating this infertility disorder.

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