Focused On-demand Library for Ribosome quality control complex subunit NEMF

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

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

 Fig. 1. The sreening 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.

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.







Alternative names:

Antigen NY-CO-1; Nuclear export mediator factor; Serologically defined colon cancer antigen 1

Alternative UPACC:

O60524; A0JLQ3; B3KSK1; B4DDL3; B4DHA9; B4E3F3; Q32Q66; Q8WW70; Q9NWG1


Ribosome Quality Control Complex Subunit NEMF, also known as Antigen NY-CO-1 and Serologically Defined Colon Cancer Antigen 1, plays a pivotal role in cellular homeostasis. It is a key component of the ribosome quality control complex (RQC), crucial for the extraction and degradation of incomplete nascent chains from stalled ribosomes, thereby preventing the accumulation of potentially toxic polypeptide chains.

Therapeutic significance:

The protein's involvement in Intellectual Developmental Disorder with Speech Delay and Axonal Peripheral Neuropathy highlights its therapeutic potential. Understanding the role of Ribosome Quality Control Complex Subunit NEMF could open doors to potential therapeutic strategies for this disorder, emphasizing the importance of targeted research in this area.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.