Focused On-demand Library for HBS1-like protein

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 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.

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

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.

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.







Alternative names:


Alternative UPACC:

Q9Y450; B7Z365; Q4VX89; Q4VX90; Q5T7G3; Q8NDW9; Q9UPW3


The HBS1-like protein, also known as ERFS, plays a crucial role in cellular homeostasis through its involvement in the No-Go Decay (NGD) pathway. This pathway is activated when ribosomes stall at the 3' end of an mRNA, a situation that can lead to the accumulation of defective proteins. The HBS1-like protein, as part of the Pelota-HBS1L complex, recognizes these stalled ribosomes and initiates a series of events that result in the degradation of the problematic mRNA, thus preventing the synthesis of potentially harmful proteins.

Therapeutic significance:

Understanding the role of HBS1-like protein could open doors to potential therapeutic strategies. Its pivotal function in the NGD pathway highlights its importance in maintaining protein quality control within cells. Targeting the mechanisms by which this protein recognizes and responds to stalled ribosomes could lead to innovative treatments for diseases caused by protein misfolding or aggregation.

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