Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
O60218

UPID:
AK1BA_HUMAN

ALTERNATIVE NAMES:
ARL-1; Aldose reductase-like; Aldose reductase-related protein; Small intestine reductase

ALTERNATIVE UPACC:
O60218; A4D1P1; O75890; Q6FHF3; Q8IWZ1

BACKGROUND:
The enzyme Aldo-keto reductase family 1 member B10 (AKR1B10) is a key player in the metabolic process, efficiently converting carbonyl groups into alcohols with the aid of NADPH. It showcases strong activity towards various forms of retinal and is instrumental in neutralizing harmful unsaturated carbonyls from diet and metabolism, such as crotonaldehyde and 4-hydroxynonenal. Despite its broad activity spectrum, AKR1B10 does not engage in glucose reduction. Its alternative names include ARL-1 and Aldose reductase-like, highlighting its diverse functionality.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Aldo-keto reductase family 1 member B10 could open doors to potential therapeutic strategies.

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