Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 high-tech, dedicated method is applied to construct targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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
O43488

UPID:
ARK72_HUMAN

ALTERNATIVE NAMES:
AFB1 aldehyde reductase 1; Aldoketoreductase 7; Succinic semialdehyde reductase

ALTERNATIVE UPACC:
O43488; O75749; Q5TG63

BACKGROUND:
The enzyme Aflatoxin B1 aldehyde reductase member 2, with alternative names such as AFB1 aldehyde reductase 1, Aldoketoreductase 7, and Succinic semialdehyde reductase, is crucial for the detoxification of various aldehydes. It utilizes NADPH to reduce harmful substances like aflatoxin B1, a known carcinogen, thereby potentially protecting the liver from its toxic effects. Its ability to process a wide range of substrates highlights its significance in metabolic pathways.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Aflatoxin B1 aldehyde reductase member 2 unveils new avenues for developing therapeutic interventions.

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.