AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for FAD-dependent oxidoreductase domain-containing protein 1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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.

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

 Fig. 1. The sreening 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.

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

Q96CU9

UPID:

FXRD1_HUMAN

Alternative names:

-

Alternative UPACC:

Q96CU9; B3KN84; B4DHU2; Q71MG0; Q9BU39; Q9UKY9

Background:

FAD-dependent oxidoreductase domain-containing protein 1 plays a crucial role in mitochondrial function, specifically in the assembly of the mitochondrial membrane respiratory chain NADH dehydrogenase (Complex I). This protein's involvement in mid-late stages of complex I assembly is pivotal for cellular energy production.

Therapeutic significance:

Given its critical role in mitochondrial complex I assembly, understanding the function of FAD-dependent oxidoreductase domain-containing protein 1 could unveil new therapeutic avenues for treating mitochondrial complex I deficiency, nuclear type 19, and related mitochondrial disorders.

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