Focused On-demand Library for Alpha-aminoadipic semialdehyde dehydrogenase

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.


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


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


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


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
Receptor.AI
 
UPACC
P49419

UPID:
AL7A1_HUMAN

ALTERNATIVE NAMES:
Aldehyde dehydrogenase family 7 member A1; Antiquitin-1; Betaine aldehyde dehydrogenase; Delta1-piperideine-6-carboxylate dehydrogenase

ALTERNATIVE UPACC:
P49419; B2R669; B4DIC7; B4DMA0; E7EPT3; O14619; Q6IPU8; Q9BUL4

BACKGROUND:
The enzyme Alpha-aminoadipic semialdehyde dehydrogenase, known under several names including Antiquitin-1 and Betaine aldehyde dehydrogenase, is pivotal in protecting cells from oxidative damage. It achieves this by metabolizing harmful aldehydes into less reactive compounds and is crucial in the metabolism of lysine, an essential amino acid.

THERAPEUTIC SIGNIFICANCE:
Its dysfunction is associated with Pyridoxine-dependent epilepsy, a disease manifesting early in life with seizures that are resistant to common anticonvulsants but respond to pyridoxine hydrochloride. The exploration of Alpha-aminoadipic semialdehyde dehydrogenase's function offers promising avenues for the development of targeted treatments for epilepsy and oxidative stress-related conditions.

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