AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Very-long-chain enoyl-CoA reductase

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.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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 employ our advanced, specialised process to create 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.

partner

Reaxense

upacc

Q9NZ01

UPID:

TECR_HUMAN

Alternative names:

Synaptic glycoprotein SC2; Trans-2,3-enoyl-CoA reductase

Alternative UPACC:

Q9NZ01; B2RD55; O75350; Q6IBB2; Q9BWK3; Q9Y6P0

Background:

The Very-long-chain enoyl-CoA reductase, also known as Synaptic glycoprotein SC2 and Trans-2,3-enoyl-CoA reductase, plays a crucial role in lipid metabolism. It is involved in the production and degradation of very long-chain fatty acids (VLCFAs), essential for sphingolipid synthesis and the sphingosine 1-phosphate metabolic pathway. This enzyme facilitates the elongation of long- and very long-chain fatty acids by adding 2 carbons per cycle, a process vital for the generation of membrane lipids and lipid mediators.

Therapeutic significance:

Given its pivotal role in lipid metabolism and association with Intellectual developmental disorder, autosomal recessive 14, targeting Very-long-chain enoyl-CoA reductase could offer novel therapeutic avenues. Understanding the enzyme's function and its impact on disease mechanisms opens doors to potential therapeutic strategies.

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