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

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.

Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.

Several key aspects differentiate our library:

Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

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.