AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Very-long-chain 3-oxoacyl-CoA reductase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.

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 high-tech, dedicated method is applied to construct targeted 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.

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

Reaxense

upacc

Q53GQ0

UPID:

DHB12_HUMAN

Alternative names:

17-beta-hydroxysteroid dehydrogenase 12; 3-ketoacyl-CoA reductase; Estradiol 17-beta-dehydrogenase 12; Short chain dehydrogenase/reductase family 12C member 1

Alternative UPACC:

Q53GQ0; A8K9B0; D3DR23; Q96EA9; Q96JU2; Q9Y6G8

Background:

Very-long-chain 3-oxoacyl-CoA reductase, known alternatively as 17-beta-hydroxysteroid dehydrogenase 12, plays a crucial role in the elongation of long-chain fatty acids. This enzyme operates within the endoplasmic reticulum, catalyzing the reduction of 3-ketoacyl-CoA to 3-hydroxyacyl-CoA, a key step in the production of very long-chain fatty acids (VLCFAs). VLCFAs serve as precursors for membrane lipids and lipid mediators, essential for cellular function and signaling.

Therapeutic significance:

Understanding the role of Very-long-chain 3-oxoacyl-CoA reductase could open doors to potential therapeutic strategies.

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