AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Peroxisomal bifunctional enzyme

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 pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

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

Q08426

UPID:

ECHP_HUMAN

Alternative names:

L-bifunctional protein; Multifunctional enzyme 1

Alternative UPACC:

Q08426; A8K6Y3; B4DWG3; D3DNU0; Q58EZ5

Background:

The Peroxisomal bifunctional enzyme, also known as L-bifunctional protein or Multifunctional enzyme 1, plays a crucial role in the metabolism of long-chain fatty acids. It exhibits peroxisomal trifunctional enzyme activities, including 2-enoyl-CoA hydratase, 3-hydroxyacyl-CoA dehydrogenase, and delta 3, delta 2-enoyl-CoA isomerase. This enzyme is pivotal in the beta-oxidation pathway, facilitating the breakdown and subsequent energy release from fatty acids.

Therapeutic significance:

Linked to Fanconi renotubular syndrome 3, a disorder characterized by impaired kidney tubule function, the Peroxisomal bifunctional enzyme's genetic variants suggest a direct impact on renal health. Understanding its role could open doors to potential therapeutic strategies for managing kidney-related disorders and metabolic diseases.

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