AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Lecithin retinol acyltransferase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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

O95237

UPID:

LRAT_HUMAN

Alternative names:

Phosphatidylcholine--retinol O-acyltransferase

Alternative UPACC:

O95237; A8K983; Q8N716

Background:

Lecithin retinol acyltransferase (LRAT), also known as Phosphatidylcholine--retinol O-acyltransferase, plays a pivotal role in vision by transferring the acyl group from phosphatidylcholine to all-trans retinol, forming all-trans retinyl esters. These esters serve as storage forms of vitamin A, essential for the survival of cone photoreceptors and proper rod photoreceptor cell morphology.

Therapeutic significance:

LRAT's critical function in vision, particularly in the synthesis of 11-cis-retinaldehyde, a key component of rhodopsin and cone photopigments, links it to Leber congenital amaurosis 14, a severe dystrophy of the retina. Understanding the role of LRAT could open doors to potential therapeutic strategies for this and related visual impairments.

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