AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Polyunsaturated fatty acid lipoxygenase ALOX12

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.

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.

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.

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 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

P18054

UPID:

LOX12_HUMAN

Alternative names:

Arachidonate (12S)-lipoxygenase; Arachidonate (15S)-lipoxygenase; Linoleate (13S)-lipoxygenase; Lipoxin synthase 12-LO; Platelet-type lipoxygenase 12

Alternative UPACC:

P18054; O95569; Q6ISF8; Q9UQM4

Background:

Polyunsaturated fatty acid lipoxygenase ALOX12, also known as Arachidonate (12S)-lipoxygenase, plays a pivotal role in the metabolism of polyunsaturated fatty acids into bioactive lipids. These lipids, including (12S)-HPETE, lipoxin A4, and resolvin D5, are crucial in various biological processes such as platelet activation and immune response modulation. ALOX12's ability to regulate the expression of VEGF and integrin beta-1 highlights its significance in tumor progression and metastasis.

Therapeutic significance:

Given ALOX12's involvement in esophageal and colorectal cancers, targeting this protein could offer a novel approach in cancer therapy. Its role in the production of bioactive lipids and regulation of key factors in tumor progression makes it a promising target for developing inhibitors that could halt cancer growth and spread.

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