AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Hypoxia-inducible factor 1-alpha inhibitor

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.

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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

Q9NWT6

UPID:

HIF1N_HUMAN

Alternative names:

Factor inhibiting HIF-1; Hypoxia-inducible factor asparagine hydroxylase

Alternative UPACC:

Q9NWT6; D3DR69; Q5W147; Q969Q7; Q9NPV5

Background:

The Hypoxia-inducible factor 1-alpha inhibitor, also known as Factor inhibiting HIF-1 and Hypoxia-inducible factor asparagine hydroxylase, plays a pivotal role in oxygen sensing. It hydroxylates HIF-1 alpha, preventing its interaction with transcriptional coactivators under normoxic conditions. This protein is crucial in transcriptional repression, interacting with HIF1A, VHL, and histone deacetylases. It targets specific Asn residues within ankyrin repeat domains of several proteins, influencing NOTCH1 activity and promoting vascular differentiation.

Therapeutic significance:

Understanding the role of Hypoxia-inducible factor 1-alpha inhibitor could open doors to potential therapeutic strategies.

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