AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Phosphatidylinositol-glycan biosynthesis class F protein

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

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

Q07326

UPID:

PIGF_HUMAN

Alternative names:

GPI11 homolog

Alternative UPACC:

Q07326; Q8WW20

Background:

The Phosphatidylinositol-glycan biosynthesis class F protein, also known as GPI11 homolog, plays a crucial role in GPI-anchor biosynthesis. This process is essential for attaching various proteins to cell membranes, influencing cell surface structure and signaling. The protein's action involves the transfer of ethanolamine phosphate to the third mannose of GPI, a key step in the biosynthesis pathway.

Therapeutic significance:

Linked to the rare Onychodystrophy, osteodystrophy, impaired intellectual development, and seizures syndrome, the GPI11 homolog's dysfunction underscores its biological importance. Understanding the role of Phosphatidylinositol-glycan biosynthesis class F protein could open doors to potential therapeutic strategies for this autosomal recessive disorder.

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