AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Progressive ankylosis protein homolog

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 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 employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9HCJ1

UPID:

ANKH_HUMAN

Alternative names:

-

Alternative UPACC:

Q9HCJ1; B2RCA7; B3KMG4; D3DTD4; Q9NQW2

Background:

The Progressive ankylosis protein homolog, encoded by the gene with accession number Q9HCJ1, plays a pivotal role in regulating intra- and extracellular levels of inorganic pyrophosphate (PPi), potentially acting as a PPi transporter. This regulation is crucial for maintaining the balance of mineralization processes in the body.

Therapeutic significance:

Given its involvement in Chondrocalcinosis 2 and Craniometaphyseal dysplasia, autosomal dominant, understanding the role of Progressive ankylosis protein homolog could open doors to potential therapeutic strategies for these conditions. Targeting the protein's function may offer new avenues for treating joint pain, arthritis, and bone dysplasias.

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