AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Podocin

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.

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 utilise our cutting-edge, exclusive workflow to develop focused 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

Q9NP85

UPID:

PODO_HUMAN

Alternative names:

-

Alternative UPACC:

Q9NP85; B1AM32; B1AM33; Q8N6Q5

Background:

Podocin, encoded by the gene with accession number Q9NP85, is a critical component in the regulation of glomerular permeability. It serves as a crucial linker between the plasma membrane and the cytoskeleton within kidney cells. This protein's role is pivotal in maintaining the filtration barrier's integrity, a fundamental process for normal kidney function.

Therapeutic significance:

Podocin mutations are directly linked to Nephrotic syndrome 2, a severe renal disorder characterized by significant proteinuria, hypoalbuminemia, hyperlipidemia, and edema. This condition, resistant to steroids, often progresses to end-stage renal failure in early life. Understanding the role of Podocin could open doors to potential therapeutic strategies, offering hope for targeted treatments in renal diseases.

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