AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Cystic fibrosis transmembrane conductance regulator

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We employ our advanced, specialised process to create targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

P13569

UPID:

CFTR_HUMAN

Alternative names:

ATP-binding cassette sub-family C member 7; Channel conductance-controlling ATPase; cAMP-dependent chloride channel

Alternative UPACC:

P13569; Q20BG8; Q20BH2; Q2I0A1; Q2I102

Background:

The Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) is pivotal in epithelial ion and water transport, crucial for maintaining fluid homeostasis. Known alternatively as ATP-binding cassette sub-family C member 7, this protein facilitates chloride ion transport across cell membranes, influencing airway fluid balance and pathogen defense.

Therapeutic significance:

CFTR's malfunction is central to Cystic Fibrosis, a prevalent genetic disorder affecting exocrine glands, leading to severe respiratory and digestive issues. Insights into CFTR's function and regulation offer avenues for correcting the defective chloride channel activity, presenting potential therapeutic strategies for Cystic Fibrosis and related conditions.

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