AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ezrin

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

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

P15311

UPID:

EZRI_HUMAN

Alternative names:

Cytovillin; Villin-2; p81

Alternative UPACC:

P15311; E1P5A8; P23714; Q4VX75; Q96CU8; Q9NSJ4

Background:

Ezrin, also known as Cytovillin, Villin-2, and p81, plays a crucial role in the structural organization of the plasma membrane. It is instrumental in connecting major cytoskeletal structures to the plasma membrane, facilitating the formation of microvilli and membrane ruffles in epithelial cells. Additionally, Ezrin, in conjunction with PLEKHG6, is essential for normal macropinocytosis, a process vital for nutrient intake and pathogen defense.

Therapeutic significance:

Understanding the role of Ezrin could open doors to potential therapeutic strategies. Its pivotal function in cellular structure and signaling pathways suggests that modulating Ezrin activity could influence disease outcomes, particularly in conditions where cellular architecture and signaling are compromised.

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