AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for EH domain-containing protein 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate 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.

Our high-tech, dedicated method is applied to construct targeted 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 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

Q9NZN4

UPID:

EHD2_HUMAN

Alternative names:

PAST homolog 2

Alternative UPACC:

Q9NZN4; B2RDH9; B4DNU6; Q96CB6

Background:

EH domain-containing protein 2, also known as PAST homolog 2, is a pivotal ATP- and membrane-binding protein. It orchestrates membrane reorganization and tubulation upon ATP hydrolysis, facilitating membrane trafficking between the plasma membrane and endosomes. This protein is crucial for the internalization of GLUT4, fusion of myoblasts to skeletal muscle myotubes, and the normal translocation of FER1L5 to the plasma membrane. Additionally, it plays a significant role in regulating the equilibrium between cell surface-associated and cell surface-dissociated caveolae.

Therapeutic significance:

Understanding the role of EH domain-containing protein 2 could open doors to potential therapeutic strategies.

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