AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Alpha-2-HS-glycoprotein

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.

Our top-notch dedicated system is used to design specialised 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 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

P02765

UPID:

FETUA_HUMAN

Alternative names:

Alpha-2-Z-globulin; Ba-alpha-2-glycoprotein; Fetuin-A

Alternative UPACC:

P02765; A8K9N6; B2R7G1; O14961; O14962; Q9P152

Background:

Alpha-2-HS-glycoprotein, also known as Fetuin-A, is a multifunctional protein with roles in endocytosis, opsonization, and mineral phase regulation in bone. It exhibits a strong affinity for calcium and barium ions, highlighting its significance in biological systems. Alternative names include Alpha-2-Z-globulin and Ba-alpha-2-glycoprotein.

Therapeutic significance:

Linked to Alopecia-intellectual disability syndrome 1, a rare autosomal recessive condition characterized by scalp hair loss, absence of eyebrows and eyelashes, and intellectual disability, Alpha-2-HS-glycoprotein's study could pave the way for novel therapeutic approaches.

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