AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Low affinity immunoglobulin gamma Fc region receptor II-a

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.

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 employ our advanced, specialised process to create targeted 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.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

P12318

UPID:

FCG2A_HUMAN

Alternative names:

CDw32; Fc-gamma RII-a

Alternative UPACC:

P12318; Q8WUN1; Q8WW64

Background:

The Low affinity immunoglobulin gamma Fc region receptor II-a, also known as CDw32 and Fc-gamma RII-a, plays a crucial role in the immune response. It binds to the Fc region of immunoglobulins gamma, functioning as a low affinity receptor. This interaction initiates cellular responses against pathogens and soluble antigens, primarily through promoting phagocytosis of opsonized antigens.

Therapeutic significance:

Understanding the role of Low affinity immunoglobulin gamma Fc region receptor II-a could open doors to potential therapeutic strategies. Its involvement in initiating cellular responses highlights its potential as a target for modulating immune responses in various conditions.

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