AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Protein S100-A7A

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 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

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.

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

Q86SG5

UPID:

S1A7A_HUMAN

Alternative names:

S100 calcium-binding protein A15; S100 calcium-binding protein A7-like 1; S100 calcium-binding protein A7A

Alternative UPACC:

Q86SG5; D3DV38; Q5SY69

Background:

Protein S100-A7A, also known as S100 calcium-binding protein A15, S100 calcium-binding protein A7-like 1, and S100 calcium-binding protein A7A, plays a pivotal role in epidermal differentiation and inflammation. This protein's involvement in these processes suggests it could be crucial for understanding the pathogenesis of psoriasis and potentially other inflammatory diseases.

Therapeutic significance:

Understanding the role of Protein S100-A7A could open doors to potential therapeutic strategies. Its involvement in epidermal differentiation and inflammation positions it as a key target for developing treatments for psoriasis and other related conditions.

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