Focused On-demand Library for Protein S100-A11

Focused On-demand Libraries - Receptor.AI 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. 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 use our state-of-the-art dedicated workflow for designing focused libraries.


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
P31949

UPID:
S10AB_HUMAN

ALTERNATIVE NAMES:
Calgizzarin; Metastatic lymph node gene 70 protein; Protein S100-C; S100 calcium-binding protein A11

ALTERNATIVE UPACC:
P31949; Q5VTK0

BACKGROUND:
The Protein S100-A11, with alternative names such as Calgizzarin and Metastatic lymph node gene 70 protein, is integral to keratinocyte differentiation and cornification. It belongs to the S100 protein family, known for their calcium-binding capabilities, playing a pivotal role in various cellular functions.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Protein S100-A11 offers a pathway to novel therapeutic approaches. Given its critical role in skin cell differentiation and health, targeting this protein could lead to breakthroughs in treatments for skin-related conditions, emphasizing the therapeutic potential of understanding S100-A11's biological activities.

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