Focused On-demand Library for Protein S100-A3

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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 top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
P33764

UPID:
S10A3_HUMAN

ALTERNATIVE NAMES:
Protein S-100E; S100 calcium-binding protein A3

ALTERNATIVE UPACC:
P33764; D3DV51; Q6FGE4

BACKGROUND:
The Protein S100-A3, with alternative names Protein S-100E and S100 calcium-binding protein A3, is integral to several physiological processes. Its ability to bind calcium and zinc underscores its importance in cellular signaling and function. The protein's role is particularly highlighted in the process of cuticle cell differentiation and in the structural development of hair, contributing to the formation of a protective barrier and maintaining hair health.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Protein S100-A3 offers a promising avenue for therapeutic innovation. Given its critical role in cuticle cell differentiation and hair formation, research into this protein could lead to novel treatments for skin and hair conditions, emphasizing the importance of its study in dermatological and cosmetic sciences.

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