Focused On-demand Libraries - Receptor.AI 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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


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

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
P31415

UPID:
CASQ1_HUMAN

ALTERNATIVE NAMES:
Calmitine; Calsequestrin, skeletal muscle isoform

ALTERNATIVE UPACC:
P31415; B1AKZ2; B2R863; Q8TBW7

BACKGROUND:
Calsequestrin-1, also referred to as Calmitine, is a high-capacity, moderate affinity, calcium-binding protein essential for muscle function. It acts as an internal calcium reservoir in muscle tissues, binding around 80 Ca(2+) ions. Its function in regulating the release of lumenal Ca(2+) via the RYR1 channel and its negative regulation of SOCE activity are crucial for triggering muscle contraction.

THERAPEUTIC SIGNIFICANCE:
The involvement of Calsequestrin-1 in diseases such as Myopathy, vacuolar, with CASQ1 aggregates and Myopathy, tubular aggregate, 1, highlights its potential as a therapeutic target. These diseases, caused by variants affecting the gene encoding Calsequestrin-1, emphasize the protein's importance in muscle health and disease, suggesting that further research could lead to novel treatments.

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