Focused On-demand Library for Cartilage intermediate layer protein 1

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.


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 includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


We utilise our cutting-edge, exclusive workflow to develop 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.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

PARTNER
Receptor.AI
 
UPACC
O75339

UPID:
CILP1_HUMAN

ALTERNATIVE NAMES:
Cartilage intermediate-layer protein

ALTERNATIVE UPACC:
O75339; B2R8F7; Q6UW99; Q8IYI5

BACKGROUND:
The Cartilage intermediate layer protein 1, known for its pivotal role in cartilage structure maintenance, acts by counteracting the effects of TGF-beta1 and IGF1, crucial factors in cartilage development and repair. Its functions include the inhibition of IGF1-induced cell proliferation and the synthesis of sulfated proteoglycans, as well as the prevention of IGF1R autophosphorylation, highlighting its importance in cartilage health.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Cartilage intermediate layer protein 1 could open doors to potential therapeutic strategies, especially in the context of Intervertebral disc disease. This disease, characterized by lumbar spine degeneration and associated pain, could benefit from targeted interventions aimed at modulating the protein's activity, offering new avenues for alleviating symptoms and potentially reversing damage.

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