AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Reticulocalbin-3

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.

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

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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

Reaxense

upacc

Q96D15

UPID:

RCN3_HUMAN

Alternative names:

EF-hand calcium-binding protein RLP49

Alternative UPACC:

Q96D15; Q9HBZ8

Background:

Reticulocalbin-3, also known as EF-hand calcium-binding protein RLP49, plays a pivotal role in protein biosynthesis and transport within the endoplasmic reticulum. It is essential for the proper function and transport of key pulmonary surfactant proteins and the lipid transporter ABCA3. This protein's involvement in regulating the expression and degradation of these crucial components underscores its significance in maintaining pulmonary surfactant homeostasis. Additionally, Reticulocalbin-3 exhibits an anti-fibrotic activity by modulating the secretion of type I and III collagens, and it influences the secretion of PCSK6, highlighting its multifunctional nature.

Therapeutic significance:

Understanding the role of Reticulocalbin-3 could open doors to potential therapeutic strategies.

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