Focused On-demand Library for RILP-like 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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


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.


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


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
Q5EBL4

UPID:
RIPL1_HUMAN

ALTERNATIVE NAMES:
Rab-interacting lysosomal-like protein 1

ALTERNATIVE UPACC:
Q5EBL4; Q66K36; Q8N1M0

BACKGROUND:
The RILP-like protein 1, known for its role in the regulation of cell shape and polarity, is essential for neuroprotection and cellular protein transport. It competes with SIAH1 for GAPDH binding, preventing GAPDH's apoptotic function in the nucleus. Notably, it does not influence lysosomal morphology but binds to phosphorylated RAB10, affecting ciliogenesis.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in Oculopharyngodistal myopathy 4, a condition marked by muscle weakness and myopathic changes, RILP-like protein 1 emerges as a key target in muscle disorder research. Understanding the role of RILP-like protein 1 could open doors to potential therapeutic strategies.

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