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.


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 employ our advanced, specialised process to create targeted 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.


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
Q9H0V9

UPID:
LMA2L_HUMAN

ALTERNATIVE NAMES:
Lectin mannose-binding 2-like

ALTERNATIVE UPACC:
Q9H0V9; B4DSH3; D3DXH6; Q53GV3; Q53S67; Q63HN6; Q8NBQ6; Q9BQ14

BACKGROUND:
VIP36-like protein, identified by its alternative name Lectin mannose-binding 2-like, is implicated in the regulation of glycoprotein export from the endoplasmic reticulum. Its role as a regulator of ERGIC-53 positions it as a key player in protein trafficking pathways, essential for proper cellular function and homeostasis.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in Intellectual developmental disorder, autosomal recessive 52, and Intellectual developmental disorder, autosomal dominant 69, the VIP36-like protein presents a promising avenue for research into novel therapeutic approaches. Understanding the role of VIP36-like protein could open doors to potential therapeutic strategies, providing new pathways for treating these developmental disorders.

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