Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive 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
Q16653

UPID:
MOG_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q16653; A6NDR4; A6NNJ9; A8MY31; B0UZR9; E9PGF0; F8W9D5; O00713; O00714; O00715; Q13054; Q13055; Q14855; Q29ZN8; Q56UY0; Q5JNX7; Q5JNY1; Q5JNY2; Q5JNY4; Q5SSB5; Q5SSB6; Q5STL9; Q5STM0; Q5STM1; Q5STM2; Q5STM5; Q5SUK5; Q5SUK7; Q5SUK8; Q5SUK9; Q5SUL0; Q5SUL1; Q8IYG5; Q92891; Q92892; Q92893; Q92894; Q92895; Q93053; Q96KU9; Q96KV0; Q96KV1; Q99605

BACKGROUND:
The protein Myelin-oligodendrocyte glycoprotein, integral to the myelin sheath in the central nervous system, facilitates crucial biological processes including cell adhesion and communication. Its role extends to serving as a receptor for pathogens like the rubella virus, showcasing its multifaceted function in both health and disease.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Myelin-oligodendrocyte glycoprotein could open doors to potential therapeutic strategies for Narcolepsy 7. This sleep disorder, with symptoms stemming from abnormal REM sleep and sudden muscle tone loss, is linked to genetic variants in the MOG gene, presenting a direct pathway for research into gene-targeted treatments.

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