Focused On-demand Library for Myelin-oligodendrocyte glycoprotein

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 our partner Reaxense.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening 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.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







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


Myelin-oligodendrocyte glycoprotein (MOG) plays a crucial role in the nervous system as a minor component of the myelin sheath. It is pivotal in mediating homophilic cell-cell adhesion, potentially influencing the completion and maintenance of the myelin sheath, alongside facilitating cell-cell communication. Additionally, MOG acts as a receptor for rubella virus, indicating its significance in microbial infection.

Therapeutic significance:

MOG's involvement in Narcolepsy 7, a neurological disorder characterized by excessive daytime sleepiness and cataplexy, underscores its therapeutic significance. The disorder's link to variants affecting the MOG gene highlights the potential for targeted therapeutic strategies aimed at mitigating or managing symptoms of narcolepsy and improving patient quality of life.

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