Focused On-demand Libraries - Receptor.AI 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.


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.


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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of 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
Q6X4W1

UPID:
NSMF_HUMAN

ALTERNATIVE NAMES:
Nasal embryonic luteinizing hormone-releasing hormone factor

ALTERNATIVE UPACC:
Q6X4W1; Q2TB96; Q6X4V7; Q6X4V8; Q6X4V9; Q8N2M2; Q96SY1; Q9NPM4; Q9NPP3; Q9NPS3

BACKGROUND:
This protein, known for its role in coupling NMDA-sensitive glutamate receptor signaling to the nucleus, triggers significant cytoarchitectural changes in dendrites and spine synapse processes. It is a key player in the CREB shut-off signaling pathway and is vital for the development of olfactory axons and the migration of GnRH and LHRH neuronal cells.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of the NMDA receptor synaptonuclear signaling and neuronal migration factor offers a promising avenue for developing treatments for Hypogonadotropic hypogonadism 9, characterized by low gonadotropin and testosterone levels. This protein's role in the disease underscores its potential as a target for therapeutic intervention.

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