Focused On-demand Library for Mu-type opioid receptor

Focused On-demand Libraries - Reaxense 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 our partner 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 for receptors.

Fig. 1. The sreening workflow of Receptor.AI

The method involves detailed molecular simulations of the receptor in its native membrane environment, with ensemble virtual screening focusing on its conformational mobility. When dealing with dimeric or oligomeric receptors, the whole functional complex is modelled, and the tentative binding pockets on and between the subunits are established to address all possible mechanisms of action.

Key features that set our library apart include:

The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

P35372

UPID:

OPRM_HUMAN

Alternative names:

Mu opiate receptor; Mu opioid receptor

Alternative UPACC:

P35372; B0FXJ1; B2R9S7; B8Q1L7; B8Q1L8; B8Q1L9; E7EWZ3; G8XRH6; G8XRH8; Q12930; Q4VWM1; Q4VWM2; Q4VWM3; Q4VWM4; Q4VWM6; Q4VWX6; Q5TDA1; Q6UPP1; Q6UQ80; Q7Z2D8; Q86V80; Q8IWW3; Q8IWW4; Q9UCZ4; Q9UN57

Background:

The Mu-type opioid receptor, encoded by the gene P35372, plays a pivotal role in mediating the effects of opioids, including natural endogenous peptides and synthetic drugs. It functions as a receptor for substances like beta-endorphin and various opioids such as morphine and fentanyl, triggering a cascade of intracellular signaling pathways. This receptor's activity involves coupling with G-proteins to modulate cellular responses, including the inhibition of adenylate cyclase and regulation of ion channels and MAPK pathways.

Therapeutic significance:

Understanding the role of the Mu-type opioid receptor could open doors to potential therapeutic strategies. Its involvement in pain modulation and reward systems makes it a critical target for treating pain and addiction. The receptor's complex signaling mechanisms offer multiple intervention points for developing drugs with improved efficacy and reduced side effects.