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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


We use our state-of-the-art dedicated workflow for designing focused 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.


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
Q86UL8

UPID:
MAGI2_HUMAN

ALTERNATIVE NAMES:
Atrophin-1-interacting protein 1; Atrophin-1-interacting protein A; Membrane-associated guanylate kinase inverted 2

ALTERNATIVE UPACC:
Q86UL8; A4D1C1; A7E2C3; O60434; O60510; Q86UI7; Q9NP44; Q9UDQ5; Q9UDU1

BACKGROUND:
The protein Membrane-associated guanylate kinase, WW and PDZ domain-containing protein 2, known for assembling neurotransmitter receptors and cell adhesion proteins, is pivotal in receptor-mediated endocytosis and ciliogenesis. Its function in regulating activin-mediated signaling and enhancing PTEN's suppression of AKT1 activation underscores its significance in neuronal development and cellular signaling pathways.

THERAPEUTIC SIGNIFICANCE:
Exploring the therapeutic potential of Membrane-associated guanylate kinase, WW and PDZ domain-containing protein 2 in the context of Nephrotic syndrome 15 could offer new avenues for treatment, given its variable disease severity and potential for rapid progression to end-stage renal failure.

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