Focused On-demand Library for Magnesium transporter NIPA1

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 strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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
Q7RTP0

UPID:
NIPA1_HUMAN

ALTERNATIVE NAMES:
Non-imprinted in Prader-Willi/Angelman syndrome region protein 1; Spastic paraplegia 6 protein

ALTERNATIVE UPACC:
Q7RTP0; B2RA76; Q5HYA9; Q7KZB0; Q86XW4

BACKGROUND:
The Magnesium transporter NIPA1, known for its alternative names such as Non-imprinted in Prader-Willi/Angelman syndrome region protein 1 and Spastic paraplegia 6 protein, is pivotal in Mg(2+) transport. It also transports divalent cations like Fe(2+), Sr(2+), and Mn(2+) albeit less efficiently.

THERAPEUTIC SIGNIFICANCE:
Linked to Spastic paraplegia 6, autosomal dominant, a condition characterized by progressive weakness and spasticity, NIPA1's genetic variants underscore its clinical importance. Exploring NIPA1's function offers a promising avenue for developing targeted treatments for this debilitating disorder.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.


Page 84 of 8789