AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Magnesium transporter protein 1

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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

Reaxense

upacc

Q9H0U3

UPID:

MAGT1_HUMAN

Alternative names:

Dolichyl-diphosphooligosaccharide--protein glycosyltransferase subunit MAGT1; Implantation-associated protein

Alternative UPACC:

Q9H0U3; B2RAR4; D3DTE3; Q53G00; Q6P577; Q8NBN6

Background:

Magnesium transporter protein 1 (MAGT1), also known as Dolichyl-diphosphooligosaccharide--protein glycosyltransferase subunit MAGT1 and Implantation-associated protein, plays a crucial role in the N-glycosylation process. It is an accessory component of the STT3B-containing form of the N-oligosaccharyl transferase (OST) complex, facilitating the transfer of high mannose oligosaccharide to nascent polypeptide chains. Additionally, MAGT1 may be involved in Mg(2+) transport in epithelial cells.

Therapeutic significance:

MAGT1's involvement in diseases such as Immunodeficiency, X-linked, with magnesium defect, Epstein-Barr virus infection and neoplasia, and Congenital disorder of glycosylation 1CC, underscores its potential as a target for therapeutic intervention. Understanding the role of MAGT1 could open doors to potential therapeutic strategies.

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