AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for E3 ubiquitin-protein ligase Midline-1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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 high-tech, dedicated method is applied to construct targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.

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

O15344

UPID:

TRI18_HUMAN

Alternative names:

Midin; Putative transcription factor XPRF; RING finger protein 59; RING finger protein Midline-1; RING-type E3 ubiquitin transferase Midline-1; Tripartite motif-containing protein 18

Alternative UPACC:

O15344; B2RCG2; O75361; Q9BZX5

Background:

E3 ubiquitin-protein ligase Midline-1, known by alternative names such as Midin and RING finger protein Midline-1, plays a crucial role in cellular processes through its E3 ubiquitin ligase activity towards IGBP1. This activity promotes monoubiquitination leading to significant cellular outcomes, including the degradation of protein phosphatase PP2A's catalytic subunit.

Therapeutic significance:

The protein's mutation is directly linked to Opitz GBBB syndrome, a congenital disorder presenting a spectrum of physical and developmental challenges. Understanding the role of E3 ubiquitin-protein ligase Midline-1 could open doors to potential therapeutic strategies for managing and treating this complex syndrome.

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