Focused On-demand Library for ER degradation-enhancing alpha-mannosidase-like protein 3

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.

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 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 utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.

Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Our library is unique due to several crucial aspects:

Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q9BZQ6

UPID:

EDEM3_HUMAN

Alternative names:

Alpha-1,2-mannosidase EDEM3

Alternative UPACC:

Q9BZQ6; B2RCH6; B7ZLZ2; Q0VGM5; Q5TEZ0; Q7L2Y5; Q9HCW1; Q9UFV7

Background:

ER degradation-enhancing alpha-mannosidase-like protein 3 (EDEM3) plays a pivotal role in the endoplasmic reticulum-associated degradation (ERAD) pathway. It accelerates the glycoprotein ERAD by proteasomes, catalyzing mannose trimming in N-glycans, essential for maintaining cellular function and protein quality control.

Therapeutic significance:

EDEM3's involvement in Congenital disorder of glycosylation 2V, characterized by neurodevelopmental delay and facial dysmorphic features, underscores its therapeutic potential. Understanding EDEM3's role could open doors to novel therapeutic strategies for addressing glycosylation disorders.