Focused On-demand Library for Putative DBH-like monooxygenase protein 2

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.

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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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

A6NHM9

UPID:

MOXD2_HUMAN

Alternative names:

DBH-like monooxygenase protein 2 pseudogene

Alternative UPACC:

A6NHM9

Background:

The Putative DBH-like monooxygenase protein 2, also known as DBH-like monooxygenase protein 2 pseudogene, represents a unique entity in the proteomic landscape. Its designation as a pseudogene suggests a complex evolutionary history, potentially encoding for enzymes involved in catalytic processes similar to those of dopamine beta-hydroxylase.

Therapeutic significance:

Understanding the role of Putative DBH-like monooxygenase protein 2 could open doors to potential therapeutic strategies. Its evolutionary link to critical enzymatic pathways hints at untapped pharmacological potential, awaiting exploration.