Focused On-demand Library for Phenazine biosynthesis-like domain-containing protein

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.

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.

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

Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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

P30039

UPID:

PBLD_HUMAN

Alternative names:

MAWD-binding protein; Unknown protein 32 from 2D-page of liver tissue

Alternative UPACC:

P30039; A8MZJ3; C9JIM0; Q9HCC2

Background:

The Phenazine biosynthesis-like domain-containing protein, also known as MAWD-binding protein and Unknown protein 32 from 2D-page of liver tissue, represents a unique entity in the proteomic landscape. Its nomenclature hints at a potential role in the biosynthesis of phenazines, a class of nitrogen-containing heterocyclic compounds known for their diverse biological activities.

Therapeutic significance:

Understanding the role of Phenazine biosynthesis-like domain-containing protein could open doors to potential therapeutic strategies. Its association with phenazine biosynthesis suggests a possible impact on microbial communities and infectious diseases, offering a novel angle for drug discovery efforts.