Focused On-demand Library for m7GpppX diphosphatase

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 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 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

Q96C86

UPID:

DCPS_HUMAN

Alternative names:

DCS-1; Decapping scavenger enzyme; Hint-related 7meGMP-directed hydrolase; Histidine triad nucleotide-binding protein 5; Histidine triad protein member 5; Scavenger mRNA-decapping enzyme DcpS

Alternative UPACC:

Q96C86; Q8NHL8; Q9Y2S5

Background:

The m7GpppX diphosphatase, also known as Decapping scavenger enzyme, plays a crucial role in mRNA decay by hydrolyzing residual cap structures after degradation. This enzyme specifically targets small capped oligoribonucleotides, releasing 5'-phosphorylated RNA fragments and 7-methylguanosine monophosphate (m7GMP), essential for mRNA turnover and cellular mRNA levels regulation.

Therapeutic significance:

Given its involvement in Al-Raqad syndrome, characterized by severe developmental delays and intellectual disability, targeting m7GpppX diphosphatase could offer novel therapeutic avenues. Understanding the enzyme's role in mRNA decay pathways may illuminate strategies to mitigate the syndrome's effects.