Focused On-demand Library for Probable ATP-dependent RNA helicase DDX20

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

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 comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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

Q9UHI6

UPID:

DDX20_HUMAN

Alternative names:

Component of gems 3; DEAD box protein 20; DEAD box protein DP 103; Gemin-3

Alternative UPACC:

Q9UHI6; B4DWV7; Q96F72; Q9NVM3; Q9UF59; Q9UIY0; Q9Y659

Background:

The Probable ATP-dependent RNA helicase DDX20, also known as Component of gems 3, DEAD box protein 20, DEAD box protein DP 103, and Gemin-3, is pivotal in the assembly of small nuclear ribonucleoproteins (snRNPs), essential for pre-mRNA splicing. It facilitates the formation of the spliceosome's building blocks by catalyzing the assembly of the Sm protein ring, crucial for core snRNP formation.

Therapeutic significance:

Understanding the role of Probable ATP-dependent RNA helicase DDX20 could open doors to potential therapeutic strategies.