Focused On-demand Library for Putative pre-mRNA-splicing factor ATP-dependent RNA helicase DHX32

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 pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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.

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

Q7L7V1

UPID:

DHX32_HUMAN

Alternative names:

DEAD/H box 32; DEAD/H helicase-like protein 1; DEAH box protein 32; HuDDX32

Alternative UPACC:

Q7L7V1; A8MSV2; D3DRF9; Q49AG5; Q5T3L0; Q5T3L5; Q96NY1; Q9BUN0; Q9H769; Q9NSL5; Q9NV74; Q9NVJ7

Background:

The Putative pre-mRNA-splicing factor ATP-dependent RNA helicase DHX32, known by alternative names such as DEAD/H box 32 and DEAH box protein 32, plays a crucial role in RNA processing. Its involvement in the intricate process of pre-mRNA splicing underscores its importance in cellular function and gene expression regulation.

Therapeutic significance:

Understanding the role of Putative pre-mRNA-splicing factor ATP-dependent RNA helicase DHX32 could open doors to potential therapeutic strategies. Its pivotal role in RNA processing makes it a promising target for drug discovery, aiming to modulate gene expression in disease conditions.