Focused On-demand Library for Ras-related protein Ral-A

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.

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 employ our advanced, specialised process to create targeted 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

P11233

UPID:

RALA_HUMAN

Alternative names:

Alternative UPACC:

P11233; A4D1W3

Background:

Ras-related protein Ral-A plays a pivotal role in cellular processes such as gene expression, cell migration, proliferation, and membrane trafficking. It functions as a multifunctional GTPase, interacting with various effectors to execute its roles. Notably, it is involved in GTP-dependent exocytosis, integrin-dependent signaling, and mitotic cell division, highlighting its versatility in cellular functions.

Therapeutic significance:

Ral-A's involvement in Hiatt-Neu-Cooper neurodevelopmental syndrome, due to gene variants, underscores its potential as a therapeutic target. Understanding Ral-A's role could pave the way for innovative treatments for this and possibly other neurodevelopmental disorders.