Focused On-demand Library for Lithostathine-1-alpha

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.

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.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

Our high-tech, dedicated method is applied to construct targeted libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

Several key aspects differentiate our library:

Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

P05451

UPID:

REG1A_HUMAN

Alternative names:

Islet cells regeneration factor; Islet of Langerhans regenerating protein; Pancreatic stone protein; Pancreatic thread protein; Regenerating islet-derived protein 1-alpha; Regenerating protein I alpha

Alternative UPACC:

P05451; P11379; Q4ZG28

Background:

Lithostathine-1-alpha, known by various names such as Islet cells regeneration factor and Pancreatic stone protein, plays a crucial role in biological systems. It acts as an inhibitor of spontaneous calcium carbonate precipitation and is linked to neuronal sprouting in the brain, as well as regeneration in the brain and pancreas.

Therapeutic significance:

Understanding the role of Lithostathine-1-alpha could open doors to potential therapeutic strategies, particularly in the context of pancreatic and neurological disorders.