AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Guanine nucleotide exchange factor subunit RIC1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

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

Q4ADV7

UPID:

RIC1_HUMAN

Alternative names:

Connexin-43-interacting protein of 150 kDa; Protein RIC1 homolog; RAB6A-GEF complex partner protein 1

Alternative UPACC:

Q4ADV7; B2RN24; B7ZM67; G5E932; Q4VXJ8; Q4VXJ9; Q76MT5; Q8N6E0; Q8TEH4; Q9H0A5; Q9H9S1

Background:

The Guanine nucleotide exchange factor subunit RIC1, also known as Connexin-43-interacting protein of 150 kDa, Protein RIC1 homolog, and RAB6A-GEF complex partner protein 1, plays a pivotal role in cellular processes. It acts as a guanine nucleotide exchange factor (GEF) for RAB6A, facilitating the fusion of endosome-derived vesicles with the Golgi compartment. Additionally, it is involved in the recycling of mannose-6-phosphate receptors, phosphorylation and localization of GJA1, and is crucial for procollagen transport and secretion, impacting cartilage morphogenesis and craniofacial skeleton development.

Therapeutic significance:

Given its critical role in cellular processes and development, understanding the function of Guanine nucleotide exchange factor subunit RIC1 could unveil new therapeutic strategies, particularly in addressing CATIFA syndrome, a disorder linked to variants affecting this gene.

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