Focused On-demand Libraries - Receptor.AI 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.


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 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 employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening 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.


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
Receptor.AI
 
UPACC
Q9Y6D6

UPID:
BIG1_HUMAN

ALTERNATIVE NAMES:
ADP-ribosylation factor guanine nucleotide-exchange factor 1; p200 ARF guanine nucleotide exchange factor; p200 ARF-GEP1

ALTERNATIVE UPACC:
Q9Y6D6; Q9NV46; Q9UFV2; Q9UNL0

BACKGROUND:
The multifunctional Brefeldin A-inhibited guanine nucleotide-exchange protein 1, known for its roles in ARF1 and ARF3 activation, is crucial for vesicular trafficking and Golgi apparatus integrity. It aids in integrin beta-1 maturation and cell polarity, acting as a bridge in Arf and PKA pathway crosstalk. Its inhibition of MYO9B's GAP activity further illustrates its regulatory complexity.

THERAPEUTIC SIGNIFICANCE:
Given its association with a spectrum of neurological disorders, including developmental delays and seizures, Brefeldin A-inhibited guanine nucleotide-exchange protein 1 represents a promising target for drug discovery. Exploring its functions could lead to breakthroughs in treating related conditions.

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