Focused On-demand Libraries - Receptor.AI 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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by 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.


We use our state-of-the-art dedicated workflow for designing focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q9Y5Q3

UPID:
MAFB_HUMAN

ALTERNATIVE NAMES:
V-maf musculoaponeurotic fibrosarcoma oncogene homolog B

ALTERNATIVE UPACC:
Q9Y5Q3; B3KNE1; Q9H1F1

BACKGROUND:
The Transcription factor MafB, alternatively named V-maf musculoaponeurotic fibrosarcoma oncogene homolog B, is pivotal in regulating hematopoiesis and differentiation in various cells, including macrophages and osteoclasts. It activates key promoters for insulin and glucagon, and its activity is influenced by SUMO modification.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in diseases like Multicentric carpotarsal osteolysis syndrome and Duane retraction syndrome 3, targeting Transcription factor MafB offers a promising avenue for developing novel treatments. Its multifaceted role in biological systems makes it an intriguing subject for scientific inquiry and therapeutic intervention.

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