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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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.


Our top-notch dedicated system is used to design specialised 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
Q92688

UPID:
AN32B_HUMAN

ALTERNATIVE NAMES:
Acidic protein rich in leucines; Putative HLA-DR-associated protein I-2; Silver-stainable protein SSP29

ALTERNATIVE UPACC:
Q92688; B2R9C7; O00655; P78458; P78459

BACKGROUND:
The multifunctional Acidic leucine-rich nuclear phosphoprotein 32 family member B is central to various biological processes including neuronal stem cell proliferation, leukemic cell differentiation, and cell cycle progression. It acts as a negative regulator of caspase-3-dependent apoptosis and possesses histone chaperone capabilities, crucial for recruiting histones to promoters. Its role extends to the regulation of mRNA export from the nucleus to the cytoplasm, particularly in response to microbial infections, where it aids in viral genome replication and foamy virus mRNA export.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Acidic leucine-rich nuclear phosphoprotein 32 family member B unveils potential pathways for innovative therapeutic interventions.

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