Focused On-demand Libraries - Receptor.AI 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.


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


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

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast 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
Receptor.AI
 
UPACC
Q9UM63

UPID:
PLAL1_HUMAN

ALTERNATIVE NAMES:
Lost on transformation 1; Pleiomorphic adenoma-like protein 1; Tumor suppressor ZAC

ALTERNATIVE UPACC:
Q9UM63; B2RBA4; B2RCM8; E1P595; E1P597; O76019; Q7Z3V8; Q92981; Q96JR9; Q9UIZ0

BACKGROUND:
The Zinc finger protein PLAGL1, with alternative names such as Lost on transformation 1, Pleiomorphic adenoma-like protein 1, and Tumor suppressor ZAC, acts as a transcriptional activator. Its role in regulating the transcription of the type 1 receptor for pituitary adenylate cyclase-activating polypeptide underscores its importance in cellular communication.

THERAPEUTIC SIGNIFICANCE:
Given PLAGL1's critical role in the onset of transient neonatal diabetes mellitus 1, marked by significant hyperglycemia within the first month of life, the protein represents a promising target for therapeutic intervention. The connection between PLAGL1 and disease pathogenesis, particularly through genetic and epigenetic mechanisms, highlights the potential for developing targeted therapies.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.