Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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


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
O60828

UPID:
PQBP1_HUMAN

ALTERNATIVE NAMES:
38 kDa nuclear protein containing a WW domain; Polyglutamine tract-binding protein 1

ALTERNATIVE UPACC:
O60828; C9JQA1; Q4VY25; Q4VY26; Q4VY27; Q4VY29; Q4VY30; Q4VY34; Q4VY35; Q4VY36; Q4VY37; Q4VY38; Q9GZP2; Q9GZU4; Q9GZZ4

BACKGROUND:
Polyglutamine-binding protein 1, with alternative names such as 38 kDa nuclear protein containing a WW domain, is crucial for pre-mRNA splicing, transcription regulation, and innate immunity. Its role extends to neuron development and stress granule assembly, showcasing its versatility in cellular functions. The protein's interaction with ATXN1 mutant and participation in the transport of neuronal RNA granules underscore its significance in cellular mechanisms.

THERAPEUTIC SIGNIFICANCE:
Given its association with Renpenning syndrome 1, characterized by intellectual disability and craniofacial anomalies, the study of Polyglutamine-binding protein 1 offers a promising avenue for therapeutic intervention. Understanding its multifaceted role could open doors to potential therapeutic strategies, especially in the realm of genetic and neurodevelopmental disorders.

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