Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


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


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
P25786

UPID:
PSA1_HUMAN

ALTERNATIVE NAMES:
30 kDa prosomal protein; Macropain subunit C2; Multicatalytic endopeptidase complex subunit C2; Proteasome component C2; Proteasome nu chain

ALTERNATIVE UPACC:
P25786; A8K400; Q53YE8; Q9BRV9

BACKGROUND:
Proteasome subunit alpha type-1, also referred to as Macropain subunit C2 or Proteasome nu chain, is integral to the 20S proteasome complex. This complex is vital for the ATP-dependent and independent degradation of proteins, playing a key role in spermatogenesis and the generation of MHC class I-presented antigenic peptides. Such processes are crucial for the maintenance of cellular integrity and function.

THERAPEUTIC SIGNIFICANCE:
The exploration of Proteasome subunit alpha type-1's function offers promising avenues for drug discovery and therapeutic intervention. Its critical role in protein homeostasis and immune response underscores its potential as a target for developing treatments that harness the body's natural degradation mechanisms.

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