Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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.


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 is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
P49721

UPID:
PSB2_HUMAN

ALTERNATIVE NAMES:
Macropain subunit C7-I; Multicatalytic endopeptidase complex subunit C7-I; Proteasome component C7-I

ALTERNATIVE UPACC:
P49721; D3DPS0; P31145; Q9BWZ9

BACKGROUND:
Proteasome subunit beta type-2, also referred to as Macropain subunit C7-I, plays a critical role in the proteolytic degradation of most intracellular proteins via the 20S core proteasome complex. This process is vital for the removal of proteins that are misfolded, damaged, or no longer needed, thereby ensuring cellular protein homeostasis. The protein is involved in both ATP-dependent and independent degradation pathways, impacting various cellular processes including spermatogenesis and the generation of MHC class I-presented antigenic peptides.

THERAPEUTIC SIGNIFICANCE:
The study of Proteasome subunit beta type-2 is crucial for the development of novel therapeutic approaches. Its central role in maintaining protein homeostasis and involvement in critical cellular processes make it a potential target for interventions aimed at treating diseases related to protein degradation and misfolding.

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