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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


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 employ our advanced, specialised process to create targeted 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
Q9H1I8

UPID:
ASCC2_HUMAN

ALTERNATIVE NAMES:
ASC-1 complex subunit p100; Trip4 complex subunit p100

ALTERNATIVE UPACC:
Q9H1I8; B7Z8E0; F5H6J9; Q4TT54; Q8TAZ0; Q9H711; Q9H9D6

BACKGROUND:
The protein Activating signal cointegrator 1 complex subunit 2, also known as ASC-1 complex subunit p100, is integral to cellular mechanisms like DNA repair and ribosome quality control. By binding to polyubiquitinated proteins, it facilitates the recruitment of crucial complexes to sites of DNA damage and stalled ribosomes, playing a significant role in maintaining genomic stability and protein synthesis accuracy.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Activating signal cointegrator 1 complex subunit 2 reveals promising avenues for the development of novel therapeutic approaches.

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.