AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Activating signal cointegrator 1 complex subunit 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner 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 sreening 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.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

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:

Activating signal cointegrator 1 complex subunit 2 (ASC-1 complex subunit p100) is a pivotal ubiquitin-binding protein, playing a crucial role in DNA repair and ribosome rescue. It is a part of the ASCC complex, enhancing DNA damage repair by recruiting ASCC3 and ALKBH3 to damaged sites. Additionally, it is involved in the ribosome quality control (RQC) pathway, identifying and disassembling stalled ribosomes, thus ensuring cellular fidelity.

Therapeutic significance:

Understanding the role of Activating signal cointegrator 1 complex subunit 2 could open doors to potential therapeutic strategies.

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