AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Cell cycle checkpoint control protein RAD9A

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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.

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.

We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.

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

Q99638

UPID:

RAD9A_HUMAN

Alternative names:

DNA repair exonuclease rad9 homolog A

Alternative UPACC:

Q99638; B2RCZ8; Q6FI29; Q96C41

Background:

Cell cycle checkpoint control protein RAD9A, also known as DNA repair exonuclease rad9 homolog A, is a key component of the 9-1-1 cell-cycle checkpoint response complex. This complex plays a pivotal role in DNA repair, particularly in long-patch base excision repair (LP-BER), by acting as a sliding clamp platform for various proteins involved in the repair process. RAD9A's activities include enhancing DNA polymerase beta (POLB) activity, facilitating endonuclease FEN1 cleavage, and stabilizing DNA ligase I (LIG1) on LP-BER substrates.

Therapeutic significance:

Understanding the role of Cell cycle checkpoint control protein RAD9A could open doors to potential therapeutic strategies.

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