AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for DNA repair protein RAD51 homolog 4

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 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 utilise our cutting-edge, exclusive workflow to develop focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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

O75771

UPID:

RA51D_HUMAN

Alternative names:

R51H3; RAD51 homolog D; RAD51-like protein 3; TRAD

Alternative UPACC:

O75771; B4DJU7; E1P637; O43537; O60355; O75196; O75847; O75848; O76073; O76085; O94908; Q9UFU5

Background:

DNA repair protein RAD51 homolog 4, also known as RAD51D, plays a crucial role in the homologous recombination repair (HRR) pathway, essential for the repair of double-stranded DNA breaks. It is part of the RAD51 paralog protein complex BCDX2, acting in the BRCA1-BRCA2-dependent HR pathway, crucial for maintaining genomic stability.

Therapeutic significance:

RAD51D is linked to Breast-ovarian cancer, familial, 4, highlighting its role in cancer predisposition. Understanding RAD51D's function could lead to novel therapeutic strategies for managing and treating familial breast and ovarian cancers.

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