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

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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

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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