Focused On-demand Libraries - Receptor.AI 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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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 employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
P0C7P0

UPID:
CISD3_HUMAN

ALTERNATIVE NAMES:
MitoNEET-related protein 2; Mitochondrial inner NEET protein

ALTERNATIVE UPACC:
P0C7P0

BACKGROUND:
The CDGSH iron-sulfur domain-containing protein 3, located in mitochondria and known alternatively as MitoNEET-related protein 2 or Mitochondrial inner NEET protein, is pivotal for transferring iron-sulfur clusters to apoferrodoxins FDX1 and FDX2. This process is vital for the regulation of mitochondrial iron homeostasis, influencing both free iron levels and reactive oxygen species, thereby supporting normal mitochondrial functionality.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of CDGSH iron-sulfur domain-containing protein 3 offers a promising avenue for developing therapeutic interventions aimed at modulating mitochondrial iron and reactive oxygen species levels.

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