AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Iron-sulfur cluster assembly 2 homolog, mitochondrial

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

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

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

Our high-tech, dedicated method is applied to construct targeted 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 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

Q86U28

UPID:

ISCA2_HUMAN

Alternative names:

HESB-like domain-containing protein 1

Alternative UPACC:

Q86U28; A6NFF1; A8K3W3; G3V291; Q8IYZ0; Q96BB2

Background:

Iron-sulfur cluster assembly 2 homolog, mitochondrial, also known as HESB-like domain-containing protein 1, plays a crucial role in the maturation of mitochondrial 4Fe-4S proteins. It functions late in the iron-sulfur cluster assembly pathway, potentially involving in the binding of an intermediate of Fe/S cluster assembly.

Therapeutic significance:

This protein is linked to Multiple mitochondrial dysfunctions syndrome 4, a severe disorder impacting systemic energy metabolism, leading to early death. Understanding the role of Iron-sulfur cluster assembly 2 homolog, mitochondrial could open doors to potential therapeutic strategies.

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