Focused On-demand Library for Complement component 1 Q subcomponent-binding protein, mitochondrial

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 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 use our state-of-the-art dedicated workflow for designing 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.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.







Alternative names:

ASF/SF2-associated protein p32; Glycoprotein gC1qBP; Hyaluronan-binding protein 1; Mitochondrial matrix protein p32; gC1q-R protein; p33

Alternative UPACC:

Q07021; Q2HXR8; Q9NNY8


The Complement component 1 Q subcomponent-binding protein, mitochondrial, known by alternative names such as ASF/SF2-associated protein p32 and Glycoprotein gC1qBP, plays a pivotal role in various biological processes. It is involved in inflammation, infection, ribosome biogenesis, mitochondrial protein synthesis, apoptosis regulation, transcriptional regulation, and pre-mRNA splicing. Its ability to bind to plasma proteins and act as a receptor for C1q highlights its significance in the immune response and coagulation pathways.

Therapeutic significance:

Given its involvement in Combined oxidative phosphorylation deficiency 33, a disorder with mitochondrial energy metabolism defects, understanding the role of Complement component 1 Q subcomponent-binding protein, mitochondrial could open doors to potential therapeutic strategies.

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