AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Complement C1q subcomponent subunit C

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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We use our state-of-the-art dedicated workflow for designing focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

P02747

UPID:

C1QC_HUMAN

Alternative names:

-

Alternative UPACC:

P02747; Q7Z502; Q96DL2; Q96H05

Background:

Complement C1q subcomponent subunit C plays a pivotal role in the immune system as part of the C1 complex, which is essential for the activation of the complement classical pathway. This pathway is crucial for the clearance of pathogens and damaged cells. The protein facilitates the binding of the C1 complex to immune complexes, triggering a cascade of immune responses.

Therapeutic significance:

C1q deficiency 3, a disorder resulting from impaired activation of the complement classical pathway, highlights the critical role of Complement C1q subcomponent subunit C. This condition leads to severe immune responses, including skin lesions and increased risk of systemic lupus erythematosus. Understanding the role of Complement C1q subcomponent subunit C could open doors to potential therapeutic strategies for treating immune complex diseases.

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