AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ficolin-3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

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 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.

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

O75636

UPID:

FCN3_HUMAN

Alternative names:

Collagen/fibrinogen domain-containing lectin 3 p35; Collagen/fibrinogen domain-containing protein 3; Hakata antigen

Alternative UPACC:

O75636; Q6IBJ5; Q8WW86

Background:

Ficolin-3, known alternatively as Collagen/fibrinogen domain-containing lectin 3 p35, plays a pivotal role in innate immunity. It activates the lectin complement pathway, binding specifically to certain sugars and lipopolysaccharides, indicating its crucial role in recognizing and combating pathogens. Its affinity for GalNAc, GlcNAc, D-fucose, and lipopolysaccharides from S.typhimurium and S.minnesota underscores its specificity and importance in immune responses.

Therapeutic significance:

Ficolin 3 deficiency, a disorder marked by immunodeficiency and recurrent infections, underscores the protein's critical role in human health. Understanding the role of Ficolin-3 could open doors to potential therapeutic strategies, especially for enhancing immune responses and developing treatments for related immunodeficiencies.

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