Focused On-demand Library for Ficolin-2

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.

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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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.

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.







Alternative names:

37 kDa elastin-binding protein; Collagen/fibrinogen domain-containing protein 2; EBP-37; Ficolin-B; Ficolin-beta; Hucolin; L-ficolin; Serum lectin p35

Alternative UPACC:

Q15485; A6NFG7; A8K478; Q6IS69; Q7M4P4; Q9UC57


Ficolin-2, also known as L-ficolin or Serum lectin p35, is a key player in innate immunity, recognized for its role in the lectin complement pathway. This calcium-dependent and GlcNAc-binding lectin is pivotal in enhancing the phagocytosis of S.typhimurium by neutrophils, indicating an opsonic effect through its collagen region. Its alternative names include 37 kDa elastin-binding protein, Collagen/fibrinogen domain-containing protein 2, and Ficolin-B, among others.

Therapeutic significance:

Understanding the role of Ficolin-2 could open doors to potential therapeutic strategies. Its involvement in innate immunity and the lectin complement pathway highlights its significance in developing treatments for infectious diseases.

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