AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Spondin-2

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.

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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

Q9BUD6

UPID:

SPON2_HUMAN

Alternative names:

Differentially expressed in cancerous and non-cancerous lung cells 1; Mindin

Alternative UPACC:

Q9BUD6; D3DVN9; Q4W5N4; Q9ULW1

Background:

Spondin-2, also known as Mindin and differentially expressed in cancerous and non-cancerous lung cells 1, is a pivotal cell adhesion protein. It plays a crucial role in promoting adhesion and outgrowth of hippocampal embryonic neurons. Beyond its structural functions, Spondin-2 directly binds to bacteria and their components, acting as an opsonin for macrophage phagocytosis of bacteria. This positions it as an essential molecule in initiating the innate immune response and as a unique pattern-recognition molecule in the extracellular matrix for microbial pathogens.

Therapeutic significance:

Understanding the role of Spondin-2 could open doors to potential therapeutic strategies.

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