AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for B9 domain-containing protein 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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner 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.

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.

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.

partner

Reaxense

upacc

Q9BPU9

UPID:

B9D2_HUMAN

Alternative names:

MKS1-related protein 2

Alternative UPACC:

Q9BPU9

Background:

B9 domain-containing protein 2, also known as MKS1-related protein 2, plays a crucial role in the structure and function of primary cilia. It is a component of the tectonic-like complex, which is essential for preventing the diffusion of transmembrane proteins between the cilia and plasma membranes. This protein's involvement in ciliary functions underscores its importance in cellular signaling pathways and developmental processes.

Therapeutic significance:

B9 domain-containing protein 2 is implicated in Meckel syndrome 10 and Joubert syndrome 34, both of which are characterized by developmental anomalies in various organs. Understanding the role of B9 domain-containing protein 2 could open doors to potential therapeutic strategies for these ciliopathies, highlighting the importance of targeted research in uncovering treatment options.

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