AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Roundabout homolog 2

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.

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.

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 employ our advanced, specialised process to create targeted libraries for protein-protein interfaces.

 Fig. 1. The sreening workflow of Receptor.AI

This process entails comprehensive molecular simulations of the target protein, individually and in complex with essential partner proteins, along with ensemble virtual screening that focuses on conformational mobility in both its free and complex states. Potential binding pockets are considered at the protein-protein interaction interface and in remote allosteric locations to address every conceivable mechanism of action.

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

Q9HCK4

UPID:

ROBO2_HUMAN

Alternative names:

-

Alternative UPACC:

Q9HCK4; O43608; Q19AB4; Q19AB5

Background:

Roundabout homolog 2, encoded by the gene with accession number Q9HCK4, serves as a receptor for SLIT2 and likely SLIT1. These ligands are pivotal in cellular migration, including axonal navigation during neural development and axonal projection to various regions.

Therapeutic significance:

Vesicoureteral reflux 2, a congenital anomaly of the kidney and urinary tract, is associated with mutations affecting Roundabout homolog 2. Understanding its role could lead to novel therapeutic strategies for managing this condition and preventing its complications, such as urinary tract infections and renal scarring.

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