AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Cerebral cavernous malformations 2 protein

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.

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.

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.

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 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

Q9BSQ5

UPID:

CCM2_HUMAN

Alternative names:

Malcavernin

Alternative UPACC:

Q9BSQ5; A4D2L4; B3KUV0; D3DVL4; E9PDJ3; F5H0E1; F5H551; Q71RE5; Q8TAT4

Background:

The Cerebral cavernous malformations 2 protein, also known as Malcavernin, plays a pivotal role in the CCM signaling pathway, essential for heart and vessel formation and integrity. It functions as a scaffold protein for MAP2K3-MAP3K3 signaling, influencing endothelial cell junctions and modulating MAP3K3-dependent p38 activation in response to hyperosmotic shock.

Therapeutic significance:

Malcavernin's involvement in Cerebral cavernous malformations 2, a condition leading to hemorrhagic stroke and seizures, underscores its potential as a target for therapeutic intervention. Understanding Malcavernin's role could open doors to novel strategies for treating vascular anomalies of the central nervous system.

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