Focused On-demand Library for Cerebral cavernous malformations 2 protein

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.

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.

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.

We employ our advanced, specialised process to create targeted libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Our library is unique due to several crucial aspects:

Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

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.