Focused On-demand Library for Plasmalemma vesicle-associated protein

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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

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 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

Q9BX97

UPID:

PLVAP_HUMAN

Alternative names:

Fenestrated endothelial-linked structure protein; Plasmalemma vesicle protein 1

Alternative UPACC:

Q9BX97; Q86VP0; Q8N8Y0; Q8ND68; Q8TER8; Q9BZD5

Background:

Plasmalemma vesicle-associated protein, also known as Fenestrated endothelial-linked structure protein, plays a pivotal role in endothelial cell membrane dynamics. It is instrumental in the formation of diaphragms in endothelial fenestrae, caveolae stomata, and transendothelial channels, crucial for microvascular permeability and the regulation of solute and water passage across the endothelial barrier.

Therapeutic significance:

Linked to Diarrhea 10, a protein-losing enteropathy type disorder, this protein's dysfunction manifests in severe electrolyte imbalances and protein loss, highlighting its potential as a therapeutic target. Understanding its role could pave the way for innovative treatments for vascular and developmental disorders.