Focused On-demand Library for Transforming growth factor-beta-induced protein ig-h3

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 utilise our cutting-edge, exclusive workflow to develop 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

Q15582

UPID:

BGH3_HUMAN

Alternative names:

Kerato-epithelin; RGD-containing collagen-associated protein

Alternative UPACC:

Q15582; D3DQB1; O14471; O14472; O14476; O43216; O43217; O43218; O43219; Q53XM1

Background:

Transforming growth factor-beta-induced protein ig-h3, also known as Kerato-epithelin and RGD-containing collagen-associated protein, plays a crucial role in cell adhesion and potentially in cell-collagen interactions. This protein's involvement in the structural integrity and function of the cornea is underscored by its association with various forms of corneal dystrophies.

Therapeutic significance:

Given its pivotal role in corneal dystrophies such as epithelial basement membrane dystrophy, Groenouw type 1, lattice type 1 and 3A, Thiel-Behnke type, Reis-Bucklers type, and Avellino type, understanding the function of Transforming growth factor-beta-induced protein ig-h3 could pave the way for innovative therapeutic strategies targeting these debilitating eye diseases.