Focused On-demand Library for Collagen triple helix repeat-containing protein 1

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We utilise our cutting-edge, exclusive workflow to develop focused libraries.

Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of 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

Q96CG8

UPID:

CTHR1_HUMAN

Alternative names:

Alternative UPACC:

Q96CG8; G3V141; Q6UW91; Q8IX63

Background:

Collagen triple helix repeat-containing protein 1 plays a pivotal role in the structural integrity and function of connective tissues. Its primary function is to act as a negative regulator of collagen matrix deposition, ensuring the proper assembly and maintenance of the extracellular matrix. This protein's unique ability to modulate collagen deposition is crucial for tissue development and repair.

Therapeutic significance:

The association of Collagen triple helix repeat-containing protein 1 with Barrett esophagus highlights its potential as a therapeutic target. Barrett esophagus, a condition resulting from chronic gastroesophageal reflux, can progress to esophageal adenocarcinoma. Understanding the role of this protein in the pathogenesis of Barrett esophagus could lead to novel strategies for preventing or treating this precursor to esophageal cancer.