Focused On-demand Libraries - Receptor.AI 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 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 screening 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 distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
P43146

UPID:
DCC_HUMAN

ALTERNATIVE NAMES:
Colorectal cancer suppressor; Immunoglobulin superfamily DCC subclass member 1; Tumor suppressor protein DCC

ALTERNATIVE UPACC:
P43146

BACKGROUND:
The protein Netrin receptor DCC, recognized for its roles as Colorectal cancer suppressor and Immunoglobulin superfamily DCC subclass member 1, is crucial for neuronal development. It binds to netrin to guide axon growth and is implicated in axon repulsion when associated with UNC5 proteins. Its function extends beyond development, serving as a dependence receptor for apoptosis in the absence of netrin, indicating its significant role in cell fate decisions.

THERAPEUTIC SIGNIFICANCE:
Given its association with diseases such as Mirror movements 1 and familial horizontal gaze palsy with progressive scoliosis, DCC represents a promising target for therapeutic intervention. Its dual role in guiding neuronal development and inducing apoptosis, when unbound to netrin, offers potential pathways for addressing neurodevelopmental disorders and exploring cancer therapeutics.

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