Focused On-demand Libraries - Receptor.AI 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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


We use our state-of-the-art dedicated workflow for designing focused libraries.


 

Fig. 1. The screening 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 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
Q9NR61

UPID:
DLL4_HUMAN

ALTERNATIVE NAMES:
Drosophila Delta homolog 4

ALTERNATIVE UPACC:
Q9NR61; Q3KP23; Q9NQT9

BACKGROUND:
The Delta-like protein 4, an alternative name Drosophila Delta homolog 4, is integral to the Notch signaling pathway, serving as a ligand that activates NOTCH1 and NOTCH4. Its functions extend to inhibiting endothelial cell proliferation and migration in angiogenesis, supporting retinal progenitor proliferation, and influencing spinal cord neurogenesis by preventing V2a interneuron fate.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in Adams-Oliver syndrome 6, which manifests through skin and limb abnormalities, Delta-like protein 4 represents a key target for therapeutic intervention. Exploring the functions of Delta-like protein 4 could lead to innovative treatments for this and related disorders.

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