Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 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 screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
Q8IZD9

UPID:
DOCK3_HUMAN

ALTERNATIVE NAMES:
Modifier of cell adhesion; Presenilin-binding protein

ALTERNATIVE UPACC:
Q8IZD9; O15017

BACKGROUND:
Dedicator of cytokinesis protein 3, known for its alternative names Modifier of cell adhesion and Presenilin-binding protein, is implicated in critical cellular functions. It serves as a potential guanine nucleotide exchange factor (GEF), essential for the activation of small GTPases through GDP to GTP exchange. Its interactions suggest a role in Alzheimer's disease by influencing Tau/MAPT phosphorylation and reducing amyloid-beta APBA1 protein secretion, which may affect small GTPase functions in actin cytoskeleton regulation or cell adhesion.

THERAPEUTIC SIGNIFICANCE:
Linked to a neurodevelopmental disorder characterized by developmental delay, hypotonia, and ataxia, Dedicator of cytokinesis protein 3's study offers a promising avenue for therapeutic intervention. Understanding its role could lead to novel strategies for treating related neurodevelopmental and neurodegenerative diseases.

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