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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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.


Our top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening 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.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
P81534

UPID:
D103A_HUMAN

ALTERNATIVE NAMES:
Beta-defensin 3; Defensin, beta 103; Defensin-like protein

ALTERNATIVE UPACC:
P81534; Q8NFG6; Q9NPF6

BACKGROUND:
Beta-defensin 103, with alternative names such as Beta-defensin 3 and Defensin-like protein, is recognized for its antimicrobial prowess. It combats a wide array of pathogens including Gram-positive and Gram-negative bacteria, as well as yeast, showcasing its capability to kill drug-resistant strains like multiresistant S. aureus and vancomycin-resistant E. faecium without significant hemolytic activity.

THERAPEUTIC SIGNIFICANCE:
The exploration of Beta-defensin 103's functionalities heralds a new era in antimicrobial therapy. Its efficacy against a diverse range of pathogens, including antibiotic-resistant strains, underscores its potential as a cornerstone in the development of innovative antimicrobial treatments.

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