Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.


We employ our advanced, specialised process to create targeted 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.


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
O75635

UPID:
SPB7_HUMAN

ALTERNATIVE NAMES:
Megsin; TP55

ALTERNATIVE UPACC:
O75635; B4DUW8; F5GZC0; Q1ED45; Q3KPG4

BACKGROUND:
The protein Serpin B7, known by its alternative names Megsin and TP55, is implicated in inhibiting Lys-specific proteases and influencing megakaryocyte maturation. Its unique functions suggest a pivotal role in the body's defense mechanisms and cellular development processes, making it a subject of significant interest in the field of molecular biology.

THERAPEUTIC SIGNIFICANCE:
Given its link to the genetic condition Keratoderma, palmoplantar, Nagashima type, Serpin B7 presents a promising avenue for research into novel treatment options. The exploration of Serpin B7's functions and mechanisms could lead to breakthroughs in therapeutic approaches for patients suffering from related keratotic disorders.

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