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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.


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
Q96KR4

UPID:
LMLN_HUMAN

ALTERNATIVE NAMES:
Invadolysin

ALTERNATIVE UPACC:
Q96KR4; B3LDG9; B3LDH0; C9J796; F8WB28; Q96KR5

BACKGROUND:
The protein Invadolysin, officially termed Leishmanolysin-like peptidase and cataloged under the accession Q96KR4, functions as a metalloprotease. It plays a pivotal role in the breakdown of proteins by cleaving peptide bonds, an essential process for cellular homeostasis and signaling.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Leishmanolysin-like peptidase offers a promising avenue for drug discovery. By elucidating its role in cellular processes, researchers can identify new targets for therapeutic intervention, potentially leading to breakthroughs in treatment modalities.

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