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.


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.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We employ our advanced, specialised process to create 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.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q9H777

UPID:
RNZ1_HUMAN

ALTERNATIVE NAMES:
Deleted in Ma29; ElaC homolog protein 1; Ribonuclease Z 1; tRNA 3 endonuclease 1; tRNase Z 1

ALTERNATIVE UPACC:
Q9H777; Q9NS99

BACKGROUND:
The Zinc phosphodiesterase ELAC protein 1, known by alternative names such as Deleted in Ma29 and Ribonuclease Z 1, is integral to tRNA repair mechanisms. It exhibits zinc phosphodiesterase activity and some tRNA 3'-processing endonuclease activity, crucial for removing 2',3'-cyclic phosphate from tRNAs post-cleavage by ANKZF1. This process is essential for the subsequent processing of tRNAs by TRNT1, highlighting its pivotal role in maintaining cellular function.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Zinc phosphodiesterase ELAC protein 1 holds promise for unveiling novel therapeutic avenues.

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