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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


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.


We use our state-of-the-art dedicated workflow for designing focused 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.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
O00370

UPID:
LORF2_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
O00370

BACKGROUND:
LINE-1 ORF2 protein, with its reverse transcriptase and endonuclease activities, is essential for the retrotransposition of LINE-1 elements, contributing to genomic variability. This protein's ability to cleave DNA in specific AT-rich regions, guided by the conformational properties of the target DNA rather than specific nucleotides, highlights its critical role in LINE-1 integration into the genome. The protein's distinctive mechanism of action, which includes compression near the cleavage site without bending the DNA helix, sets it apart from related endonucleases.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of the LINE-1 ORF2 protein offers a promising pathway to uncovering new therapeutic avenues. Its fundamental role in the process of retrotransposition and genomic diversity makes it an attractive target for developing innovative treatments for a range of genetic conditions.

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