Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 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 high-tech, dedicated method is applied to construct targeted 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.


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
Q9BXT4

UPID:
TDRD1_HUMAN

ALTERNATIVE NAMES:
Cancer/testis antigen 41.1

ALTERNATIVE UPACC:
Q9BXT4; A6NEN3; A6NMN2; B3KVI4; B4E2L5; D3DRC2; Q4G0Y8; Q6P518; Q9H7B3

BACKGROUND:
The Tudor domain-containing protein 1, known alternatively as Cancer/testis antigen 41.1, plays a central role in maintaining germline integrity during spermatogenesis. It acts by repressing transposable elements through the piRNA metabolic process, forming complexes with piRNAs and Piwi proteins to govern transposon methylation and repression. Essential for Piwi protein localization to the meiotic nuage, it also ensures the correct transcripts enter the piRNA pool, limiting cellular transcript entry into the piRNA pathway.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Tudor domain-containing protein 1 could open doors to potential therapeutic strategies.

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