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.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


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


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds 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
Q86YW9

UPID:
MD12L_HUMAN

ALTERNATIVE NAMES:
Mediator complex subunit 12-like protein; Thyroid hormone receptor-associated-like protein; Trinucleotide repeat-containing gene 11 protein-like

ALTERNATIVE UPACC:
Q86YW9; Q96PC7; Q96PC8; Q9H9M5; Q9HCD7; Q9UI69

BACKGROUND:
The Mediator of RNA polymerase II transcription subunit 12-like protein, alternatively named Thyroid hormone receptor-associated-like protein, is integral to the Mediator complex. This complex is a coactivator involved in the transcription of RNA polymerase II-dependent genes, serving as a scaffold for the preinitiation complex and ensuring efficient gene transcription.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Mediator of RNA polymerase II transcription subunit 12-like protein could open doors to potential therapeutic strategies. Its association with Nizon-Isidor syndrome, characterized by developmental delays and behavioral issues, underscores the importance of research into its functions and mechanisms. Targeting this protein could offer new pathways for treating or managing this and potentially other related neurodevelopmental disorders.

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