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.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


Our top-notch dedicated system is used to design specialised libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
Q15047

UPID:
SETB1_HUMAN

ALTERNATIVE NAMES:
ERG-associated protein with SET domain; Histone H3-K9 methyltransferase 4; Lysine N-methyltransferase 1E; SET domain bifurcated 1

ALTERNATIVE UPACC:
Q15047; A6NEW2; Q5SZD8; Q5SZD9; Q5SZE0; Q5SZE7; Q96GM9

BACKGROUND:
SET domain bifurcated 1, a histone H3-K9 methyltransferase, is integral to the epigenetic transcriptional repression mechanism by inducing H3 'Lys-9' trimethylation. This enzyme is vital for the silencing of genes in euchromatic regions, linking DNA methylation with histone modification. It plays a significant role in embryonic stem cells by maintaining a transcriptionally repressive state, and in colorectal cancer cells, it is implicated in the hypermethylation and silencing of tumor suppressor genes. SETDB1's interaction with TRIM28 and KRAB zinc-finger proteins underscores its importance in gene regulation.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of SET domain bifurcated 1 could open doors to potential therapeutic strategies.

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