Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.


We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.


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
Q8NB12

UPID:
SMYD1_HUMAN

ALTERNATIVE NAMES:
SET and MYND domain-containing protein 1

ALTERNATIVE UPACC:
Q8NB12; A0AV30; A6NE13

BACKGROUND:
The enzyme Histone-lysine N-methyltransferase SMYD1, alternatively named SET and MYND domain-containing protein 1, is integral to the process of histone modification. By methylating histone H3 at 'Lys-4', it can perform mono-, di-, and trimethylation, serving as a transcriptional repressor. Its crucial role in the differentiation of cardiomyocytes and the formation of cardiac structures underscores its importance in cardiovascular development.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of Histone-lysine N-methyltransferase SMYD1 holds promise for uncovering novel therapeutic approaches. Given its key role in heart development, targeting this protein could lead to breakthroughs in the treatment of cardiovascular diseases.

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