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 pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


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.


We utilise our cutting-edge, exclusive workflow to develop 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 stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q86Y97

UPID:
KMT5C_HUMAN

ALTERNATIVE NAMES:
Lysine N-methyltransferase 5C; Lysine-specific methyltransferase 5C; Suppressor of variegation 4-20 homolog 2; [histone H4]-N-methyl-L-lysine20 N-methyltransferase KMT5B; [histone H4]-lysine20 N-methyltransferase KMT5B

ALTERNATIVE UPACC:
Q86Y97; Q8WZ10; Q9BRZ6

BACKGROUND:
The enzyme KMT5C, with alternative names such as Suppressor of variegation 4-20 homolog 2, is a key player in the epigenetic regulation mechanism, specifically through the methylation of 'Lys-20' on histone H4. This action facilitates the transition of monomethylated and dimethylated 'Lys-20' to higher methylation states, crucial for gene silencing and chromatin structure maintenance. KMT5C's interaction with RB1 family proteins and its role in DNA damage response underscore its importance in cellular processes related to genome stability and repair.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of KMT5C could open doors to potential therapeutic strategies.

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