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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We use our state-of-the-art dedicated workflow for designing focused 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 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
Q4FZB7

UPID:
KMT5B_HUMAN

ALTERNATIVE NAMES:
Lysine N-methyltransferase 5B; Lysine-specific methyltransferase 5B; Suppressor of variegation 4-20 homolog 1; [histone H4]-N-methyl-L-lysine20 N-methyltransferase KMT5B; [histone H4]-lysine20 N-methyltransferase KMT5B

ALTERNATIVE UPACC:
Q4FZB7; A0A0A0MT19; B7WNX7; Q3SX56; Q4V775; Q6P150; Q96E44; Q9BUL0; Q9H022; Q9H2K3; Q9NXV3; Q9Y393

BACKGROUND:
The protein Histone-lysine N-methyltransferase KMT5B, with alternative names such as Suppressor of variegation 4-20 homolog 1, is a key enzyme in histone modification. It catalyzes the methylation of histone H4 at Lys-20, a modification associated with transcriptional repression and genome stability. KMT5B interacts with RB1 family proteins to target histone H3, playing a significant role in cell cycle regulation, myogenesis, and DNA damage response.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in Intellectual developmental disorder, autosomal dominant 51, KMT5B represents a potential target for therapeutic intervention. Understanding the role of KMT5B could open doors to potential therapeutic strategies for intellectual developmental disorders and improving genome stability.

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