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 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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of 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
P55769

UPID:
NH2L1_HUMAN

ALTERNATIVE NAMES:
High mobility group-like nuclear protein 2 homolog 1; OTK27; SNU13 homolog; U4/U6.U5 small nuclear ribonucleoprotein SNU13; U4/U6.U5 tri-snRNP 15.5 kDa protein

ALTERNATIVE UPACC:
P55769

BACKGROUND:
The NHP2-like protein 1, with alternative names such as SNU13 homolog and U4/U6.U5 tri-snRNP 15.5 kDa protein, is integral to the nucleolus-based assembly of the SSU processome, impacting the generation of the small eukaryotic ribosomal subunit. It engages in targeted degradation of pre-ribosomal RNA by the RNA exosome and is involved in pre-mRNA splicing, showcasing a conformational change upon RNA-binding.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of NHP2-like protein 1 holds promise for unveiling novel therapeutic avenues.

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