AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Box C/D snoRNA protein 1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

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

Reaxense

upacc

Q9NWK9

UPID:

BCD1_HUMAN

Alternative names:

Serologically defined breast cancer antigen NY-BR-75; Zinc finger HIT domain-containing protein 6

Alternative UPACC:

Q9NWK9; B2RBA1; B4DP13; D3DT20; Q9H278; Q9H3X3; Q9NWN0

Background:

Box C/D snoRNA protein 1, also known as Serologically defined breast cancer antigen NY-BR-75 and Zinc finger HIT domain-containing protein 6, plays a crucial role in the accumulation of box C/D snoRNAs. These snoRNAs are essential for snoRNA processing, transport to the nucleolus, and ribosome biogenesis, highlighting the protein's significance in cellular machinery.

Therapeutic significance:

Understanding the role of Box C/D snoRNA protein 1 could open doors to potential therapeutic strategies. Its involvement in fundamental cellular processes underscores its potential as a target for drug discovery, aiming to modulate ribosome biogenesis and snoRNA processing.

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