AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ubiquitin carboxyl-terminal hydrolase CYLD

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 our associate 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.

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

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.

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

Q9NQC7

UPID:

CYLD_HUMAN

Alternative names:

Deubiquitinating enzyme CYLD; Ubiquitin thioesterase CYLD; Ubiquitin-specific-processing protease CYLD

Alternative UPACC:

Q9NQC7; O94934; Q7L3N6; Q96EH0; Q9NZX9

Background:

Ubiquitin carboxyl-terminal hydrolase CYLD, also known as Deubiquitinating enzyme CYLD, plays a crucial role in cellular processes by specifically cleaving 'Lys-63'- and linear 'Met-1'-linked polyubiquitin chains. This action is pivotal in NF-kappa-B activation, TNF-alpha-induced necroptosis, and the regulation of cell survival, proliferation, and differentiation. CYLD's ability to regulate microtubule dynamics underscores its importance in cell proliferation, migration, and angiogenesis.

Therapeutic significance:

CYLD's involvement in diseases such as familial cylindromatosis, multiple familial trichoepithelioma 1, Brooke-Spiegler syndrome, and frontotemporal dementia and/or amyotrophic lateral sclerosis 8 highlights its therapeutic potential. Understanding CYLD's role could open doors to novel therapeutic strategies targeting these conditions.

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