Focused On-demand Library for Mixed lineage kinase domain-like protein

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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.


We employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

PARTNER
Receptor.AI
 
UPACC
Q8NB16

UPID:
MLKL_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q8NB16; A6NCE4; Q8N6V0

BACKGROUND:
The Mixed lineage kinase domain-like protein (MLKL) serves as a key component in the necroptosis pathway, a programmed cell death mechanism activated by TNF and certain viral infections. MLKL, a pseudokinase, is activated by RIPK3 phosphorylation, leading to its trimerization and interaction with the plasma membrane, resulting in cell death. Its unique action in the nucleus against orthomyxoviruses, through disruption of the nuclear envelope, underscores its critical function in cellular integrity and immune response.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Mixed lineage kinase domain-like protein could open doors to potential therapeutic strategies.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.


Page 8507 of 8789