AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Receptor-interacting serine/threonine-protein kinase 3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 our partner Reaxense.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

 Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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

Q9Y572

UPID:

RIPK3_HUMAN

Alternative names:

RIP-like protein kinase 3; Receptor-interacting protein 3

Alternative UPACC:

Q9Y572; B4DJL9; C4AM87; Q5J795; Q5J796; Q6P5Y1

Background:

Receptor-interacting serine/threonine-protein kinase 3 (RIPK3) is a pivotal enzyme in mediating necroptosis and apoptosis, key pathways for programmed cell death. It activates through phosphorylation of MLKL in response to TNF-alpha, leading to necrosis. Additionally, RIPK3's role extends to apoptosis regulation, independent of its kinase activity, and involves RIPK1, FADD, and CASP8. Its interaction with viral infections, such as Zika virus and herpes simplex virus 1, showcases its versatility in cellular defense mechanisms, either by promoting cell death or by altering cellular metabolism to restrict viral replication.

Therapeutic significance:

Understanding the role of Receptor-interacting serine/threonine-protein kinase 3 could open doors to potential therapeutic strategies.

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