AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Triggering receptor expressed on myeloid cells 1

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.

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

This includes comprehensive molecular simulations of the receptor in its native membrane environment, paired with ensemble virtual screening that factors in its conformational mobility. In cases involving dimeric or oligomeric receptors, the entire functional complex is modelled, pinpointing potential binding pockets on and between the subunits to capture the full range of mechanisms of action.

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

Q9NP99

UPID:

TREM1_HUMAN

Alternative names:

Triggering receptor expressed on monocytes 1

Alternative UPACC:

Q9NP99; B4DWG2; K7EJW1; Q53FL8; Q5T2C9; Q86YU1

Background:

Triggering receptor expressed on myeloid cells 1 (TREM1) is a pivotal protein in innate and adaptive immunity, enhancing inflammatory responses upon activation by ligands like PGLYRP1, HMGB1, or HSP70. It forms a complex with TYROBP/DAP12, initiating a SYK-mediated phosphorylation cascade, activating BTK, MAPK1, MAPK3, and phospholipase C-gamma. This cascade facilitates the release of pro-inflammatory cytokines and chemokines, crucial for neutrophil and macrophage function in response to bacterial and fungal infections.

Therapeutic significance:

Understanding the role of Triggering receptor expressed on myeloid cells 1 could open doors to potential therapeutic strategies, especially in managing acute and chronic inflammatory diseases such as septic shock and atherosclerosis.

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