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.


Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.


 

Fig. 1. The screening 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.


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
P80511

UPID:
S10AC_HUMAN

ALTERNATIVE NAMES:
CGRP; Calcium-binding protein in amniotic fluid 1; Calgranulin-C; Extracellular newly identified RAGE-binding protein; Migration inhibitory factor-related protein 6; Neutrophil S100 protein; S100 calcium-binding protein A12

ALTERNATIVE UPACC:
P80511; P83219; Q5SY66; Q7M4R1

BACKGROUND:
S100 calcium-binding protein A12, known for its roles in immune response modulation, acts as an alarmin, stimulating innate immune cells through AGER binding. This interaction activates key signaling pathways, promoting pro-inflammatory cytokine production and cell adhesion molecule up-regulation. Additionally, S100A12 exhibits antimicrobial activities, including antifungal and antibacterial effects, showcasing its versatility in host defense mechanisms.

THERAPEUTIC SIGNIFICANCE:
The exploration of S100 calcium-binding protein A12's functions illuminates its potential in developing new therapeutic approaches. Its capacity to influence immune cell recruitment and inflammatory processes positions it as a valuable target for drug discovery, particularly in treatments aimed at inflammatory and infectious diseases. The protein's broad biological activities underscore its therapeutic relevance.

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