AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Serum amyloid A-1 protein

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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

Reaxense

upacc

P0DJI8

UPID:

SAA1_HUMAN

Alternative names:

-

Alternative UPACC:

P0DJI8; P02735; P02736; P02737; Q16730; Q16834; Q16835; Q16879; Q3KRB3; Q6FG67; Q96QN0; Q9UCK9; Q9UCL0

Background:

Serum amyloid A-1 protein (SAA1) plays a pivotal role as a major acute phase protein in the body's response to stress and injury. Its expression is significantly upregulated in response to inflammation, influencing several biological pathways involved in lipid metabolism, immune response, and tissue repair.

Therapeutic significance:

Understanding the role of Serum amyloid A-1 protein could open doors to potential therapeutic strategies. Its involvement in acute phase responses and regulation of inflammatory processes highlights its potential as a target for developing treatments aimed at modulating immune responses and inflammation.

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