Focused On-demand Libraries - Receptor.AI 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.


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 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 enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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
P05067

UPID:
A4_HUMAN

ALTERNATIVE NAMES:
ABPP; APPI; Alzheimer disease amyloid A4 protein homolog; Alzheimer disease amyloid protein; Amyloid precursor protein; Amyloid-beta (A4) precursor protein; Amyloid-beta A4 protein; Cerebral vascular amyloid peptide; PreA4; Protease nexin-II

ALTERNATIVE UPACC:
P05067; B2R5V1; B4DII8; D3DSD1; D3DSD2; D3DSD3; P09000; P78438; Q13764; Q13778; Q13793; Q16011; Q16014; Q16019; Q16020; Q6GSC0; Q8WZ99; Q9BT38; Q9UC33; Q9UCA9; Q9UCB6; Q9UCC8; Q9UCD1; Q9UQ58

BACKGROUND:
The Amyloid-beta precursor protein (APP) functions as a key player in neuron development and repair, mediating critical processes such as cell adhesion, neurite outgrowth, and synaptic formation. APP's interaction with various extracellular matrix components and its role in copper homeostasis underscore its importance in maintaining neuronal health and function.

THERAPEUTIC SIGNIFICANCE:
Given APP's crucial role in the pathogenesis of Alzheimer's disease and its related cerebral amyloid angiopathy, targeting APP and its metabolic pathways offers a promising avenue for developing treatments for these debilitating conditions. Exploring APP's functions and interactions could unlock new therapeutic potentials in neurodegenerative disease management.

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