Focused On-demand Library for Amyloid-beta precursor protein

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.

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 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.

Key features that set our library apart include:

The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

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:

Amyloid-beta precursor protein (APP) is a cell surface receptor with a pivotal role in neuronal functions, including neurite growth, neuronal adhesion, and axonogenesis. It is involved in various physiological processes on neuron surfaces and plays a crucial role in synaptogenesis. APP undergoes proteolytic processing, leading to the production of neurotoxic amyloid-beta peptides, which are central to the pathogenesis of Alzheimer's disease.

Therapeutic significance:

The involvement of APP in Alzheimer's disease and cerebral amyloid angiopathy highlights its significance in neurodegenerative disorders. Understanding the multifaceted role of APP in these conditions could pave the way for innovative therapeutic strategies targeting amyloid-beta peptides' production, aggregation, and neurotoxic effects.