Focused On-demand Library for Atlastin-2

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.

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 employ our advanced, specialised process to create targeted libraries for enzymes.

Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Our library distinguishes itself through several key aspects:

The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q8NHH9

UPID:

ATLA2_HUMAN

Alternative names:

ADP-ribosylation factor-like protein 6-interacting protein 2

Alternative UPACC:

Q8NHH9; B7Z1X2; B7Z7X8; Q4ZG30; Q7Z630; Q8NHH8; Q9H5M7

Background:

Atlastin-2, also known as ADP-ribosylation factor-like protein 6-interacting protein 2, plays a crucial role in the formation of the endoplasmic reticulum's tubular network. It achieves this through GTPase tethering membranes, forming trans-homooligomers, and mediating homotypic fusion of endoplasmic reticulum membranes. This process is vital for maintaining the structural integrity and function of the endoplasmic reticulum.

Therapeutic significance:

Understanding the role of Atlastin-2 could open doors to potential therapeutic strategies. Its pivotal function in endoplasmic reticulum biogenesis suggests that modulation of its activity could have implications for diseases related to endoplasmic reticulum dysfunction.