AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for S-arrestin

Available from Reaxense
Predicted by Alphafold

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.

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.

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

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

P10523

UPID:

ARRS_HUMAN

Alternative names:

48 kDa protein; Retinal S-antigen; Rod photoreceptor arrestin

Alternative UPACC:

P10523; A0FDN6; Q53SV3; Q99858

Background:

S-arrestin, also known as 48 kDa protein, Retinal S-antigen, and Rod photoreceptor arrestin, plays a crucial role in the visual process. It binds to photoactivated, phosphorylated RHO, terminating RHO signaling via G-proteins by competing with G-proteins for the same binding site on RHO. This action is essential in preventing light-dependent degeneration of retinal photoreceptor cells.

Therapeutic significance:

S-arrestin is implicated in several retinal disorders, including Night blindness, congenital stationary, Oguchi type 1, and Retinitis pigmentosa (RP) types 47 and 96. These conditions highlight the protein's critical role in visual impairment diseases, making it a potential target for therapeutic intervention to restore vision or slow the progression of these disorders.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.