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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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
Receptor.AI
 
UPACC
Q9NZC9

UPID:
SMAL1_HUMAN

ALTERNATIVE NAMES:
HepA-related protein; Sucrose nonfermenting protein 2-like 1

ALTERNATIVE UPACC:
Q9NZC9; A6NEH0; Q53R00; Q96AY1; Q9NXQ5; Q9UFH3; Q9UI93

BACKGROUND:
The protein SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily A-like protein 1, with alternative names HepA-related protein and Sucrose nonfermenting protein 2-like 1, is pivotal in DNA dynamics. It acts as an ATP-dependent annealing helicase, with a unique ability to rewind stably unwound DNA, playing a key role in the DNA damage response by acting at stalled replication forks.

THERAPEUTIC SIGNIFICANCE:
Given its critical function in DNA repair and its association with Schimke immuno-osseous dysplasia, the study of SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily A-like protein 1 offers promising avenues for therapeutic intervention. Targeting the mechanisms by which this protein influences DNA repair and cellular health could lead to novel treatments for related genetic disorders.

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