Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.


 

Fig. 1. The screening 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.


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
Receptor.AI
 
UPACC
O96019

UPID:
ACL6A_HUMAN

ALTERNATIVE NAMES:
53 kDa BRG1-associated factor A; Actin-related protein Baf53a; ArpNbeta; BRG1-associated factor 53A; INO80 complex subunit K

ALTERNATIVE UPACC:
O96019; B3KMN1; D3DNR9; Q8TAE5; Q9BVS8; Q9H0W6

BACKGROUND:
Actin-like protein 6A, identified by alternative names such as ArpNbeta and BRG1-associated factor 53A, is integral to the NuA4 histone acetyltransferase complex, involved in transcriptional activation of select genes. This protein's modification of nucleosomal histones plays a role in DNA repair and may influence oncogene and proto-oncogene mediated growth, pointing to its broad impact on cellular processes.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Actin-like protein 6A offers promising avenues for developing novel therapeutic approaches.

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