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 use our state-of-the-art dedicated workflow for designing 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.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
P61247

UPID:
RS3A_HUMAN

ALTERNATIVE NAMES:
40S ribosomal protein S3a; v-fos transformation effector protein

ALTERNATIVE UPACC:
P61247; B2R4D4; D3DP05; P33443; P49241

BACKGROUND:
The protein Small ribosomal subunit protein eS1, with alternative names 40S ribosomal protein S3a and v-fos transformation effector protein, is a key player in the ribosome, the cell's protein factory (PubMed:23636399). It is part of the SSU processome that contributes to the nascent pre-rRNA's processing, ensuring the proper assembly of the ribosomal subunits (PubMed:34516797). Additionally, its potential role in erythropoiesis via DDIT3 regulation highlights its importance in cellular processes.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Small ribosomal subunit protein eS1 holds promise for uncovering novel therapeutic avenues.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.