AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Signal recognition particle receptor subunit beta

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive 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

Reaxense

upacc

Q9Y5M8

UPID:

SRPRB_HUMAN

Alternative names:

Protein APMCF1

Alternative UPACC:

Q9Y5M8; Q6P595; Q8N2D8

Background:

Signal recognition particle receptor subunit beta, also known as Protein APMCF1, plays a pivotal role in protein synthesis and cellular function. It is a key component of the signal recognition particle (SRP) complex receptor, ensuring the accurate targeting of nascent secretory proteins to the endoplasmic reticulum membrane system. This process is crucial for maintaining cellular homeostasis and proper protein localization.

Therapeutic significance:

Understanding the role of Signal recognition particle receptor subunit beta could open doors to potential therapeutic strategies. Its critical function in protein targeting and synthesis highlights its potential as a target for developing treatments aimed at correcting protein mislocalization, which is a feature of many diseases.

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