AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Large ribosomal subunit protein bL32m

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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.

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

Reaxense

upacc

Q9BYC8

UPID:

RM32_HUMAN

Alternative names:

39S ribosomal protein L32, mitochondrial

Alternative UPACC:

Q9BYC8; Q96Q68; Q9P098

Background:

The Large ribosomal subunit protein bL32m, also known as 39S ribosomal protein L32, mitochondrial, plays a crucial role in protein synthesis within mitochondria. Its involvement in the mitochondrial ribosome suggests a fundamental contribution to mitochondrial biogenesis and function, essential for cellular energy production.

Therapeutic significance:

Understanding the role of Large ribosomal subunit protein bL32m could open doors to potential therapeutic strategies. Its pivotal function in mitochondrial protein synthesis positions it as a key target for interventions aimed at mitochondrial diseases and disorders related to energy metabolism.

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