Focused On-demand Library for Large ribosomal subunit protein mL65

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.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal 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 sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

Our library is unique due to several crucial aspects:

Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q9NP92

UPID:

RT30_HUMAN

Alternative names:

39S ribosomal protein S30, mitochondrial; Large ribosomal subunit protein mS30; Programmed cell death protein 9

Alternative UPACC:

Q9NP92; Q96I91; Q96Q19; Q9H0P8; Q9NSF9; Q9NZ76

Background:

The Large ribosomal subunit protein mL65, also known as 39S ribosomal protein S30, mitochondrial, and Programmed cell death protein 9, plays a crucial role in mitochondrial function and apoptosis. Its involvement in the mitochondrial ribosome suggests a key role in protein synthesis within mitochondria, essential for cellular energy production and regulation of cell death pathways.

Therapeutic significance:

Understanding the role of Large ribosomal subunit protein mL65 could open doors to potential therapeutic strategies. Its pivotal role in mitochondrial function and apoptosis pathways makes it a promising target for drug discovery efforts aimed at treating mitochondrial disorders and diseases characterized by dysregulated apoptosis.