Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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.


Our high-tech, dedicated method is applied to construct targeted libraries.


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
Q9HD33

UPID:
RM47_HUMAN

ALTERNATIVE NAMES:
39S ribosomal protein L47, mitochondrial; Nasopharyngeal carcinoma metastasis-related protein 1

ALTERNATIVE UPACC:
Q9HD33; Q6XRG1; Q8N5D1

BACKGROUND:
Large ribosomal subunit protein uL29m, known alternatively as 39S ribosomal protein L47, mitochondrial, and Nasopharyngeal carcinoma metastasis-related protein 1, is integral to mitochondrial ribosomal operations. It facilitates the synthesis of proteins within mitochondria, essential for cellular energy processes and mitochondrial health.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Large ribosomal subunit protein uL29m holds promise for novel therapeutic avenues. Given its central role in mitochondrial protein synthesis, targeting this protein could lead to breakthroughs in treating mitochondrial diseases and improving cellular energy efficiency.

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