AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Nonsense-mediated mRNA decay factor SMG9

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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate 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.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening 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 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

Q9H0W8

UPID:

SMG9_HUMAN

Alternative names:

-

Alternative UPACC:

Q9H0W8; O60429; Q9H9A9

Background:

Nonsense-mediated mRNA decay factor SMG9 plays a crucial role in the cellular mechanism known as nonsense-mediated decay (NMD), targeting mRNAs with premature stop codons for degradation. This process is vital for maintaining the integrity of genetic information by preventing the translation of potentially harmful truncated proteins. SMG9, as part of the SMG1C protein kinase complex, is essential for the recruitment of release factors to stalled ribosomes, facilitating the efficient association between SMG1 and SMG8.

Therapeutic significance:

Understanding the role of Nonsense-mediated mRNA decay factor SMG9 could open doors to potential therapeutic strategies. Its involvement in heart and brain malformation syndrome, characterized by multiple congenital anomalies, and a neurodevelopmental disorder with intention tremor and dyspraxia, highlights its significance in human health. Targeting SMG9 or its pathway could offer new avenues for treating these complex disorders.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.