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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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 screening 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
Receptor.AI
 
UPACC
Q99613

UPID:
EIF3C_HUMAN

ALTERNATIVE NAMES:
Eukaryotic translation initiation factor 3 subunit 8; eIF3 p110

ALTERNATIVE UPACC:
Q99613; A8K7Z0; B2RXG3; B4E1D5; H3BRV0; O00215; Q9BW98

BACKGROUND:
The Eukaryotic translation initiation factor 3 subunit C, known alternatively as eIF3 p110, is integral to the eIF-3 complex, crucial for protein synthesis initiation. It aids in the recruitment of eIF-1, eIF-1A, eIF-2:GTP:methionyl-tRNAi, and eIF-5, forming the 43S pre-initiation complex. This complex is vital for mRNA scanning and AUG recognition, playing a key role in cell cycle regulation, differentiation, and apoptosis through specific mRNA translation.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Eukaryotic translation initiation factor 3 subunit C could open doors to potential therapeutic strategies.

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