AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Tripartite motif-containing protein 49D

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

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

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.

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

C9J1S8

UPID:

TR49D_HUMAN

Alternative names:

Tripartite motif-containing protein 49-like protein; Tripartite motif-containing protein 49D1; Tripartite motif-containing protein 49D2

Alternative UPACC:

C9J1S8; I1YAP9

Background:

The Tripartite motif-containing protein 49D, with alternative names such as Tripartite motif-containing protein 49-like protein, Tripartite motif-containing protein 49D1, and Tripartite motif-containing protein 49D2, represents a significant area of interest in protein research. Its unique structure and naming suggest a complex role in cellular mechanisms, although the specific functions remain to be fully elucidated.

Therapeutic significance:

Understanding the role of Tripartite motif-containing protein 49D could open doors to potential therapeutic strategies. Its multifaceted role in biological systems makes it an intriguing subject for scientific inquiry, promising advancements in medical treatments.

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