AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for TBC1 domain family member 7

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.

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

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We employ our advanced, specialised process to create targeted 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.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q9P0N9

UPID:

TBCD7_HUMAN

Alternative names:

Cell migration-inducing protein 23

Alternative UPACC:

Q9P0N9; E7EV96; Q2TU37; Q53F44; Q5SZL7; Q86VM8; Q96MB8

Background:

TBC1 domain family member 7 (TBC1D7) is a pivotal component of the TSC-TBC complex, alongside TSC1-TSC2, with a crucial role in regulating the mTORC1 signaling cascade. This complex exhibits GTPase-activating protein (GAP) activity towards RHEB, a direct activator of mTORC1, thereby acting as a negative regulator in response to cellular growth conditions. TBC1D7's involvement in sensing growth factors and glucose highlights its integral role in cellular metabolism and growth regulation.

Therapeutic significance:

TBC1D7's association with Macrocephaly/megalencephaly syndrome, an autosomal recessive disorder, underscores its clinical relevance. Understanding the role of TBC1D7 could open doors to potential therapeutic strategies for treating this syndrome, which is characterized by abnormal brain enlargement, intellectual disability, and skeletal muscle underdevelopment.

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