Focused On-demand Library for Tubulin alpha-3C chain

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 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 for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

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.







Alternative names:

Alpha-tubulin 2; Alpha-tubulin 3C; Tubulin alpha-2 chain

Alternative UPACC:

P0DPH7; A6NJQ0; Q13748; Q5W099; Q6PEY3; Q96F18


Tubulin alpha-3C chain, also known as Alpha-tubulin 2, Alpha-tubulin 3C, and Tubulin alpha-2 chain, plays a pivotal role in cell structure and function. It is a major component of microtubules, cylindrical structures essential for cell shape, intracellular transport, and cell division. Microtubules are dynamic entities that grow by adding GTP-tubulin dimers, with alpha-tubulin's GTPase activity crucial for this process.

Therapeutic significance:

Understanding the role of Tubulin alpha-3C chain could open doors to potential therapeutic strategies. Its fundamental involvement in cell division and transport makes it a potential target for cancer therapy, where controlling cell proliferation is crucial.

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