Focused On-demand Library for Tubulin-specific chaperone D

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

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 high-tech, dedicated method is applied to construct 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 stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.







Alternative names:

Beta-tubulin cofactor D; SSD-1; Tubulin-folding cofactor D

Alternative UPACC:

Q9BTW9; O95458; Q7L8K1; Q8IXP6; Q8NAX0; Q8WYH4; Q96E74; Q9UF82; Q9UG46; Q9Y2J3


Tubulin-specific chaperone D, also known as Beta-tubulin cofactor D, plays a pivotal role in the tubulin folding pathway, essential for assembling tubulin complexes. It regulates microtubule dynamics, influencing both polymerization and depolymerization processes. This protein is crucial for the correct assembly and maintenance of the mitotic spindle, ensuring proper mitotic progression. Additionally, it is involved in neuron morphogenesis, highlighting its significance in cellular structure and function.

Therapeutic significance:

Given its involvement in progressive encephalopathy with early-onset brain atrophy and thin corpus callosum, understanding the role of Tubulin-specific chaperone D could open doors to potential therapeutic strategies. Its critical function in neurodevelopment and neurodegeneration points to its potential as a target for treating related neurological disorders.

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