AI-ACCELERATED DRUG DISCOVERY

Probable tubulin polyglutamylase TTLL2

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Probable tubulin polyglutamylase TTLL2 - Focused Library Design

Available from Reaxense

This protein is integrated into the Receptor.AI ecosystem as a prospective target with high therapeutic potential. We performed a comprehensive characterization of Probable tubulin polyglutamylase TTLL2 including:

1. LLM-powered literature research

Our custom-tailored LLM extracted and formalized all relevant information about the protein from a large set of structured and unstructured data sources and stored it in the form of a Knowledge Graph. This comprehensive analysis allowed us to gain insight into Probable tubulin polyglutamylase TTLL2 therapeutic significance, existing small molecule ligands, relevant off-targets, and protein-protein interactions.

 Fig. 1. Preliminary target research workflow

2. AI-Driven Conformational Ensemble Generation

Starting from the initial protein structure, we employed advanced AI algorithms to predict alternative functional states of Probable tubulin polyglutamylase TTLL2, including large-scale conformational changes along "soft" collective coordinates. Through molecular simulations with AI-enhanced sampling and trajectory clustering, we explored the broad conformational space of the protein and identified its representative structures. Utilizing diffusion-based AI models and active learning AutoML, we generated a statistically robust ensemble of equilibrium protein conformations that capture the receptor's full dynamic behavior, providing a robust foundation for accurate structure-based drug design.

 Fig. 2. AI-powered molecular dynamics simulations workflow

3. Binding pockets identification and characterization

We employed the AI-based pocket prediction module to discover orthosteric, allosteric, hidden, and cryptic binding pockets on the protein’s surface. Our technique integrates the LLM-driven literature search and structure-aware ensemble-based pocket detection algorithm that utilizes previously established protein dynamics. Tentative pockets are then subject to AI scoring and ranking with simultaneous detection of false positives. In the final step, the AI model assesses the druggability of each pocket enabling a comprehensive selection of the most promising pockets for further targeting.

 Fig. 3. AI-based binding pocket detection workflow

4. AI-Powered Virtual Screening

Our ecosystem is equipped to perform AI-driven virtual screening on Probable tubulin polyglutamylase TTLL2. With access to a vast chemical space and cutting-edge AI docking algorithms, we can rapidly and reliably predict the most promising, novel, diverse, potent, and safe small molecule ligands of Probable tubulin polyglutamylase TTLL2. This approach allows us to achieve an excellent hit rate and to identify compounds ready for advanced lead discovery and optimization.

 Fig. 4. The screening workflow of Receptor.AI

Receptor.AI, in partnership with Reaxense, developed a next-generation technology for on-demand focused library design to enable extensive target exploration.

The focused library for Probable tubulin polyglutamylase TTLL2 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.

Probable tubulin polyglutamylase TTLL2

partner:

Reaxense

upacc:

Q9BWV7

UPID:

TTLL2_HUMAN

Alternative names:

Testis-specific protein NYD-TSPG; Tubulin--tyrosine ligase-like protein 2

Alternative UPACC:

Q9BWV7; B2RB11; B3KS77; Q7Z6R8; Q86X22

Background:

Probable tubulin polyglutamylase TTLL2, also known as Testis-specific protein NYD-TSPG and Tubulin--tyrosine ligase-like protein 2, is implicated in the modification of tubulin through the addition of glutamate side chains. This process, known as polyglutamylation, is crucial for the functional diversity of tubulin in cellular processes. TTLL2's activity is suggested to be essential in the initiation step of polyglutamylation, indicating a specialized role in this post-translational modification.

Therapeutic significance:

Understanding the role of Probable tubulin polyglutamylase TTLL2 could open doors to potential therapeutic strategies.

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