AI-ACCELERATED DRUG DISCOVERY

Tissue alpha-L-fucosidase

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Tissue alpha-L-fucosidase - 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 Tissue alpha-L-fucosidase 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 Tissue alpha-L-fucosidase 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 Tissue alpha-L-fucosidase, 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 Tissue alpha-L-fucosidase. 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 Tissue alpha-L-fucosidase. 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 Tissue alpha-L-fucosidase 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.

Tissue alpha-L-fucosidase

partner:

Reaxense

upacc:

P04066

UPID:

FUCO_HUMAN

Alternative names:

Alpha-L-fucosidase I; Alpha-L-fucoside fucohydrolase 1

Alternative UPACC:

P04066; B2RBG3; Q14334; Q14335; Q3LID0; Q8NAC2

Background:

Tissue alpha-L-fucosidase, also known as Alpha-L-fucosidase I and Alpha-L-fucoside fucohydrolase 1, encoded by the gene with accession number P04066, plays a crucial role in cellular processes. It is responsible for hydrolyzing the alpha-1,6-linked fucose joined to the reducing-end N-acetylglucosamine of the carbohydrate moieties of glycoproteins. This enzymatic activity is vital for the proper degradation and recycling of glycoproteins within cells.

Therapeutic significance:

The dysfunction of Tissue alpha-L-fucosidase is directly linked to Fucosidosis, an autosomal recessive lysosomal storage disease. This condition is marked by the accumulation of fucose-containing glycolipids and glycoproteins, leading to severe symptoms including facial dysmorphism, dysostosis multiplex, moderate hepatomegaly, severe intellectual deficit, and deafness. Understanding the role of Tissue alpha-L-fucosidase could pave the way for innovative therapeutic strategies targeting the molecular basis of Fucosidosis.

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