AI-ACCELERATED DRUG DISCOVERY

E3 ubiquitin-protein ligase MIB2

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

E3 ubiquitin-protein ligase MIB2 - 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 E3 ubiquitin-protein ligase MIB2 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 E3 ubiquitin-protein ligase MIB2 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 E3 ubiquitin-protein ligase MIB2, 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 E3 ubiquitin-protein ligase MIB2. 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 E3 ubiquitin-protein ligase MIB2. 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 E3 ubiquitin-protein ligase MIB2 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.

E3 ubiquitin-protein ligase MIB2

partner:

Reaxense

upacc:

Q96AX9

UPID:

MIB2_HUMAN

Alternative names:

Mind bomb homolog 2; Novel zinc finger protein; Putative NF-kappa-B-activating protein 002N; RING-type E3 ubiquitin transferase MIB2; Skeletrophin; Zinc finger ZZ type with ankyrin repeat domain protein 1

Alternative UPACC:

Q96AX9; A2AGM5; A2AGM6; B3KV93; B3KVF4; B3KXY1; B4DZ57; E9PGU1; E9PHQ1; F8WA73; J3KNZ7; Q7Z437; Q8IY62; Q8N786; Q8N897; Q8N8R2; Q8N911; Q8NB36; Q8NCY1; Q8NG59; Q8NG60; Q8NG61; Q8NI59; Q8WYN1

Background:

E3 ubiquitin-protein ligase MIB2, known for its pivotal role in mediating ubiquitination of Delta receptors, is crucial in the Notch signaling pathway. This protein, also recognized by alternative names such as Mind bomb homolog 2 and Zinc finger ZZ type with ankyrin repeat domain protein 1, facilitates the endocytosis of Delta receptors by ubiquitinating their intracellular domain, thereby positively regulating Delta-mediated Notch signaling.

Therapeutic significance:

Understanding the role of E3 ubiquitin-protein ligase MIB2 could open doors to potential therapeutic strategies. Its involvement in the Notch signaling pathway, a key player in cell differentiation and proliferation, suggests its potential as a target in therapeutic interventions aimed at modulating these processes.

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