AI-ACCELERATED DRUG DISCOVERY

Corrinoid adenosyltransferase MMAB

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Corrinoid adenosyltransferase MMAB - 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 Corrinoid adenosyltransferase MMAB 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 Corrinoid adenosyltransferase MMAB 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 Corrinoid adenosyltransferase MMAB, 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 Corrinoid adenosyltransferase MMAB. 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 Corrinoid adenosyltransferase MMAB. 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 Corrinoid adenosyltransferase MMAB 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.

Corrinoid adenosyltransferase MMAB

partner:

Reaxense

upacc:

Q96EY8

UPID:

MMAB_HUMAN

Alternative names:

ATP:co(I)rrinoid adenosyltransferase MMAB; Methylmalonic aciduria type B protein

Alternative UPACC:

Q96EY8; C5HU05; Q9BSH0

Background:

Corrinoid adenosyltransferase MMAB, also known as ATP:co(I)rrinoid adenosyltransferase and Methylmalonic aciduria type B protein, plays a pivotal role in vitamin B12 metabolism. It converts cob(I)alamin into adenosylcobalamin (AdoCbl), a crucial coenzyme for methylmalonyl-CoA mutase. This process is essential for the final step of vitamin B12 conversion, highlighting the protein's significance in metabolic pathways.

Therapeutic significance:

Given its critical role in the metabolism of methylmalonate and cobalamin, MMAB is directly linked to Methylmalonic aciduria type cblB, a metabolic disorder. Understanding the function of Corrinoid adenosyltransferase MMAB could open doors to potential therapeutic strategies for treating this condition by targeting the underlying genetic variants.

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