AI-ACCELERATED DRUG DISCOVERY

Myelin protein zero-like protein 1

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Myelin protein zero-like protein 1 - 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 Myelin protein zero-like protein 1 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 Myelin protein zero-like protein 1 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 Myelin protein zero-like protein 1, 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 Myelin protein zero-like protein 1. 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 Myelin protein zero-like protein 1. 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 Myelin protein zero-like protein 1 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.

Myelin protein zero-like protein 1

partner:

Reaxense

upacc:

O95297

UPID:

MPZL1_HUMAN

Alternative names:

Protein zero-related

Alternative UPACC:

O95297; B2REB9; B2REC0; Q5R332; Q8IX11; Q9BWZ3; Q9NYK4; Q9UL20

Background:

Myelin protein zero-like protein 1, alternatively known as Protein zero-related, plays a pivotal role in cell surface receptor signaling. It facilitates the recruitment of PTPN11/SHP-2 to the cell membrane and acts as a substrate for PTPN11/SHP-2. This protein is a key receptor for concanavalin-A (ConA), engaging in cellular signaling pathways initiated by ConA, which likely involve Src family tyrosine-protein kinases. Notably, isoform 3 of this protein exerts a dominant negative effect by inhibiting tyrosine phosphorylation of MPZL1 induced by ConA, whereas isoform 1 is implicated in the regulation of integrin-mediated cell motility.

Therapeutic significance:

Understanding the role of Myelin protein zero-like protein 1 could open doors to potential therapeutic strategies.

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