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Methionine Functionalized Biocompatible Block Copolymers for Targeted Plasmid DNA Delivery

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PTM-Mamba: a PTM-aware protein language model with bidirectional gated Mamba blocks.

Fred Zhangzhi Peng¹, Chentong Wang², Tong Chen¹

¹Department of Biomedical Engineering, Duke University, Durham, NC, USA.

|April 10, 2025

Summary

We introduce PTM-Mamba, a novel protein language model that incorporates post-translational modifications (PTMs). This advancement enables more accurate modeling of protein diversity, function, and interactions for various applications.

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Area of Science:

Proteomics
Bioinformatics
Computational Biology

Background:

Current protein language models (LMs) excel at encoding protein properties but lack representation of post-translational modifications (PTMs).
PTMs are critical for proteomic diversity, influencing protein structure, function, and interactions.
Existing models do not fully capture the complexity introduced by PTMs.

Purpose of the Study:

To develop a PTM-aware protein language model that integrates PTM information.
To enable accurate modeling of both wild-type and PTM-modified protein sequences.
To establish a foundational tool for PTM-aware protein modeling and design.

Main Methods:

Developed PTM-Mamba, a novel protein LM architecture.
Integrated PTM tokens using bidirectional Mamba blocks.
Fused PTM tokens with ESM-2 protein LM embeddings via a novel gating mechanism.

Main Results:

PTM-Mamba uniquely models wild-type and PTM sequences.
Enabled downstream tasks including disease association and druggability prediction.
Facilitated prediction of PTM effects on protein-protein interactions and zero-shot PTM discovery.

Conclusions:

PTM-Mamba represents a significant advancement in protein language modeling.
The model provides a powerful tool for understanding PTMs' role in protein function.
Established PTM-Mamba as a foundational resource for PTM-aware protein research and design.