PTM-Mamba: A PTM-Aware Protein Language Model with Bidirectional Gated Mamba Blocks

Current protein language models (pLMs) accurately encode protein properties but have yet to represent post-translational modifications (PTMs), which are critical for proteomic diversity and influence protein structure, function, and interactions. To address this gap, we develop PTM-Mamba, a PTM-aware pLM that integrates PTM tokens using bidirectional Mamba blocks fused with ESM-2 pLM embeddings via a novel gating mechanism. PTM-Mamba uniquely models both wild-type and PTM sequences, enabling downstream tasks such as disease association and druggability prediction, PTM effect prediction on protein-protein interactions, and zero-shot PTM discovery. In total, our work establishes PTM-Mamba as a foundational tool for PTM-aware protein modeling and design.