Lei Wang

PepMCP predicts membrane contact probability for short peptides using graph-based modeling, achieving high correlation with experimental data.

This paper introduces improved Anisotropic Network Models that incorporate Membrane Contact Probability to better predict membrane protein dynamics and mechanosensitivity, aligning with experimental findings.

This study screens antimicrobial peptides using a mechanism-driven approach, identifying seven peptides with membrane-targeting and pore-forming activity that show antimicrobial efficacy with low cytotoxicity.

The paper introduces ProtRAP-LM, a transformer-based model using language model embeddings to predict membrane contact probability and relative accessibility of proteins, achieving faster and more accurate results than MSA-based methods.