A5032401858- RNA and protein synthesis mechanisms
- Lipid Membrane Structure and Behavior
- Protein Structure and Dynamics
- Advanced biosensing and bioanalysis techniques
- Machine Learning in Bioinformatics
- Receptor Mechanisms and Signaling
Leiden University
2022-2024
Proteins can specifically bind to curved membranes through curvature-induced hydrophobic lipid packing defects. The chemical diversity among such curvature “sensors” challenges our understanding of how they differ from general membrane “binders” that without selectivity. Here, we combine an evolutionary algorithm with coarse-grained molecular dynamics simulations (Evo-MD) resolve the peptide sequences optimally recognize membranes. We subsequently demonstrate a synergy between Evo-MD and...
Many membrane peripheral proteins have evolved to transiently interact with the surface of (curved) lipid bilayers. Currently, methods quantitatively predict sensing and binding free energies for protein sequences or structures are lacking, such tools could greatly benefit discovery membrane-interacting motifs, as well their de novo design.
Abstract Motivation Many membrane peripheral proteins have evolved to transiently interact with the surface of (curved) lipid bilayers. Currently, methods quantitatively predict sensing and binding free energies for protein sequences or structures are lacking, such tools could greatly benefit discovery membrane-interacting motifs, as well their de novo design. Results Here, we trained a transformer neural network model on molecular dynamics data > 50,000 peptides that is able accurately...
The occurrence of linear cholesterol-recognition motifs in alpha-helical transmembrane domains has long been debated. Here, we demonstrate the ability a genetic algorithm guided by coarse-grained molecular dynamics simulations—a method coined evolutionary (Evo-MD)—to directly resolve sequence which maximally attracts cholesterol for single-pass (TMDs). We illustrate that landscape attraction membrane proteins is characterized sharp, well-defined global optimum. Surprisingly, this optimal...
Abstract Proteins can specifically bind to curved membranes through curvature-induced hydrophobic lipid packing defects. The chemical diversity among such curvature ‘sensors’ challenges our understanding of how they differ from general membrane ‘binders’, that without selectivity. Here, we combine an evolutionary algorithm with coarse-grained molecular dynamics simulations (Evo-MD) resolve the peptide sequences optimally recognize membranes. We subsequently demonstrate a synergy between...