tmhop

tmhop applies a lipophilicity-based energy function to model and design membrane proteins by integrating protein-membrane and intra-protein interactions for structure prediction and sequence optimization.

Key Features:

• Lipophilicity-Based Energy Function: Employs an energy function that incorporates lipophilicity profiles tailored to the solvation constraints of the plasma membrane.
• Integration with Rosetta: Expresses inferred insertion energies as lipophilicity terms within the Rosetta framework.
• dsTβL Experimental Data: Uses insertion energies from the high-throughput dsTβL screen for amino acids at positions across the bacterial plasma membrane.
• Integration of Protein-Membrane and Intra-Protein Interactions: Combines intra-protein contacts with protein-membrane interaction terms in modeling and design calculations.
• Improved Modeling Accuracy: Demonstrated recapitulation of two-thirds of experimentally determined membrane-spanning homo-oligomer structures with RMSD < 2.5Å within the top five predicted models.
• Enhanced Sequence Design: Improves discrimination of stabilizing point mutations and replicates natural membrane-protein sequences with known structures.

Scientific Applications:

• Membrane-Protein Modeling: Predicts three-dimensional structures of membrane proteins by accounting for membrane-specific energetic contributions.
• Protein Design: Optimizes sequences of membrane-integral proteins to favor stable, membrane-compatible conformations.
• Biological Research: Provides experimentally grounded insights into protein-membrane interactions relevant to studies such as drug-target characterization.

Methodology:

Implements a lipophilicity-based energy function derived from dsTβL insertion energies, expresses insertion energies as lipophilicity terms within Rosetta, integrates intra-protein contacts with protein-membrane interactions, and was benchmarked on membrane-spanning homo-oligomers and sequence-design tests measuring RMSD and discrimination of stabilizing point mutations.