Modeling ensembles of transmembrane beta-barrel proteins

Area of Science:

• Biochemistry and structural biology
• Computational biology and bioinformatics

Background:

• Transmembrane beta-barrel (TMB) proteins are crucial components of outer membranes in various organisms.
• Determining TMB structures via X-ray diffraction is challenging due to experimental difficulties in protein crystallization.

Purpose of the Study:

• To introduce partiFold, a novel computational program for investigating the folding landscape of TMB proteins.
• To enhance the prediction of TMB structures and understand their folding mechanisms.

Main Methods:

• PartiFold computes the Boltzmann partition function to estimate inter-beta-strand residue interaction probabilities.
• It utilizes a grammatical model for beta-barrel structures and a novel energy function based on amino acid pair potentials.
• The program predicts contacts, per-residue B-values, and samples conformations from the low-energy ensemble.

Main Results:

• PartiFold demonstrates superior accuracy and consistency in predicting inter-beta-strand residue contacts compared to existing programs.
• Its predictions for B-values are competitive with specialized methods.
• Sampling TMBs from the Boltzmann ensemble using partiFold yields better structural matches than single-structure prediction methods.

Conclusions:

• PartiFold provides a comprehensive approach to modeling TMB folding landscapes, offering insights unattainable by other methods.
• The tool enhances the prediction of TMB structures, aiding in understanding their biological roles.
• A webserver for partiFold is publicly available for research use.