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Interfaces Between Alpha-helical Integral Membrane Proteins: Characterization, Prediction, and Docking.

Bian Li¹, Jeffrey Mendenhall¹, Jens Meiler¹

¹Department of Chemistry and Center for Structural Biology, Vanderbilt University, Nashville, TN 37232, USA.

Computational and Structural Biotechnology Journal

|July 16, 2019

Summary

This summary is machine-generated.

This study reveals that integral membrane protein (IMP) interfaces are highly conserved, unlike globular proteins. A new neural network method accurately predicts these interfaces and aids in reconstructing IMP dimer structures.

Keywords:

AUC, Area under the ROC curve IMP, Integral membrane protein MAE, Mean absolute error MSA, Multiple sequence alignment Membrane protein docking Membrane protein interfaces Neural networks OPM, Orientations of proteins in membranes PCC, Pearson correlation coefficient PDB, Protein data bank PPI, Protein-protein interaction PPM, Positioning of proteins in membrane.PPV, Positive predictive value PSSM, Position-specific scoring matrix RMSD, Root-mean-square distance ROC, Receiver operating characteristic curve RSA, Relative solvent accessibility TNR, True negative rate TPR, True positive rate WCN, Weighted contact number Weighted contact numbers

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A Protocol for Computer-Based Protein Structure and Function Prediction

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Published on: November 3, 2011

Area of Science:

Structural biology
Computational biology
Biophysics

Background:

Protein-protein interactions (PPIs) are crucial for protein function, with well-studied characteristics for globular proteins.
Understanding interactions between integral membrane proteins (IMPs) is limited, hindering structural modeling.
Limited computational tools exist for analyzing IMP interfaces and complexes.

Purpose of the Study:

To analyze the molecular features of interfaces in alpha-helical IMP complexes.
To develop a computational method for predicting IMP interface residues and contact numbers.
To utilize predicted interface data for reconstructing IMP dimer structures.

Main Methods:

Analysis of high-resolution structures of non-redundant alpha-helical IMP complexes.
Development of a neural network for predicting interface residues and weighted contact numbers (WCNs).
Application of predicted interface residues and WCNs as restraints in protein docking simulations.

Main Results:

IMP interfaces show higher residue conservation compared to non-interface regions.
The neural network achieved an AUC of 0.75 and PCC of 0.70 for predicting interface residues and WCNs.
Successful reconstruction of 14 out of 16 IMP dimer complexes using predicted restraints, with RMSD100 < 2.5 Å for 14 cases.

Conclusions:

Structural analysis provides molecular insights into alpha-helical IMP interfaces.
Predicted interface residues and WCNs are effective restraints for scoring IMP docking candidates.
The developed method facilitates structural modeling of IMP complexes.