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Updated: May 17, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

MP-T: improving membrane protein alignment for structure prediction.

Jamie R Hill¹, Charlotte M Deane

¹Department of Statistics, University of Oxford, Oxford, OX1 3TG, UK.

Bioinformatics (Oxford, England)

|November 1, 2012

Summary

This summary is machine-generated.

Membrane Protein Threader (MP-T) improves sequence-structure alignments for membrane proteins, leading to more accurate protein models. This new tool enhances structural modeling by considering membrane-specific factors.

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Last Updated: May 17, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction

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Published on: November 3, 2011

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

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Published on: July 8, 2025

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Area of Science:

Structural Biology
Computational Biology
Biophysics

Background:

Crystal structures of clinically relevant membrane proteins are scarce.
Existing modeling methods rely on sequence-structure alignments often generated by tools optimized for soluble proteins.
Membrane protein modeling is challenged by the unique hydrophobic environment and distinct amino acid preferences within biological membranes.

Purpose of the Study:

To develop an improved sequence-structure alignment method specifically for membrane proteins.
To enhance the accuracy of membrane protein structural models by incorporating membrane-specific biophysical properties.
To provide a more reliable blueprint for building models of membrane proteins.

Main Methods:

Developed Membrane Protein Threader (MP-T), a novel sequence-structure alignment tool.
MP-T utilizes multiple sequence alignment and incorporates factors specific to biological membranes, such as hydrophobicity and amino acid substitution preferences.
Evaluated alignment accuracy against seven other methods using 165 non-redundant membrane protein alignments.

Main Results:

MP-T generated significantly more accurate alignments compared to all tested methods, with improvements in δF(M) ranging from +0.9 to +5.5%.
Alignments produced by MP-T resulted in substantially better membrane protein models.
One-fourth of the models built using MP-T alignments showed a GDT_TS score increase of ≥4% compared to models from the best alternative alignment tool.

Conclusions:

MP-T represents a significant advancement in sequence-structure alignment for membrane proteins.
The tool's ability to account for membrane-specific characteristics leads to improved accuracy in protein modeling.
Enhanced membrane protein models can be generated using MP-T, aiding further research into these critical biological molecules.