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Introduction to Membrane Proteins

Introduction to Membrane Proteins

The cell membrane, or plasma membrane, is an ever-changing landscape. It is described as a fluid mosaic where various macromolecules are embedded in the phospholipid bilayer. Among the macromolecules are proteins. The protein content varies across cell types. For example, mitochondrial inner membranes contain ~76% protein content, while myelin contains ~18% protein content. Individual cells contain many types of membrane proteins—red blood cells contain over 50—and different cell types have...

Single-pass Transmembrane Proteins

Single-pass Transmembrane Proteins

Integral membrane proteins are tightly associated with the cell membrane and play a crucial role in cell communication, signaling, adhesion, and transport of the molecules. Some integral membrane proteins are present only in the membrane monolayer. For example, the enzyme fatty acid amide hydrolase is present in the cytoplasmic side of the membrane monolayer. In contrast, another type of integral membrane protein, also known as a transmembrane protein, spans across the membrane. Transmembrane...

Membrane Proteins

Membrane Proteins

Plasma membranes have integral transmembrane proteins involved in facilitated transport. These proteins are collectively referred to as transport proteins, and they function as either channels for the material or as carriers themselves. Channel proteins have hydrophilic domains exposed to the intracellular and extracellular fluids and a hydrophilic channel through their core that provides a hydrated opening for solutes to pass through the membrane layers. Passage through the channel allows...

Membrane Proteins

Membrane Proteins

Plasma membranes have integral transmembrane proteins involved in facilitated transport. These proteins are collectively referred to as transport proteins, and they function as either channels for the material or as carriers themselves. Channel proteins have hydrophilic domains exposed to the intracellular and extracellular fluids and a hydrophilic channel through their core that provides a hydrated opening for solutes to pass through the membrane layers. Passage through the channel allows...

Fluid Mosaic Model

Fluid Mosaic Model

Scientists identified the plasma membrane in the 1890s and its principal chemical components (lipids and proteins) by 1915. The model for plasma membrane structure, proposed in 1935 by Hugh Davson and James Danielli, was the first model to be widely accepted in the scientific community. The model was based on the plasma membrane's "railroad track" appearance in early electron micrographs. Davson and Danielli theorized that the plasma membrane's structure resembled a sandwich with the analogy of...

Multi-pass Transmembrane Proteins and β-barrels

Multi-pass Transmembrane Proteins and β-barrels

In multi-pass transmembrane proteins, the polypeptide chain crosses the membrane more than once. The transmembrane polypeptide chain either forms an α-helix or β-strand structure. α-Helix containing multi-pass transmembrane proteins are ubiquitous, whereas β-strand containing ones are mainly found in gram-negative bacteria, mitochondria, and chloroplasts.
α-Helix containing multi-pass transmembrane proteins
Multi-pass transmembrane proteins such as G-protein-linked receptors (GPCRs) and...

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Related Experiment Video

Updated: May 24, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Mem-PHybrid: hybrid features-based prediction system for classifying membrane protein types.

Maqsood Hayat¹, Asifullah Khan

¹Department of Computer and Information Sciences, Pakistan Institute of Engineering and Applied Sciences, Nilore, Islamabad, Pakistan.

Analytical Biochemistry

|February 21, 2012

Summary

A new system, Mem-PHybrid, accurately predicts membrane proteins and their types using hybrid features. This computational tool enhances understanding of these vital proteins, which constitute a significant portion of the genome.

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Area of Science:

Proteomics
Bioinformatics
Computational Biology

Background:

Membrane proteins are crucial cellular components, encoded by a substantial percentage of genes across organisms.
Accurate prediction of membrane proteins and their subtypes is essential for understanding cellular functions and disease mechanisms.

Purpose of the Study:

To develop a novel, two-layer prediction system, Mem-PHybrid, for identifying membrane proteins and classifying their types.
To enhance the accuracy and efficiency of membrane protein prediction through a hybrid feature approach.

Main Methods:

The Mem-PHybrid system utilizes a two-layer approach for protein classification.
Hybrid features are generated by fusing physicochemical and split amino acid composition-based features.
Minimum redundancy and maximum relevance techniques are applied for feature dimensionality reduction.
Performance is evaluated using Random Forest, Evidence-Theoretic K-Nearest Neighbor, and Support Vector Machine (SVM) classifiers on two independent datasets.

Main Results:

The SVM classifier, combined with hybrid features, achieved the highest prediction accuracy.
Accuracies reached 89.6% and 97.3% on dataset1, and 91.5% and 95.5% on dataset2, using jackknife and independent dataset tests, respectively.
The system demonstrates superior performance attributed to the synergy of hybrid features and SVM's learning capacity.

Conclusions:

Mem-PHybrid offers a highly accurate method for predicting membrane proteins and their types.
The integration of hybrid features and advanced machine learning classifiers significantly improves prediction performance.
Mem-PHybrid provides a valuable computational tool for researchers in proteomics and bioinformatics.