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Related Concept Videos

Fischer Projections02:18

Fischer Projections

Learning to draw Fischer projections of molecules and understanding their relevance plays a crucial role in the visual depiction of organic molecules. A Fischer projection is a two-dimensional projection on a planar surface to simplify the three-dimensional wedge–dash representation of molecules. This is especially helpful in the case of molecules with multiple chiral centers that can be difficult to draw. Here, all the bonds of interest are represented as horizontal or vertical lines. While...
Types of Membrane Protrusions01:28

Types of Membrane Protrusions

The protrusion of the cell surface is an initial step for several cellular processes, including cell migration, phagocytosis, and neurite outgrowth. These membrane protrusions are a result of cytoskeletal rearrangement. The most  widely observed cell protrusions include lamellipodia, pseudopodia, filopodia, microvilli, invadopodia, and podosomes. These protrusions can be of two types — static or dynamic.
The microvilli, an example of stable protrusions, are finger-like projections with a...
Multi-pass Transmembrane Proteins and β-barrels01:09

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...
Fluid Mosaic Model01:19

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...
Newman Projections02:06

Newman Projections

Different notations are used to represent the three-dimensional structure of molecules on two-dimensional surfaces. One of the most commonly used representations is the dash-wedge formula. The dashed wedges, solid wedges, and the plane lines indicate the groups situated behind the plane, coming out of the plane, and in the plane, respectively.
The organic molecules rotate across the single bonds leading to numerous temporary three-dimensional structures of varying energy known as conformers.
Mechanisms of Membrane-bending01:15

Mechanisms of Membrane-bending

The living membranes are flexible due to their fluid mosaic nature; however, their bending into different shapes is an active process regulated by specific lipids and proteins. The membrane bending can be transient as seen in vesicles or stable for a long time as in microvilli. Cells regulate the size, location, and duration of the membrane curvature.
Membrane bending can happen due to intrinsic changes in lipid composition or extrinsic association with different proteins. The proteins involved...

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Determining Membrane Protein Topology Using Fluorescence Protease Protection (FPP)
08:14

Determining Membrane Protein Topology Using Fluorescence Protease Protection (FPP)

Published on: April 20, 2015

Geometry preserving projections algorithm for predicting membrane protein types.

Tong Wang1, Tian Xia, Xiao-ming Hu

  • 1Institute of Computer and Information, Shanghai Second Polytechnic University, Shanghai 201209, China. tongwang0818@yahoo.cn

Journal of Theoretical Biology
|October 6, 2009
PubMed
Summary
This summary is machine-generated.

Predicting membrane protein types is crucial for understanding protein function. This study introduces a computational method combining pseudo position-specific score matrix (PsePSSM) and dipeptide composition (DC) for accurate membrane protein classification.

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Last Updated: Jun 19, 2026

Determining Membrane Protein Topology Using Fluorescence Protease Protection (FPP)
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A Protocol for Computer-Based Protein Structure and Function Prediction
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Realistic Membrane Modeling Using Complex Lipid Mixtures in Simulation Studies
07:31

Realistic Membrane Modeling Using Complex Lipid Mixtures in Simulation Studies

Published on: September 1, 2023

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Protein Science

Background:

  • Determining if a protein is a membrane protein and its type is essential for understanding its biological function.
  • Computational methods can aid biologists in classifying uncharacterized protein sequences.

Purpose of the Study:

  • To develop an effective computational method for predicting membrane protein types.
  • To represent protein sequences using a combination of pseudo position-specific score matrix (PsePSSM) and dipeptide composition (DC).

Main Methods:

  • A novel sequence encoding scheme combining PsePSSM and dipeptide composition (DC) was developed.
  • Geometry Preserving Projections (GPP) was used for dimensionality reduction of high-dimensional feature vectors.
  • K-nearest neighbor (K-NN) and Support Vector Machine (SVM) classifiers were employed for membrane protein type identification.

Main Results:

  • The proposed method effectively reduced the dimensionality of protein feature vectors.
  • Promising results were achieved in predicting membrane protein types using jackknife and independent dataset tests.
  • The combined PsePSSM and DC encoding scheme, along with GPP, demonstrated efficacy.

Conclusions:

  • The developed computational approach is effective for predicting membrane protein types.
  • This method provides a valuable tool for biologists studying uncharacterized membrane proteins.
  • The integration of advanced sequence encoding and dimensionality reduction techniques shows significant potential in protein classification.