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Related Concept Videos

Protein Folding01:22

Protein Folding

Overview
Protein Folding01:22

Protein Folding

Overview
Protein Folding01:25

Protein Folding

Proteins are chains of amino acids linked together by peptide bonds. Upon synthesis, a protein folds into a three-dimensional conformation, critical to its biological function. Interactions between its constituent amino acids guide protein folding, and hence the protein structure is primarily dependent on its amino acid sequence.
Protein Structure Is Critical to Its Biological Function
Proteins perform a wide range of biological functions such as catalyzing chemical reactions, providing...
Protein Folding Quality Check in the RER01:29

Protein Folding Quality Check in the RER

ER is the primary site for the maturation and folding of soluble and transmembrane secretory proteins. The calnexin cycle is a specific chaperone system that folds and assesses the confirmation of N-glycosylated proteins before they can exit the ER lumen. The primary players of this quality check pipeline are the lectins, ER-resident chaperones, and a glucosyl transferase enzyme. In case the calnexin system in the lumen fails to salvage a misfolded protein, it is transported to the cytoplasm...
Molecular Chaperones and Protein Folding03:00

Molecular Chaperones and Protein Folding

The native conformation of a protein is formed by interactions between the side chains of its constituent amino acids. When the amino acids cannot form these interactions, the protein cannot fold by itself and needs chaperones. Notably, chaperones do not relay any additional information required for the folding of polypeptides; the native conformation of a protein is determined solely by its amino acid sequence. Chaperones catalyze protein folding without being a part of the folded protein.
The...
Molecular Chaperones and Protein Folding03:00

Molecular Chaperones and Protein Folding

The native conformation of a protein is formed by interactions between the side chains of its constituent amino acids. When the amino acids cannot form these interactions, the protein cannot fold by itself and needs chaperones. Notably, chaperones do not relay any additional information required for the folding of polypeptides; the native conformation of a protein is determined solely by its amino acid sequence. Chaperones catalyze protein folding without being a part of the folded protein.
The...

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Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
09:51

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

DescFold: a web server for protein fold recognition.

Ren-Xiang Yan1, Jing-Na Si, Chuan Wang

  • 1State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, China. simpleyrx@163.com

BMC Bioinformatics
|December 17, 2009
PubMed
Summary
This summary is machine-generated.

The enhanced DescFold method significantly improves protein fold recognition using new descriptors like profile-profile alignment (PPA) and profile-structural-profile alignment (PSPA). This machine learning tool aids in predicting protein structures by identifying structural homologs.

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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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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

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A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Machine learning in proteomics

Background:

  • Machine learning methods, including Support Vector Machines (SVMs), are powerful for developing protein fold recognition tools.
  • The previous DescFold method utilized four descriptors: Psi-blast, Rps-blast, secondary structure element alignment (SSEA), and PROSITE motifs.
  • This study aimed to enhance DescFold by incorporating more effective descriptors and creating a user-friendly web server.

Purpose of the Study:

  • To improve the performance of the DescFold protein fold recognition tool.
  • To introduce novel, more powerful descriptors for enhanced accuracy.
  • To develop a publicly accessible web server for the improved DescFold method.

Main Methods:

  • Introduced new descriptors: profile-profile alignment (PPA) using COMPASS and profile-structural-profile alignment (PSPA) utilizing TM-align.
  • Trained and tested the enhanced DescFold on 1,835 diverse proteins from SCOP 1.73.
  • Constructed a web server using SVM models trained on the SCOP_1.73_40% dataset.

Main Results:

  • The incorporation of PPA and PSPA descriptors substantially boosted DescFold's fold recognition performance.
  • Tested on a stringent set of 1,866 proteins from SCOP 1.75, the enhanced DescFold correctly recognized structural homologs at the fold level for nearly 46% of proteins at a <5% false positive rate.
  • Benchmarked against established methods using LiveBench targets and the Lindahl dataset, demonstrating competitive performance.

Conclusions:

  • The improved DescFold method exhibits highly competitive performance compared to existing fold recognition algorithms.
  • DescFold serves as a valuable tool for assisting in template-based protein structure prediction.
  • The DescFold web server is available for public use at http://202.112.170.199/DescFold/index.html.