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Protein Networks

Protein Networks

Conservation of Protein Domains Over Different Proteins

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain. Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...

Proteomics

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...

Conservation of Protein Domains

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Protein-Protein Interfaces

Protein-Protein Interfaces

Protein-protein Interfaces

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...

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Related Experiment Video

Updated: Jul 25, 2025

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

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

Published on: July 8, 2025

iQDeep: an integrated web server for protein scoring using multiscale deep learning models.

Md Hossain Shuvo¹, Mohimenul Karim², Debswapna Bhattacharya³

¹Department of Computer Science, Virginia Tech, Blacksburg, VA 24061, United States. Electronic address: https://twitter.com/mzs0149.

Journal of Molecular Biology

|June 25, 2023

Summary

This summary is machine-generated.

iQDeep is a new web server for protein scoring that uses deep residual neural networks to assess prediction accuracy. It provides an independent, open-access tool for evaluating computational protein models with high reliability.

Keywords:

accuracy estimation deep learning protein scoring protein structure prediction

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Published on: July 16, 2017

Area of Science:

Computational biology
Structural bioinformatics
Artificial intelligence in biochemistry

Background:

Recent advances in protein structure prediction offer high accuracy.
Existing prediction methods lack independent, open-access scoring systems.
A versatile protein scoring tool is needed for various predictive modeling scenarios.

Purpose of the Study:

To introduce iQDeep, an integrated and customizable web server for independent protein scoring.
To provide a reliable method for estimating Global Distance Test (GDT) scores for protein models.
To offer a freely accessible platform for evaluating computational protein structure predictions.

Main Methods:

Utilizes multiscale deep residual neural networks (ResNets) for residue-level error classification.
Probabilistically combines error classifications to generate protein scores.
Adjusts error resolutions to estimate standard and high-accuracy Global Distance Test (GDT) metrics.

Main Results:

iQDeep demonstrates reliable estimation of GDT metrics for versatile protein scoring.
The method's performance was validated against state-of-the-art approaches in CASP12, CASP13, and CASP14.
The iQDeep web server provides features for individual/batch processing, job tracking, and results analysis.

Conclusions:

iQDeep offers a robust, independent, and open-access solution for protein scoring.
The web server facilitates automated job submission, privacy-preserving analysis, and interpretation of results.
iQDeep enhances the evaluation of computational protein structure prediction accuracy.