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Protein Complex Assembly

Protein Complex Assembly

Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types. Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...

Protein Complex Assembly

Protein Complex Assembly

Protein Complexes with Interchangeable Parts

Protein Complexes with Interchangeable Parts

Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order...

Protein Complexes with Interchangeable Parts

Protein Complexes with Interchangeable Parts

Predicting Molecular Geometry

Predicting Molecular Geometry

VSEPR Theory for Determination of Electron Pair Geometries

Prediction Intervals

Prediction Intervals

The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

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Related Experiment Video

Updated: Feb 4, 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

Performance evaluation measures for protein complex prediction.

Asma Ivazeh¹, Javad Zahiri², Maseud Rahgozar¹

¹Database Research Group (DBRG), Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.

|October 13, 2018

Summary

This summary is machine-generated.

Computational methods predict protein complexes crucial for cell function. This study addresses inconsistencies in evaluating these methods by introducing CompEvaluator, a tool for critical assessment of protein complex prediction algorithms.

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A Protocol for Computer-Based Protein Structure and Function Prediction

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Published on: November 3, 2011

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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

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Area of Science:

Computational biology
Bioinformatics
Systems biology

Background:

Protein complexes are vital for cellular organization and function.
Predicting protein complexes from protein-protein interaction (PPI) networks is a key research area.
Numerous computational methods exist for protein complex identification.

Purpose of the Study:

To address inconsistencies in performance evaluation measures for protein complex prediction methods.
To present the most important performance evaluation measures.
To develop a tool, CompEvaluator, for critically assessing these prediction methods.

Main Methods:

Literature review to identify key performance evaluation measures.
Development of the CompEvaluator tool.
Public release of the tool and documentation.

Main Results:

A consolidated set of important performance evaluation measures for protein complex prediction.
The development and release of CompEvaluator, a dedicated assessment tool.
Standardization of evaluation metrics for computational approaches.

Conclusions:

CompEvaluator provides a standardized approach to assess protein complex prediction methods.
Addressing inconsistencies in evaluation metrics is crucial for advancing the field.
The tool facilitates more reliable comparisons of different prediction algorithms.