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Protein Organization

Protein Organization

Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence.

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Updated: May 26, 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

Atomic-level protein structure refinement using fragment-guided molecular dynamics conformation sampling.

Jian Zhang¹, Yu Liang, Yang Zhang

¹Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.

Structure (London, England : 1993)

|December 14, 2011

Summary

This summary is machine-generated.

Molecular dynamics (MD) simulations for protein structure refinement face challenges. This study reshapes the MD energy funnel using template-based distance maps, improving protein structure prediction accuracy.

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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

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Published on: March 1, 2022

Area of Science:

Computational Biology
Structural Bioinformatics
Biophysics

Background:

Molecular dynamics (MD) simulations are crucial for protein structure refinement.
Physics-based energy landscapes in MD simulations often lack a funnel to guide nonnative conformations to near-native states.

Purpose of the Study:

To address the limitations of MD simulations in protein structure refinement.
To develop a novel method for reshaping the MD energy funnel using template information.

Main Methods:

Utilized target models as probes to identify fragmental analogs from the Protein Data Bank (PDB).
Employed distance maps derived from fragmental analogs to reshape the MD energy funnel.
Tested the protocol on 181 benchmarking and 26 CASP targets.

Main Results:

Successfully refined protein structures with correct folds (TM-score >0.5), improving GDT-HA scores.
Observed less pronounced improvements for models with incorrect folds (TM-score <0.5).
Demonstrated that template-based fragmental distance maps reshape the MD energy landscape towards a funnel-like structure.

Conclusions:

The proposed method effectively reshapes the molecular dynamics energy landscape.
Combining knowledge-based template information with physics-based MD simulations offers a new avenue for improving high-resolution protein structures.