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Related Experiment Video

Updated: May 1, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

MD-Phylogeny: Constructing Statistically Supported Phylogenetic Trees from Protein Structures Using Molecular

Désirée B Langer¹, Ashar J Malik^2,3,4, Paul Klemm⁵

¹School of Biological Sciences, The University of Auckland, Auckland, New Zealand.

Methods in Molecular Biology (Clifton, N.J.)

|April 29, 2026

Summary

This summary is machine-generated.

MD-phylogeny uses protein structural comparisons and molecular dynamics (MD) simulations to build evolutionary trees when sequence similarity is low. This method provides robust phylogenies and statistical support for deep evolutionary relationships.

Keywords:

Molecular dynamics Evolution Protein structure Structural phylogeny Twilight zone

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Last Updated: May 1, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

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Published on: August 14, 2018

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

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Published on: August 16, 2017

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Area of Science:

Computational biology
Structural bioinformatics
Evolutionary biology

Background:

Phylogenetic tree construction typically relies on homologous sequence alignment.
Low sequence similarity poses challenges for traditional phylogenetic methods, especially in deep evolutionary analyses.
Protein structure comparison offers an alternative for inferring evolutionary relationships when sequence data is insufficient.

Purpose of the Study:

To introduce and detail the MD-phylogeny method for constructing robust phylogenetic trees.
To enable the study of deep evolutionary relationships using protein structure data, particularly in the twilight zone of sequence similarity.
To provide a protocol for generating statistically supported phylogenies through integrated structural and simulation approaches.

Main Methods:

Utilizes structural superposition methods for initial tree building.
Integrates molecular dynamics (MD) simulations to generate structural variants.
Derives confidence scores analogous to bootstrapping from MD simulations for statistical support.

Main Results:

MD-phylogeny generates robust phylogenies for protein datasets with low sequence similarity.
The method allows for the inference of deep evolutionary relationships.
Confidence scores derived from MD simulations provide statistical support for the constructed trees.

Conclusions:

MD-phylogeny is a valuable tool for evolutionary studies when sequence-based methods fail.
Integrating structural comparisons with MD simulations enhances the reliability of phylogenetic inference.
This protocol facilitates the application of MD-phylogeny for comprehensive evolutionary analyses.