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Updated: May 2, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

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Published on: December 7, 2021

evo3D R package: a spatial haplotype framework for structure-informed analysis of molecular evolution.

Bradley K Broyles¹, Qixin He^1,2

¹Department of Biological Sciences, Purdue University, West Lafayette, IN, USA.

Molecular Biology and Evolution

|April 30, 2026

Summary

This summary is machine-generated.

The evo3D R package enables structure-informed evolutionary analysis of proteins, moving beyond linear sequences. It identifies conserved spatial neighborhoods missed by traditional methods, advancing molecular evolution studies.

Keywords:

MSA-structure integration interaction surface evolution protein evolution spatial haplotypes spatial windows structure-informed evolution

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Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Area of Science:

Molecular Biology
Evolutionary Biology
Bioinformatics

Background:

Evolutionary analyses traditionally focus on linear protein sequences, overlooking crucial 3D structural features.
Existing structure-informed methods have limitations in predefined statistics and 3D window types, restricting analytical scope.
A need exists for flexible frameworks that integrate 3D structural information into evolutionary analyses.

Purpose of the Study:

To introduce evo3D, a novel R package for comprehensive structure-informed evolutionary analysis.
To provide a flexible framework supporting diverse downstream statistics and complex protein structures.
To facilitate the direct evaluation of evolutionary patterns within 3D structural contexts.

Main Methods:

Developed the evo3D R package with a focus on extracting structure-informed multiple sequence alignment subsets (spatial haplotypes).
Implemented fixed-count and fixed-distance spatial windows, residue and codon analysis modes.
Utilized a single wrapper function, run_evo3d(), to extend analysis to multimers, interfaces, and multiple structural models.

Main Results:

Demonstrated evo3D's utility through an epitope-level diversity scan of the Hepatitis C virus E1/E2 complex.
Identified conserved spatial neighborhoods missed by linear sliding window approaches.
Evaluated evo3D's scalability using the octameric Chikungunya virus E1/E2 assembly.

Conclusions:

evo3D formalizes key components of structure-informed evolutionary analysis, removing technical barriers.
The package streamlines the evaluation of evolutionary patterns within 3D structural contexts.
Anticipate wide application of evo3D in molecular evolution studies.