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Updated: Jan 14, 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

Structome-AlignViewer: On Confidence Assessment in Structure-Aware Alignments.

Ashar J Malik^1,2,3, Siying Mao^1,2, Philip Hugenholtz^1,2

¹School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia.

Genome Biology and Evolution

|January 13, 2026

Summary

This summary is machine-generated.

Protein structure comparison reveals evolutionary links missed by sequence analysis. A new tool, Structome-AlignViewer, assesses alignment quality using spatial mapping and confidence scores for robust evolutionary studies.

Keywords:

alignment confidence scoring deep structural homology protein structure comparison structural phylogenetics structure-based alignment

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Last Updated: Jan 14, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction

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Published on: November 3, 2011

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Area of Science:

Computational Biology
Structural Bioinformatics
Evolutionary Biology

Background:

Protein structure comparison offers deeper evolutionary insights than sequence-based methods.
Structure-aware alphabets simplify 3D protein structures into comparable strings.
Challenges exist in aligning divergent protein structures, leading to misalignments.

Purpose of the Study:

To introduce Structome-AlignViewer, a web resource for evaluating structure-aware alignment quality.
To provide tools for spatial mapping and quantitative confidence scoring of alignments.
To support robust comparative and evolutionary analyses of protein structures.

Main Methods:

Encoding 3D protein structures into simplified, structure-aware strings.
Developing spatial mapping of alignment columns to protein structures.
Computing confidence scores based on pairwise structural substitutions and normalization.

Main Results:

Structome-AlignViewer enables visual and quantitative assessment of alignment quality.
Confidence scoring highlights well-supported alignment columns.
Analysis of existing structural classifications provides empirical benchmarks for alignment quality.

Conclusions:

Structome-AlignViewer offers an interpretable method for assessing structural alignment quality.
The tool aids in refining alignments by excluding gap-rich regions to focus on conserved cores.
Improved structural alignment quality facilitates more robust evolutionary and comparative analyses.