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Protein Families

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Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism. Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members. If these new proteins contain similar amino acids in key...

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

Gene Families

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Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
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Evolution shapes the features of organisms over time, ensuring that they are suited for the environments in which they live. Sometimes, selection pressure leads to the rise of similar but unrelated adaptations in organisms with no recent common ancestors, a process known as convergent evolution.

Structural Protein Function

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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
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Updated: May 10, 2025

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

Evaluating sequence and structural similarity metrics for predicting shared paralog functions.

Olivier Dennler^1,2,3, Colm J Ryan^1,2,3

¹School of Medicine, University College Dublin, Dublin 4, D04 V1W8, Ireland.

NAR Genomics and Bioinformatics

|April 28, 2025

Summary

This summary is machine-generated.

New protein similarity metrics, including structural and language model embeddings, better predict gene paralog functions than sequence identity alone. Combining these novel approaches enhances functional prediction accuracy.

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An Integrated Approach for Microprotein Identification and Sequence Analysis

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Published on: July 12, 2022

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Gene duplication is a major driver of new gene evolution, creating paralogs that often retain similar functions.
Protein sequence identity is a common proxy for functional similarity, aiding in the prediction of shared functions between paralogs.
Emerging protein representations like protein language model (PLM) embeddings and AlphaFold-predicted structures offer new avenues for assessing functional similarity.

Purpose of the Study:

To evaluate alternative protein similarity metrics beyond sequence identity for predicting shared paralog functionality.
To determine if structural or PLM-based similarity metrics can outperform or complement sequence identity.
To investigate the impact of contextual features, such as homology, on predicting shared paralog functions.

Main Methods:

Comparison of various similarity metrics (sequence identity, PLM embeddings, structural similarity) using two species (yeast, human).
Assessment of shared functionality based on protein-protein interactions and synthetic lethality.
Integration of contextual features representing cross-species and within-species homology.

Main Results:

Alternative similarity metrics, including structural and PLM-based approaches, showed promise in predicting shared paralog functions.
These novel metrics are not redundant with sequence identity and improve predictions when combined.
Incorporating contextual homology features significantly enhanced the accuracy of predicting shared paralog functionality.

Conclusions:

Alternative protein similarity metrics capture functional aspects not represented by sequence identity alone.
Combining sequence identity with structural, PLM, and contextual homology features offers a more comprehensive approach to predicting paralog function.
These findings suggest improved methods for understanding gene function and evolution through comparative genomics.