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Protein Families

Protein Families

Conservation of Protein Domains Over Different Proteins

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain. Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...

Conservation of Protein Domains

Conservation of Protein Domains

Protein Complexes with Interchangeable Parts

Protein Complexes with Interchangeable Parts

Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order...

Multi-species Conserved Sequences

Multi-species Conserved Sequences

Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved...

Maxam-Gilbert Sequencing

Maxam-Gilbert Sequencing

In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
The...

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Related Experiment Video

Updated: Jun 3, 2025

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

Identifying representative sequences of protein families using submodular optimization.

Ha Nguyen¹, Hung Nguyen¹, Phuong Nguyen¹

¹Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, 36849, USA.

Scientific Reports

|January 8, 2025

Summary

This summary is machine-generated.

We developed efficient algorithms using submodular optimization to select representative protein sequences for enzyme families. The Greedy algorithm excels at reducing redundancy while maintaining accuracy in sequence representation.

Keywords:

Protein analysis Representative sequences Submodular optimization

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Last Updated: Jun 3, 2025

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

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

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Published on: July 25, 2013

Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

Area of Science:

Bioinformatics
Computational Biology
Enzymology

Background:

Identifying representative protein sequences for functionally similar enzymes is computationally challenging.
Existing methods struggle with accuracy and redundancy in large datasets.

Purpose of the Study:

To apply submodular optimization for selecting representative sequences in thioesterase enzyme families.
To introduce and validate Greedy and Bidirectional Greedy algorithms for this task.

Main Methods:

Submodular optimization was employed to select representative sequences.
Two algorithms, Greedy and Bidirectional Greedy, were developed and tested.
Curated protein sequence data from the Thioester-active enzymes (ThYme) database was used for validation.

Main Results:

Both algorithms successfully generated sequence subsets preserving completeness and specificity.
The Greedy algorithm demonstrated superior performance in reducing redundancy compared to Bidirectional Greedy and other methods.
The approach offers near-optimal results in polynomial time.

Conclusions:

Submodular optimization provides an efficient method for selecting representative protein sequences.
The Greedy algorithm is a highly effective tool for reducing redundancy in enzyme family sequence representation.
This work can enhance protein databases by improving sequence selection and optimization.