What bioinformatics tools can you use to analyze protein structures?

1 Protein databases

The first step in protein structure analysis is to find and access the relevant data. Protein databases store and organize information about protein sequences, structures, families, and functions. Some of the most popular protein databases are Protein Data Bank (PDB), UniProt, and Pfam. PDB is the largest repository of experimentally determined protein structures, with over 170,000 entries that can be searched, downloaded, and visualized using various web-based tools and software. UniProt is a comprehensive database of protein sequences, annotations, and classifications with more than 200 million entries that can be searched, filtered, and analyzed using various tools and algorithms. Pfam is a database of protein families and domains with over 20,000 entries that can be searched, browsed, and aligned using various tools and methods.

3 Protein prediction

The third step in protein structure analysis is to predict the data. Protein prediction tools can help you infer the structure, function, or interaction of proteins from their sequences, using various computational models and algorithms. Phyre2 is a web-based and easy-to-use tool with high accuracy and speed for modeling the 3D structure of a protein sequence as well as identifying its function, domains, and interactions. I-TASSER is a web-based and advanced tool with high accuracy and reliability for predicting the 3D structure of a protein sequence, as well as its function, binding sites, and interactions. Rosetta is a software suite and platform with high flexibility and versatility for modeling the 3D structure of a protein sequence, designing new proteins, optimizing protein-protein interactions, and simulating protein folding.

4 Protein comparison

The fourth step in protein structure analysis is to compare the data. Protein comparison tools, such as DALI, TM-align, and VAST, can help you measure the similarity, difference, or evolution of protein structures. DALI is a web-based and fast tool with high sensitivity and specificity; it can be used to search, align, and cluster protein structures, as well as generate protein structure networks and phylogenies. TM-align is a web-based and simple tool with high accuracy and efficiency; it can be used to align and superimpose protein structures, as well as calculate their structural similarity and distance. VAST is a web-based and comprehensive tool with high coverage and diversity; it can be used to search, align, and classify protein structures, as well as explore their structural relationships and variations.

5 Protein design

The fifth step in protein structure analysis is to design the data. Protein design tools, such as Foldit, Coot, and PyRosetta, can help you create, modify, or optimize protein structures. Foldit is a game-like and interactive tool for protein design, with high creativity and fun. Coot is a software for protein design with high functionality and usability. PyRosetta is a software for protein design that has high flexibility and power. All of these tools can be used to build and refine protein structures, edit and correct errors and anomalies, as well as design and engineer new proteins or modify existing ones.

6 Protein learning

The sixth step in protein structure analysis is to learn from the data. Protein learning tools, such as Proteopedia, PDB-101, and SWISS-MODEL, can help you understand, test, or teach the concepts and principles of protein structure. Proteopedia is a wiki-like and collaborative tool with high quality and accessibility, allowing you to browse, edit, and contribute to various articles and topics about protein structure and function. PDB-101 is a web-based and educational tool with high diversity and relevance, offering exploration of various aspects and applications of protein structure and function. SWISS-MODEL is a web-based and practical tool with high simplicity and utility, providing the basics and steps of protein structure prediction as well as various tools and methods for practice.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?