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Structural bioinformatics

Structural bioinformatics is a engineering topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Structural bioinformatics rather than just read about it. In short: Structural bioinformatics is the branch of bioinformatics that is related to the analysis and prediction of the three-dimensional structure of biological macromolecules such as proteins, RNA, and DNA. It deals with generalizations about macromolecular 3D structures such as comparisons of overall folds and local motifs, principles of molecular folding, evolution, binding interactions, and structure/function relations…

Structural bioinformatics — main illustration
Structural bioinformatics — illustration

Key takeaways

  • Structural bioinformatics belongs to engineering; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Structural bioinformatics to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Structural bioinformatics from memory before moving on to harder problems.

Reference excerpt

Structural bioinformatics is the branch of bioinformatics that is related to the analysis and prediction of the three-dimensional structure of biological macromolecules such as proteins, RNA, and DNA. It deals with generalizations about macromolecular 3D structures such as comparisons of overall folds and local motifs, principles of molecular folding, evolution, binding interactions, and structure/function relationships, working both from experimentally solved structures and from computational models. The term structural has the same meaning as in structural biology, and structural bioinformatics can be seen as a part of computational structural biology. The main objective of structural bioinformatics is the creation of new methods of analysing and manipulating biological macromolecular data in order to solve problems in biology and generate new knowledge.

Introduction

Protein structure

The structure of a protein is directly related to its function. The presence of certain chemical groups in specific locations allows proteins to act as enzymes, catalyzing several chemical reactions. In general, protein structures are classified into four levels: primary (sequences), secondary (local conformation of the polypeptide chain), tertiary (three-dimensional structure of the protein fold), and quaternary (association of multiple polypeptide structures). Structural bioinformatics mainly addresses interactions among structures taking into consideration their space coordinates. Thus, the primary structure is better analyzed in traditional branches of bioinformatics. However, the sequence implies restrictions that allow the formation of conserved local conformations of the polypeptide chain, such as alpha-helix, beta-sheets, and loops (secondary structure). Also, weak interactions (such as hydrogen bonds) stabilize the protein fold. Interactions could be intrachain, i.e., when occurring between parts of the same protein monomer (tertiary structure), or interchain, i.e., when occurring between different structures (quaternary structure). Finally, the topological arrangement of interactions, whether strong or weak, and entanglements is being studied in the field of structural bioinformatics, utilizing frameworks such as circuit topology.

Structure visualization

Protein structure visualization is an important issue for structural bioinformatics. It allows users to observe static or dynamic representations of the molecules, also allowing the detection of interactions that may be used to make inferences about molecular mechanisms. The most common types of visualization are:

Cartoon: this type of protein visualization highlights the secondary structure differences. In general, α-helix is represented as a type of screw, β-strands as arrows, and loops as lines. Lines: each amino acid residue is represented by thin lines, which allows a low cost for graphic rendering. Surface: in this visualization, the external shape of the molecule is shown. Sticks: each covalent bond between amino acid atoms is represented as a stick. This type of visualization is most used to visualize interactions between amino acids...

DNA structure The classic DNA duplexes structure was initially described by Watson and Crick (and contributions of Rosalind Franklin). The DNA molecule is composed of three substances: a phosphate group, a pentose, and a nitrogen base (adenine, thymine, cytosine, or guanine). The DNA double helix structure is stabilized by hydrogen bonds formed between base pairs: adenine with thymine (A-T) and cytosine with guanine (C-G). Many structural bioinformatics studies have focused on understanding interactions between DNA and small molecules, which has been the target of several drug design studies.

Interactions Interactions are contacts established between parts of molecules at different levels. They are responsible for stabilizing protein structures and perform a varied range of activities. In biochemistry, interactions are characterized by the proximity of atom groups or molecules regions that present an effect upon one another, such as electrostatic forces, hydrogen bonding, and hydrophobic effect. Proteins can perform several types of interactions, such as protein-protein interactions (PPI), protein-peptide interactions, protein-ligand interactions (PLI), and protein-DNA interaction.

Calculating contacts Calculating contacts is an important task in structural bioinformatics, being important for the correct prediction of protein structure and folding, thermodynamic stability, protein-protein and protein-ligand interactions, docking and molecular dynamics analyses, and so on. Traditionally, computational methods have used threshold distance between atoms (also called cutoff) to detect possible interactions. This detection is performed based on Euclidean distance and angles between atoms of determined types. However, most of the methods based on simple Euclidean distance cannot detect occluded contacts. Hence, cutoff free methods, such as Delaunay triangulation, have gained prominence in recent years. In addition, the combination of a set of criteria, for example, physicochemical properties, distance, geometry, and angles, have been used to improve the contact determination.

Protein Data Bank (PDB)

The Protein Data Bank (PDB) is a database of 3D structure data for large biological molecules, such as proteins, DNA, and RNA. PDB is managed by an international organization called the Worldwide Protein Data Bank (wwPDB), which is composed of several local organizations, as. PDBe, PDBj, RCSB, and BMRB. They are responsible for keeping copies of PDB data available on the internet at no charge. The number of structure data available at PDB has increased each year, being obtained typically by X-ray crystallography, NMR spectroscopy, or cryo-electron microscopy.

… excerpt ends here. Continue reading the full article.

Illustrations

Structural bioinformatics: Three-dimensional structure of a protein
Three-dimensional structure of a protein
Structural bioinformatics: Structural visualization of BACTERIOPHAGE T4 LYSOZYME (PDB ID: 2LZM). (A) Cartoon; (B) Lines; (C) Surface; (D) Sticks.
Structural visualization of BACTERIOPHAGE T4 LYSOZYME (PDB ID: 2LZM). (A) Cartoon; (B) Lines; (C) Surface; (D) Sticks.
Structural bioinformatics: Contacts between two amino acid residues: Q196-R200 (PDB ID- 2X1C)[7]
Contacts between two amino acid residues: Q196-R200 (PDB ID- 2X1C)[7]
Structural bioinformatics: The number of structures from PDB. (A) The overall growth of released structures in Protein DataBank per year. (B) Growth of structures deposited in PDB from X-ray crystallography, NMR spectroscopy, and 3D electron microscopy experiments per year. Source: https://www.rcsb.org/stats/growth
The number of structures from PDB. (A) The overall growth of released structures in Protein DataBank per year. (B) Growth of structures deposited in PDB from X-ray crystallography, NMR spectroscopy, and 3D electron microscopy experiments per year. Source: https://www.rcsb.org/stats/growth
Structural bioinformatics: A Ramachandran plot generated from human PCNA (PDB ID 1AXC). The red, brown, and yellow regions represent the favored, allowed, and "generously allowed" regions as defined by ProCheck. This plot can be used to verify incorrectly modeled amino acids.
A Ramachandran plot generated from human PCNA (PDB ID 1AXC). The red, brown, and yellow regions represent the favored, allowed, and "generously allowed" regions as defined by ProCheck. This plot can be used to verify incorrectly modeled amino acids.

Worked examples

Example 1 — a first encounter with Structural bioinformatics

Start with the simplest possible case. Write down what Structural bioinformatics claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In engineering, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Structural bioinformatics before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Structural bioinformatics ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Structural bioinformatics

In research
Structural bioinformatics appears in engineering research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Structural bioinformatics in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Structural bioinformatics is common in secondary-school and first-year university syllabi. It links to neighbouring topics Structural bioinformatics, so understanding it makes those chapters shorter.
In everyday life
Look for Structural bioinformatics outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Structural bioinformatics in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Structural bioinformatics means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Structural bioinformatics out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Structural bioinformatics in simple terms?

Structural bioinformatics is the branch of bioinformatics that is related to the analysis and prediction of the three-dimensional structure of biological macromolecules such as proteins, RNA, and DNA. It deals with generalizations about macromolecular 3D structures such as comparisons of overall fo…

Why does Structural bioinformatics matter?

Because it connects several engineering ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Structural bioinformatics?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Structural bioinformatics.

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