Bioinformatics and Protein Structural Analysis

Our fascination with protein folds

Proteins are large, complex molecules that play many important roles in the body. They regulate most of the work done by our cells and are required for the structure, function and regulation of the body’s tissues and organs. 

A protein is made up of one or more long, folded chains of amino acids (each called a polypeptide), whose sequences are determined by the DNA sequence of the protein-encoding gene.

Sometime around 1960, biologists got their first atomic-resolution look at protein structures within human cells and realized that each presents distinct folding patterns. These folds, how they cluster into different “families” and the clues they give about biological change have captured the attention of researchers ever since.

Undergraduates today will encounter protein structural analysis from different perspectives —  health science, environmental science, and ecology. If you have some interest and aptitude in math, computer science, and biology, you might consider pursuing bioinformatics as a graduate degree and a career.

What is Bioinformatics?

Bioinformatics uses computer technology to collect, store, analyze and disseminate biological data and information, such as DNA and amino acid sequences or annotations about those sequences. Scientists and clinicians use databases that organize and index such biological information to increase our understanding of health and disease and, in certain cases, as part of medical care.

Cellular Linguistics 

Just as linguistics studies patterns in language,  bioinformatics looks for patterns within sequences of DNA or protein. By comparing genes and other sequences in proteins, scientists learn about how these proteins influence every living function.

Over time, science came to understand that all proteins fold into stable three‐dimensional shapes, or conformations, that are determined by their amino acid sequence. They also discovered that the fold of a protein offers clues about its function.

The protein “folding problem.”

Today, biology researchers continue to try  to better understand three aspects of these protein folding patterns:

  1. The folding code: the thermodynamic question of what balance of interatomic forces (say the interaction of nitrogen and hydrogen atoms) dictates the structure of the protein, for a given amino acid sequence. 
  1. Protein structure prediction: the computational problem of how to predict a protein’s native structure from its amino acid sequence. Raw computing power and smart algorithms allow scientists to predict the structure of a protein by inputting the amino acid sequence into a computer. The advanced technology and modeling software allow scientists and researchers to form a predicted structure. Science continues to discover new genes and proteins, which means that other scientists race to predict structures. 
  1. The folding process: the kinetics question of what routes or pathways some proteins use to fold and at what speeds. Recent kinetics experiments show that the rate of folding varies across different phases of the process. The amount of folded functional protein in a cell depends on several factors such as, rate of protein biosynthesis and degradation.

Underlying all of these ongoing areas of research is the question of the inherent stability of an individual protein segment. As a future biology researcher or bioinformatician, you will advance this science and learn even more about what is generally called the “folding problem” — the limits of humankind’s ability to understand how a cell’s life relies on the ability of its constituent proteins to fold into 3D structures that are crucial for their function. 


Inspired Futures: John Carroll University biology majors move into careers in health science, environmental science, and a range of other life science fields. Concentrations in cell and molecular biology and environmental science prepares you for graduate programs and research positions in biology and related disciplines such as physiology, neuroscience, and evolutionary biology.