Application of Python in Bioinformatics

According to the National Human Genome Research Institute (NIH), bioinformatics is the subfield of biology that utilizes technology to analyze biological information, like DNA, genetic/amino acid sequences (Adams, D., 2025). So, how does Python connect with bioinformatics ? Well, our genetic information is basically a set of code that is ready to be executed, and so scientists thought, what if we use the code in our genes and replicate it in the Python environment?

In a recent study published in BMC Bioinformatics, a group of researchers developed a Python package known as PyPropel, which enables users to analyze protein sequences and the functions they perform (Sun et al., 2025). To understand how PyPropel works, let’s first take a step back and try to understand how proteins work. In a simplified context, proteins are biological molecules that consist of chains of amino acids. Protein acts as a biological catalyst (enzymes), physical and chemical transporters (protein channels; hormones), an energy source, antibodies, etc. Proteins are divided into 4 structural levels, which include:

• Primary structure: chains of amino acids that are bonded by peptide bonds
• Secondary structure: the folding of the chains into either alpha helices or beta pleated sheets
• Tertiary structure: the bonding between the R groups
• Quaternary structure: the bonding between two or more proteins

Now that we understand the basics of how proteins work, let’s start to analyze how PyPropel works. PyPropel is a comprehensive Python package that enables users to calculate the distance between two amino acids or a specified chain of amino acids, it can check the composition of the amino acid, calculate the length of the protein, and predict protein properties(Sun et al., 2025).

1. Calculating the distance between two amino acids

Distance Function

The dist.all_vs_all is the built-in comparison function that compares the distance between 2 protein chains. For instance, you can see that the distance between chain 1 (L) and chain 2 (M) is around 33.363850. This function is important as it helps us identify the active site of the protein, which tells us about the function of the protein and its structure (Sun et al., 2025).

Distance function sample answer

2. Identifying proteins’ composition

Single amino acid function

Di-amino acid function

Tri-amino acid function

Quad-amino acid function

Pypropel can also calculate the composition of the amino acids across the protein chains. There are about 20 common amino acids that exist in nature, so the program would extract the feature of the protein chain, identify the common amino acids that are found on the chain, and convert it into the percentage composition by using the fpseq.composition function (Sun et al., 2025). Noted that those common amino acids can also form a di, tri, and quad amino acids. Pypropel could also identify those complex amino acids and calculate their composition by using the msa.composition function. Below is a sample output of the program and based on the result, it is mostly the built in function that utilized the usage of dictionary in the process.

fpseq.composition function sample output

msa.composition function sample output

3. Calculate the length of the protein chains

Length Function

Length calculation is another feature that PyPropel can perform. PyPropel utilized the fpseq.length to extract the protein chain and measure the length in either the normal or logarithmic scale (Sun et al., 2025). Calculating the length of the protein chain supports a better understanding of the protein. Below is the sample output of the program.

Normal Mode Output

Logarithmic Mode Output

4. Predicting the protein properties

Protein Characteristic function

Lastly, Pypropel can also predict the properties of a protein where they identify the protein and check the 23 preset physiochemical properties (Table A) that are found in amino acids (Sun et al., 2025).

Table 1

Pypropel can perform this function by utilizing the prebuilt function fpsite.property. Property function allow user to input the logic, set and delete values which in this case, the logic set is the 23 physiochemical properties of protein and value will be assign for each property (Geeksforgeeks, 2025). Below is the sample output.

Sample Output for Protein Property

In conclusion, Pypropel is one of the many Python models that utilized in the bioinformatics industries. Due to the easy-understanding nature of Python, Pypropel allows scientists to perform various functions which includes calculating distance between amino acids and its chain (allow to identifying the active site of the protein), calculate the composition of the amino acids across the protein chains with the length of protein and checking the protein properties. Understanding the function of proteins and its structure is the gateway for further understanding of genome and drug delivery system.

References:

1. Sun, J., Ru, J., Cribbs, A. P., & Xiong, D. (2025). PyPropel: a Python-based tool for efficiently processing and characterising protein data. BMC bioinformatics, 26(1), 70. https://doi.org/10.1186/s12859-025-06079-3
2. Adams D.,. (2025, September 24). Bioinformatics. Genome.gov; National Human Genome Research Institute. https://www.genome.gov/genetics-glossary/Bioinformatics
3. GeeksforGeeks. (2018, September 21). Python property() function. GeeksforGeeks. https://www.geeksforgeeks.org/python/python-property-function/