I have been tasked with writing a program for computing properties of a give set of peptides. These peptides are given as 1-letter amino acid sequences and I need to compute the following :

  • Length of peptide
  • Number of Each Amino Acid
  • Percent composition of each amino acid
  • Molecular weight
  • Net charge of peptide
  • Positive charge
  • Negative charge
  • Isoelectric point (pI)
  • Hydropathicity
  • Percent polar amino acids
  • Percent positive amino acids
  • Percent negative amino acids
  • Percent hydrophobic amino acids
  • Hydrophobicity
  • Lipophilicity
  • Amphiphilicity
  • Water-Octanol Partition Coefficient
  • Steric Bulk
  • Side chain bulk
  • Net donated hydrogen bonds
  • Percent \alpha helix
  • Percent random coil
  • Percent \beta sheet

While some of these properties are self explanatory ( eg. size, num. of amino acids, percentage of amino acids. ) and easy to compute. Other properties ( like Molecular weight, Net. charge, Positive charge, Hydorphobicity etc ) have been difficult for me.

I donot have Chemistry or Biology background and hence have found these difficult to compute. I would be appreciative if someone could point me in the correct direction ( I have already been through Wikipedia ) containing methods to compute the above mentioned properties or to a standard text which would explain the above mentioned properties and also provide methods to compute them. Thank you all.


2 Answers 2


Biopython and the other bio-programming languages typically have examples of how to do this kind of thing.

For example here is some python code for calculating some of these:


Many of the propensity scales are in this database: http://www.genome.jp/aaindex/

And there are also biojava classes for accessing these. Essentially you will need to know what these physicochemical properties are and get access to a scale for converting the letter to a numerical value.


That's quite a laundry list, and I doubt someone is going to sit down and give you hints for all of them. Note that some of the properties (like percent alpha helix) rely on prediction method (secondary structure prediction, in this case). "Net donated hydrogen bonds" sounds like it makes sense only for a given complex with a solved 3D structure.

Nonetheless, you will probably find some of the stats implemented in EMBOSS, for example in the pepstats app.

  • $\begingroup$ Thank you for your reply. It has been helpful but would you happen to know of any reference text which goes over these properties ? $\endgroup$
    – Samrat Roy
    Jul 24, 2012 at 13:01
  • 1
    $\begingroup$ The introductory chapter of Proteins by Thomas Creighton (books.google.com/books/about/Proteins.html?id=hu8T_kI1LrkC) would be a great place to start. It was my Bible for introductory biochemistry in college! $\endgroup$
    – gkadam
    Jul 24, 2012 at 17:37

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