| chou_fasman {proteinKit} | R Documentation |
It was developed by Peter Y. Chou and Gerald D. Fasman in the 1970s. The method is based on the observation
that certain amino acids have a propensity to form specific types of secondary structures, such as alpha-helices,
beta-sheets, and turns.
Here's a brief overview of how the Chou-Fasman method works:
1. Amino Acid Propensities: Each amino acid is assigned a set of probability values that reflect its
tendency to be found in alpha-helices, beta-sheets, and turns. These values are derived from statistical
analysis of known protein structures.
2. Sliding Window Technique: A sliding window of typically 7 to 9 amino acids is moved along the protein
sequence. At each position, the average propensity for each type of secondary structure is calculated
for the amino acids within the window.
3. Thresholds and Rules: The method uses predefined thresholds and rules to identify regions of the
protein sequence that are likely to form alpha-helices or beta-sheets based on the calculated propensities.
For example, a region with a high average propensity for alpha-helix and meeting certain criteria
might be predicted to form an alpha-helix.
4. Secondary Structure Prediction: The method predicts the secondary structure by identifying contiguous
regions of the sequence that exceed the thresholds for helix or sheet formation. It also takes into
account the likelihood of turns, which are important for the overall folding of the protein.
5. Refinement: The initial predictions are often refined using additional rules and considerations, such
as the tendency of certain amino acids to stabilize or destabilize specific structures, and the overall
composition of the protein.
The Chou-Fasman method was one of the first widely used techniques for predicting protein secondary structure
and played a significant role in the field of structural bioinformatics. However, it has largely been superseded
by more accurate methods, such as those based on machine learning and neural networks, which can take into
account more complex patterns and interactions within protein sequences.
Despite its limitations, the Chou-Fasman method remains a historical milestone in the understanding of
protein structure and the development of computational methods for predicting it. It also serves as a
foundational concept for those learning about protein structure prediction and bioinformatics.
chou_fasman(prot,
polyaa = FALSE); print(chou_fasman("AAABAAGKKKJLLMMMMMM"));