R: Calculates amino acid chemical properties for sequence data

aminoAcidProperties {alakazam} | R Documentation

## Calculates amino acid chemical properties for sequence data

### Description

`aminoAcidProperties` calculates amino acid sequence physicochemical properties, including length, hydrophobicity, bulkiness, polarity, aliphatic index, net charge, acidic residue content, basic residue content, and aromatic residue content.

### Usage

    aminoAcidProperties(data, property = c("length", "gravy", "bulk",
      "aliphatic", "polarity", "charge", "basic", "acidic", "aromatic"),
      seq = "JUNCTION", nt = FALSE, trim = FALSE, label = NULL, ...)

### Arguments

`data` | `data.frame` containing sequence data.
`property` | vector strings specifying the properties to be calculated. Defaults to calculating all defined properties.
`seq` | `character` name of the column containing input sequences.
`nt` | boolean, TRUE if the sequences (or sequence) are DNA and will be translated.
`trim` | if `TRUE` remove the first and last codon/amino acids from each sequence before calculating properties. If `FALSE` do not modify input sequences.
`label` | name of sequence region to add as prefix to output column names.
`...` | additional named arguments to pass to the functions gravy, bulk, aliphatic, polar or charge.

### Details

For all properties except for length, non-informative positions are excluded, where non-informative is defined as any character in `c("X", "-", ".", "*")`.

The scores for GRAVY, bulkiness and polarity are calculated as simple averages of the scores for each informative positions. The basic, acid and aromatic indices are calculated as the fraction of informative positions falling into the given category.

The aliphatic index is calculated using the Ikai, 1980 method.

The net charge is calculated using the method of Moore, 1985, excluding the N-terminus and C-terminus charges, and normalizing by the number of informative positions. The default pH for the calculation is 7.4.

The following data sources were used for the default property scores:

- hydropathy: Kyte & Doolittle, 1982.

- bulkiness: Zimmerman et al, 1968.

- polarity: Grantham, 1974.

- pK: EMBOSS.

### Value

A modified `data` data.frame with the following columns:

- `*_AA_LENGTH`: number of amino acids.

- `*_AA_GRAVY`: grand average of hydrophobicity (GRAVY) index.

- `*_AA_BULK`: average bulkiness of amino acids.

- `*_AA_ALIPHATIC`: aliphatic index.

- `*_AA_POLARITY`: average polarity of amino acids.

- `*_AA_CHARGE`: net charge.

- `*_AA_BASIC`: fraction of informative positions that are Arg, His or Lys.

- `*_AA_ACIDIC`: fraction of informative positions that are Asp or Glu.

- `*_AA_AROMATIC`: fraction of informative positions that are His, Phe, Trp or Tyr.

Where `*` is the value from `label` or the name specified for `seq` if `label=NULL`.

### References

1. Zimmerman JM, Eliezer N, Simha R. The characterization of amino acid sequences in proteins by statistical methods. J Theor Biol 21, 170-201 (1968).

2. Grantham R. Amino acid difference formula to help explain protein evolution. Science 185, 862-864 (1974).

3. Ikai AJ. Thermostability and aliphatic index of globular proteins. J Biochem 88, 1895-1898 (1980).

4. Kyte J, Doolittle RF. A simple method for displaying the hydropathic character of a protein. J Mol Biol 157, 105-32 (1982).

5. Moore DS. Amino acid and peptide net charges: A simple calculational procedure. Biochem Educ 13, 10-11 (1985).

6. Wu YC, et al. High-throughput immunoglobulin repertoire analysis distinguishes between human IgM memory and switched memory B-cell populations. Blood 116, 1070-8 (2010).

7. Wu YC, et al. The relationship between CD27 negative and positive B cell populations in human peripheral blood. Front Immunol 2, 1-12 (2011).

8. http://emboss.sourceforge.net/apps/cvs/emboss/apps/iep.html

### See Also

See countPatterns for counting the occurance of specific amino acid subsequences. See gravy, bulk, aliphatic, polar and charge for functions that calculate the included properties individually.

### Examples

    # Subset example data
    db <- ExampleDb[c(1,10,100), c("SEQUENCE_ID", "JUNCTION")]

    # Calculate default amino acid properties from amino acid sequences
    # Use a custom output column prefix
    db$JUNCTION_TRANS <- translateDNA(db$JUNCTION)
    aminoAcidProperties(db, seq="JUNCTION_TRANS", label="JUNCTION")
    # Calculate default amino acid properties from DNA sequences
    aminoAcidProperties(db, seq="JUNCTION", nt=TRUE)

    # Use the Grantham, 1974 side chain volume scores from the seqinr package
    # Set pH=7.0 for the charge calculation
    # Calculate only average volume and charge
    # Remove the head and tail amino acids from the junction, thus making it the CDR3
    library(seqinr)
    data(aaindex)
    x <- aaindex[["GRAR740103"]]$I
    # Rename the score vector to use single-letter codes
    names(x) <- translateStrings(names(x), ABBREV_AA)
    # Calculate properties
    aminoAcidProperties(db, property=c("bulk", "charge"), seq="JUNCTION", nt=TRUE,
                        trim=TRUE, label="CDR3", bulkiness=x, pH=7.0)

[Package alakazam version 0.3.0 Index]