In a-albuquerque/snpCYP: Assessing potential snp impact on CYP cathalitic activity

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Summary

snpCYP is an R package to streamline and automate the process of reading and analyzing nonsynonymous single nucleotide polymorphisms (SNP) on CYP (cytochrome P450 enzyme) genes. It is supposed to allow for easier exploratory analysis by graphically outputting the nsSNP distribution and their potential disruptions on drug metabolism by correlating the SNPs to known from DIDB databases.

This document gives a tour of snpCYP (version 0.1.9001). It was written in R Markdown, using the knitr package for production. See help(package = "snpCYP") for further details.

To download snpCYP, use the following commands, (user should also load basic data regarding wild-type CYP isoforms in order to run examples or shiny, unless if custom wild-type data is to be provided): ``` {r eval=FALSE} require("devtools") install_github("a.albuquerque/snpCYP", build_vignettes = TRUE) library("snpCYP") load(file = "./data/baseSeqs.rda") load(file = "./data/drugs.rda") library("snpCYP") # second time

To list all sample functions available in the package:
``` {r eval=FALSE}
ls("package:snpCYP")

To list all sample datasets available in the package: ``` {r eval=FALSE} data(package = "snpCYP")

To run the shinyApp:
```r
snpCYP::runsnpCYP()

Functions

More details about the 4 functions available:

1. detectSNP

Summary of the function

detectSNP is a function to facilitate detection of nsSNP when the protein sequence of the clinically relevant CYP are available (CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4). It compares each aminoacid on the sequence in each of the sequences to the canonical wide-type sequence at UniProtKB.

How to use the function

Parameter Format

The function receives a list of sequences of any one of the CYPs above and a list of the corresponding canonical name of the isoform also as above. Both must be lists of string.. list of CYPs to be analyzed, list of strings.

The function will then plot each of the CYP provided and compare then with respect of the frequency of nsSNP at each.

Example of Using the Function

In the following example, we are providing 2 sequences from the same individual (artificial), corresponding to isoforms 1A2 and 2B6.

``` {r eval=FALSE} load(file = "./data/baseSeqs.rda") detectSNP(list("CYP1A2", "CYP2B6"), list(paste("ASASQSVPFSATELLLASAIFCLVFWVLKGLRPRVPKGLKSPPEPWGWPLLGHVLTLGKN", "PHLALSRMSQRYGDVLQIRIGSTPVLVLSRLDTIRQALVRQGDDFKGRPDLYTSTLITDG", "QSLTFSTDSGPVWAARRRLAQNALNTFSIASDPASSSSCYLEEHVSKEAKALISRLQELM", "AGPGHFDPYNQVVVSVANVIGAMCFGQHFPESSDEMLSLVKNTHEFVETASSGNPLDFFP", "ILRYLPNPALQRFKAFNQRFLWFLQKTVQEHYQDFDKNSVRDITGALFKHSKKGPRASGN", "LIPQEKIVNLVNDIFGAGFDTVTTAISWSLMYLVTKPEIQRKIQKELDTVIGRERRPRLS", "DRPQLPYLEAFILETFRHSSFLPFTIPHSTTRDTTLNGFYIPKKCCVFVNQWQVNHDPEL", "WEDPSEFRPERFLTADGTAINKPLSEKMMLFGMGKRRCIGEVLAKWEIFLFLAILLQQLE", "FSVPPGVKVDLTPIYGLTMKHARCEHVQARLRFSIN", sep=""), paste("MEL", "SVLLFLALLTGLLLLLVQRHPNTHDRLPPGPRPLPLLGNLLQMDRRGLLKSFLRFRE", "KYGDVFTVHLGPRPVVMLCGVEAIREALVDKAEAFSGRGKIAMVDPFFRGYGVIFANGNR", "WKVLRRFSVTTMRDFGMGKRSVEERIQEEAQCLIEELRKSKGALMDPTFLFQSITANIIC", "SIVFGKRFHYQDQEFLKMLNLFYQTFSLISSVFGQLFELFSGFLKYFPGAHRQVYKNLQE", "INAYIGHSVEKHRETLDPSAPKDLIDTYLLHMEKEKSNAHSENAHQNLNLNTLSLFFAGT", "ETTSTTLRYGFLLMLKYPHVAERVYREIEQVIGPHRPPELHDRAKMPYTEAVIYEIQRFS", "DLLPMGVPHIVTQHTSFRGYIIPKDTEVFLILSTALHDPHYFEKPDAFNPDHFLDANGAL", "KKTEAFIPFSLGKRICLGEGIARAELFLFFTTILQNFSMASPVAPEDIDLTPQECGVGKI", "PPTYQIRFLPR", sep="")))

![](./nsSNP.png)

The example would generate the comparison of 2 isoforms only (for simplicity) 
but the function would display all the isoforms and their nsSNP frequencies if
provided. The function also returns a vector describing the SNP locations:
[1] "CYP1A2" "1" "CYP1A2" "2" "CYP1A2" "3" "CYP2B6" "283" "CYP2B6" "284"

### 2. snpDist

#### Summary of the function

**snpDist** creates a graphic output of the frequency of nsSNPs for each region
of the provided CYP isoform protein. The regions are divided in groups of 
50 residues.

#### How to use the function

**Parameter Format / Examples**

The parameters include the CYP isoform name to be analyzed (i.e. a string
among CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6 and CYP3A4), and the 
aminoacid sequence (one-letter code) of the corresponding CYP isoform. 

**Example of Using the Function**

We will use now call to the function providing an artificial sequence
for the isoform 1A2:

```r
load(file = "./data/baseSeqs.rda")
snpDist("CYP1A2",
paste("AALSQSVPFSATELLLASAIFCLVFWVLKGLRPRVPKGLKSPPEPWGWPLLGHVLTLGKN",
"LALALSRMSQRYGDVLQIRIGSTPVLVLSRLDTIRQALVRQGDDFKGRPDLYTSTLITDG",
"TFSTFSTDSGPVWAARRRLAQNALNTFSIASDPASSSSCYLEEHVSKEAKALISRLQELM",
"GHFGHFDPYNQVVVSVANVIGAMCFGQHFPESSDEMLSLVKNTHEFVETASSGNPLDFFP",
"PNPALPNPALQRFKAFNQRFLWFLQKTVQEHYQKNSKNSVRDITGALFKHSKKGPRASGN",
"PQPQEKIVNLVNDIFGAGFDTVTTAISWSLMYLVTKPEIQRKIQKELDTVIGRERRPRLS",
"PQPQLPYLEAFILETFRHSSFLPFTIPHSTTRDTTLNGFYIPKKCCVFVNQWQVNHDPEL",
"EEDPSEFRPERFLTADGTAINKPLSEKMMLFGMGKRRCIGEVLAKWEIFLFLAILLQQLE",
"SSVPPGVKVDLTPIYGLTMKHARCEHVQARLRFSIN", sep=""))

{width=90%}

The function return a visualization of the frequency of nsSNPs for each protein region and also a vector with the SNPs count for each region:

0 50 100 150 200 250 300 350 400 450 1 2 3 3 4 3 2 2 1 1

3. snpToDrug

Summary of the function

snpToDrug outputs drugs in clinical use of which metabolism would be potentially disrupted by a critical SNP. The correlation data is sourced from the following:

Drug interaction guideline for drug development and labeling recommendations European Medicines Agency (2013). Guideline on the Investigation of Drug Interactions.

University of Washington Metabolism and Transport Drug Interaction Database [Hachad et al. (2010), Hum Genomics, 5(1):61] by a critical snp at the provided CYP isoform

How to use the function

Parameter Format / Examples

The parameter must be a string containing the canonical name of one of the clinically relevant (according to above sources) CYP isoforms, i.e. CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, or CYP3A4, all provided as a string.

Example of Using the Function

``` {r eval=FALSE} load(file = "./data/drugs.rda") snpToDrug("CYP1A2")

The function return a list of drug with the metabolism potentially disrupted:

CYP1A2 
"omeprazole, lansoprazole, caffeine, tizanidine, fluvoxamine, alosetron, 
duloxetine, melatonin, ramelteon, tasimelteon, tizanidine, clozapine, 
pirfenidone, ramosetron, theophylline, ciprofloxacin, enoxacin, fluvoxamine, 
methoxsalen, mexiletine , estrogen, acyclovir, allopurinol, cimetidine, 
peginterferon alpha-2a, piperine, zileuton, phenytoin, rifampin, ritonavir, 
tobaco, teriflunomide"


## Package References

[Albuquerque A. (2021) snpCYP: An R Package For
  BCB410H. Unpublished.](https://github.com/a-albuquerque/snpCYP)

This vignette format was inspired by Dianna Callister's production:
[McAllister, D. (2020) MethylExpress: An R Package For
  BCB410H. Unpublished.](https://github.com/diannamcallister/MethylExpress)

<br>

## Other References

Adzhubei, I., Jordan, D. M., & Sunyaev, S. R. (2013). Predicting
functional effect of human missense mutations using PolyPhen-2. *Current
Protocols in Human Genetics*, 76 (1), 7–20.

Banerjee, P., Dunkel, M., Kemmler, E., & Preissner, R. (2020).
SuperCYPsPred—a web server for the prediction of cytochrome activity.
*Nucleic Acids Research*, 48 (W1), W580–W585.

DIDB - the drug interaction database. (2021). *UW Drug Interaction
Solutions*. Washinton University.
<https://www.druginteractionsolutions.org/solutions/drug-interaction-database/>

Rostkowski, M., Spjuth, O., & Rydberg, P. (2013). WhichCyp: Prediction
of cytochromes P450 inhibition. *Bioinformatics*, 29 (16), 2051–2052.

Wang, L.-L., Li, Y., & Zhou, S.-F. (2009). A bioinformatics approach for
the phenotype prediction of nonsynonymous single nucleotide
polymorphisms in human cytochromes P450. *Drug Metabolism and
Disposition*  37 (5), 977–991.

Zhang, T., Zhou, Q., Pang, Y., Wang, Y., Jin, C., Huo, J., Liu, L. A., &
Wei, D. (2012). CYP-nsSNP: A specialized database focused on effect of
non-synonymous SNPs on function of CYPs. *Interdisciplinary Sciences:
Computational Life Sciences*, 4 (2), 83–89.

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sessionInfo()

a-albuquerque/snpCYP documentation built on Dec. 18, 2021, 9:23 p.m.