How to estimate and compute the isoelectric point of peptides and proteins?

By +Yasset Perez-Riverol and +Enrique Audain :

Isoelectric point (pI) can be defined as the point of singularity in a titration curve, corresponding to the solution pH value at which the net overall surface charge is equal to zero. Currently, there are available different modern analytical biochemistry and proteomics methods depend on the isoelectric point as a principal feature for protein and peptide characterization. Peptide/Protein fractionation according to their pI is widely used in current proteomics sample preparation procedures previous to the LC-MS/MS analysis. The experimental pI records generated by pI-based fractionation procedures are a valuable information to validate the confidence of the identifications, to remove false positive and and could be used to re-compute peptide/protein posterior error probabilities in MS-based proteomics experiments. 

Theses approaches require an accurate  theoretical prediction of pI. Even thought there are several tools/methods to predict the isoelectric point, it remains hard to define beforehand what methods perform well on a specific dataset.  

We believe that the best way to compute the isoelectric point (pI) is to have a complete package with most of the algorithms and methods in the state of the art that can do the job for you [2]. We recently developed an R package (pIR) to compute isoelectric point using long-standing and novels pI methods that can be grouped in three main categories : a) iterative, b) Bjellvist-based methods and c) machine learning methods. In addition, pIR also offers a statistical and graphical framework to evaluate the performance of each method and its capability to “detect” outliers (those peptides/protein with theoretical pI biased from experimental value) in a high-throughput environment.

First lets install the package:

First, we need to install devtools:

install.packages("devtools")
library(devtools)

Then we just call:

install_github("ypriverol/pIR")
library(pIR)

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#http://www.htslib.org/workflow/#mapping_to_variant
set -xeu

FQ1=y1.fastq
FQ2=y2.fastq
REF=yeast.fasta
BNM=yeastD

RUNINDOCKER=1

SAMTOOLS=samtools
BWA=bwa
TABIX=tabix
BCFTOOLS=bcftools
PLOTVCFSTATS=plot-vcfstats

if [[ "$RUNINDOCKER" -eq "1" ]]; then
echo "RUNNING IN DOCKER"
DRUN="docker run --rm -v $PWD:/data --workdir /data -i"
#--user=biodocker

SAMTOOLS_IMAGE=biodckr/samtools
BWA_IMAGE=biodckr/bwa
TABIX_IMAGE=biodckrdev/htslib:1.2.1
BCFTOOLS_IMAGE=biodckr/bcftools


docker pull $SAMTOOLS_IMAGE
docker pull $BWA_IMAGE
docker pull $TABIX_IMAGE
docker pull $BCFTOOLS_IMAGE

SAMTOOLS="$DRUN $SAMTOOLS_IMAGE $SAMTOOLS"
BWA="$DRUN $BWA_IMAGE $BWA"
TABIX="$DRUN $TABIX_IMAGE $TABIX"
BCFTOOLS="$DRUN $BCFTOOLS_IMAGE $BCFTOOLS"
PLOTVCFSTATS="$DRUN $BCFTOOLS_IMAGE $PLOTVCFSTATS"
else
echo "RUNNING LOCAL"
fi

HEADLEN=100000

if [[ ! -f "$FQ1" ]]; then
curl ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR507/SRR507778/SRR507778_1.fastq.gz| gzip -d | head -$HEADLEN > $FQ1.tmp && mv $FQ1.tmp $FQ1
fi

if [[ ! -f "$FQ2" ]]; then
curl ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR507/SRR507778/SRR507778_2.fastq.gz| gzip -d | head -$HEADLEN > $FQ2.tmp && mv $FQ2.tmp $FQ2
fi

if [[ ! -f "$REF" ]]; then
curl ftp://ftp.ensembl.org/pub/current_fasta/saccharomyces_cerevisiae/dna/Saccharomyces_cerevisiae.R64-1-1.dna_sm.toplevel.fa.gz | gunzip -c > $REF.tmp && mv $REF.tmp $REF
fi

if [[ ! -f "$REF.fai" ]]; then
$SAMTOOLS faidx $REF
fi

if [[ ! -f "$REF.bwt" ]]; then
$BWA index $REF
fi

if [[ ! -f "$BNM.sam" ]]; then
$BWA mem -R '@RG\tID:foo\tSM:bar\tLB:library1' $REF $FQ1 $FQ2 > $BNM.sam.tmp && mv $BNM.sam.tmp $BNM.sam
fi

if [[ ! -f "$BNM.bam" ]]; then
#$SAMTOOLS sort -O bam -T /tmp -l 0 --input-fmt-option SAM -o $BNM.tmp.bam $BNM.sam && mv $BNM.tmp.bam $BNM.bam
$SAMTOOLS sort -O bam -T /tmp -l 0 -o $BNM.tmp.bam $BNM.sam && mv $BNM.tmp.bam $BNM.bam
fi

if [[ ! -f "$BNM.cram" ]]; then
$SAMTOOLS view -T $REF -C -o $BNM.tmp.cram $BNM.bam && mv $BNM.tmp.cram $BNM.cram
fi

if [[ ! -f "$BNM.P.cram" ]]; then
$BWA mem $REF $FQ1 $FQ2 | \
$SAMTOOLS sort -O bam -l 0 -T /tmp - | \
$SAMTOOLS view -T $REF -C -o $BNM.P.tmp.cram - && mv $BNM.P.tmp.cram $BNM.P.cram
fi

#if [[ ! -f "" ]]; then
#$SAMTOOLS view $BNM.cram
#fi

#if [[ ! -f "" ]]; then
#$SAMTOOLS mpileup -f $REF $BNM.cram
#fi

if [[ ! -f "$BNM.vcf.gz" ]]; then
$SAMTOOLS mpileup -ugf $REF $BNM.bam | $BCFTOOLS call -vmO z -o $BNM.vcf.gz.tmp && mv $BNM.vcf.gz.tmp $BNM.vcf.gz
fi

if [[ ! -f "$BNM.vcf.gz.tbi" ]]; then
$TABIX -p vcf $BNM.vcf.gz
fi

if [[ ! -f "$BNM.vcf.gz.stats" ]]; then
$BCFTOOLS stats -F $REF -s - $BNM.vcf.gz > $BNM.vcf.gz.stats.tmp && mv $BNM.vcf.gz.stats.tmp $BNM.vcf.gz.stats
fi

mkdir plots &>/dev/null || true

#if [[ ! -f "plots/tstv_by_sample.0.png" ]]; then
#$PLOTVCFSTATS -p plots/ $BNM.vcf.gz.stats
#fi

if [[ ! -f "$BNM.vcf.filtered.gz" ]]; then
$BCFTOOLS filter -O z -o $BNM.vcf.filtered.gz -s LOWQUAL -i'%QUAL>10' $BNM.vcf.gz
fi