SNAP2

SNAP2 is a method that predicts the effects of single amino acid substitutions in a protein on the protein's function using neural networks. A webservice is currently provided by the Rostlab (https://rostlab.org/services/snap/ and https://rostlab.org/services/snap2web/). The implementation started in November 2011 by Maximilian Hecht. Perl is the programming language.

License

The software is licensed under an Academic Software License Agreement.

HOWTO Install

The recommended and tested environment is Debian Wheezy (7). See the wiki for instructions on other environments and more details about the installation process and dependencies. Furthermore, see these wiki page for on instructions on how to set up a virtual machine if needed.

Install essentials and add rostlab repository:

cd ~
sudo apt-get update
sudo apt-get install csh vim wget build-essential devscripts debhelper devscripts python-software-properties
sudo apt-add-repository "deb http://rostlab.org/debian/ stable main contrib non-free"
sudo apt-get update
sudo apt-get install rostlab-debian-keyring
sudo apt-get update

Install blimps the hard way:

wget https://launchpad.net/debian/+archive/primary/+files/blimps_3.9-1.dsc
wget https://launchpad.net/debian/+archive/primary/+files/blimps_3.9.orig.tar.gz
wget https://launchpad.net/debian/+archive/primary/+files/blimps_3.9-1.debian.tar.gz
tar xzvf blimps_3.9.orig.tar.gz
tar xzvf blimps_3.9-1.debian.tar.gz
mv debian blimps-3.9/
mv blimps_3.9-1.dsc  blimps-3.9/
cd blimps-3.9
dpkg-source --commit
# -> add a patch name -> ctrl+o -> return -> ctrl+x
debuild -us -uc
cd ..
sudo dpkg -i \*blimps\*.deb

Install sift the hard way:

wget http://rostlab.org/debian/pool/non-free/s/sift/sift_4.0.3b-4.debian.tar.gz
wget http://rostlab.org/debian/pool/non-free/s/sift/sift_4.0.3b-4.dsc
wget http://rostlab.org/debian/pool/non-free/s/sift/sift_4.0.3b.orig.tar.gz
tar xzvf sift_4.0.3b.orig.tar.gz
mv sift_4.0.3b-4.dsc sift4.0.3b/
tar xzvf sift_4.0.3b-4.debian.tar.gz
mv debian sift4.0.3b/
cd sift4.0.3b/
dpkg-source --commit
# -> add a patch name -> ctrl+o -> return -> ctrl+x
debuild -us -uc
cd ..
sudo dpkg -i sift*.deb

Install snap2 via aptitude:

sudo apt-get install snap2

HOWTO get and configure databases

Complete these steps after installing SNAP2 (on your VM). Ensure that there is enough space on your (virtual) machine. Depending on the type of database you want to use, you will need up to 110 GB disk space. If you initialized a vagrant box with default settings, you might want to use an external hard drive and forward it to the virtual machine. On the tested System (Mac OS X 10.10 and debain/wheezy64 in box), USB port forwarding was disabled and not possible to be used. To use the hard drive as shared folder, configure the virtualmachine in Vagrantfile (on your local machine) as follows, whereas $host_folder_path and $guest_folder_path are the folders on the local and virtual system, respectively:

Vagrant.configure(2) do |config|
	config.vm.synced_folder "$host_folder_path", "$guest_folder_path"
end

Then download and unzip the single databases to the folder of your choice on your local machine (cd $host_folder_path):

swiss_dat

wget ftp://ftp.uniprot.org/pub/databases/uniprot/knowledgebase/uniprot_sprot.dat.gz
gunzip uniprot_sprot.dat.gz

uniref100, uniref90, swissprot

wget ftp://ftp.uniprot.org/pub/databases/uniprot/uniref/uniref100/uniref100.fasta.gz
gunzip uniref100.fasta.gz
wget ftp://ftp.uniprot.org/pub/databases/uniprot/uniref/uniref90/uniref90.fasta.gz
gunzip uniref90.fasta.gz
wget ftp://ftp.uniprot.org/pub/databases/uniprot/knowledgebase/uniprot_sprot.fasta.gz
gunzip uniprot_sprot.fasta.gz

generate db_swiss:

/usr/share/librg-utils-perl/dbSwiss --datadir ./ --infile ./uniprot_sprot.dat --table dbswiss

format fasta databases for use with blast on the virtual machine if used (formatdbwas already installed as a dependency of SNAP2)

formatdb -i uniref100.fasta
formatdb -i uniref90.fasta
formatdb -i uniprot_sprot.fasta

HOWTO configure the tool

There is a config file, containing all necessary data in /usr/share/snap2/snap2rc.default. Copy that file to your homefolder and change its contents to adjust the settings.

cp /usr/share/snap2/snap2rc.default ~/.snap2rc
vim ~/.snap2rc

Most default settings are ok, but check the last paragraphs. They should state the locations of the recently downloaded databases. Edit the file to your needs, e.g.

[data]
# swiss_dat=path - location of UniProt/Swiss-Prot dat file
swiss_dat=/home/snap_db/uniprot_sprot.dat
# db_swiss=path - path to ID index of Swiss-Prot dat file (generated by /usr/share/librg-utils-perl/dbSwiss.pl)
db_swiss=/home/snap_db/dbswiss
# PHAT substitution matrix
phat_matrix=/usr/share/snap2/phat.txt

[blast]
# big80=path - path to redundancy reduced database (UniProtKB 80 or equivalent)
big80=/home/snap_db/big80.fasta
# swiss=path - path to SwissProt database
swiss=/home/snap_db/uniprot_sprot.fasta

Note, however, that given the standard configuration of predictprotein at /usr/share/predictprotein/predictproteinrc.default, the tool still throws an error.

HOWTO workaround the "runtime" error due to probable configuration errors

• download a predictprotein virtual machine image (https://rostlab.org/services/ppmi/)
• download the database set, which is offer as download together with the image
• get the virtual machine to run
• make the databases available inside the virtual machine
• change all paths in /usr/share/predictprotein/predictproteinrc.default and /usr/share/snap2/snap2rc.default to the databases, you made available to the virtual machine

Make sure to generate the machine on a strong enough hardware, as snap2 uses a lot of memory.

HOWTO Run

HOWTO Use the Web Service

The service can be accessed via https://rostlab.org/services/snap/ and https://rostlab.org/services/snap2web/. (Exactly) One protein sequence in the Fasta format can be pasted into the textfield. Upon submission via Run Prediction, a popup shows up, presenting an adress, which leads to the result page, once the calculations are done.

The result page shows a heatmap with the input sequence along the x-axis and all 20 possible amino acid exchanges along the y-axis. Below the heatmap, the color code for the heatmap is presented. Red indicates an effect of the respective amino acid exchange, whereas blue predicts the exchange to be neutral with respect to the proteins function.

A sliding window enables the user to zoom into the heatmap. The zoom area is shown below the interpretation scale. Further down, a table presents all possible amiono acid exchanges at every position with the exact numerical scores and estimated accuracy.

For detailed information about the method, its results, and interpretations, refer to the method description below.

HOWTO Use the CLI Tool

• Input: Fasta Protein Sequence
• Output: Prediction Score between -100 (neutral) and 100 (effect) for every possible SNP at every position

snap2 -i /usr/share/doc/snap2/examples/MT4_HUMAN.fasta -m all -o MT4_HUMAN.snap2

• -i specifies the input file with a sequence in fasta format
• -m specifies the effects at which positions and mutations at this position are to be predicted. With all, all possible positions and mutations are considered
• -o textual output of snap2, containing a prediction score between -100 (neutral) and 100(effect) for every defined position and mutation of the input sequence

Method Description

• Author: Maximilian Hecht
• Year of public: 2015
• Description
  • feature calculation (using predict protein pipeline)
  • neural network with 650 input, 100 hidden and 2 output nodes
  • all 10 models from 10-fold cross validation used to calculate the results
  • 10 results averaged in jury decision

Publications and other Resources

• Hecht, M., Bromberg, Y., & Rost, B. (2015). Better prediction of functional effects for sequence variants. BMC Genomics, 16(Suppl 8), S1 PubMed Full PDF
• Bromberg Y & Rost B. (2007). SNAP: predict effect of non-synonymous polymorphisms on function. Nucleic Acids Research, Vol. 35, No. 11 3823-3835 PubMed Full PDF
• Hecht, M., Bromberg, Y., & Rost, B. (2013). News from the protein mutability landscape. Journal of molecular biology, 425(21), 3937-3948 PubMed Full PDF
• SNAP2 Wiki by Rostlab.org (https://rostlab.org/owiki/index.php/Snap2)

Training / Test data

About 100,000 variants from the Protein Mutant Database (PMD), SwissProt, OMIM and HumVar are used for testing and training of SNAP2. The variants are either classified as 'neutral' or 'effect'.

If a variant is annotated with 'no change' in PMD, the variant is classified as neutral. If there is any change in its function independent of in- or decrease, it is classified as effect. The function of enzymes that are listed in SwissProt is descibed by the Enzyme Commission (EC) number. If two variants have the same EC number, they are classified as neutral. The databases OMIM and HumVar contain protein variants that are associated with diseases. Therefore, they provide variants with an effect.

Evaluation

SNAP2 was compared with the original version SNAP, SIFT, and PolyPhen-2