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All the applications are in the bin folder, in there you will find a set of programs ready to use, all of them have the -h option, that shows which are the possible options to run the program. In the following section all the application are explain and also there is at least one example on how to use it.

Biopool library

The Biopool class implementation follows the composite design pattern and for a complete description of the class hierarchy we recommend to see the [Doxygen documentation]. Without going into implementation details a Protein object is just a container for vectors representing chains. Each vector has 2 elements: the Spacer and the Ligand Set. The Spacer is the container for AminoAcid objects whereas the LigandSet is a container for all other molecules and ions, including DNA/RNA chains. Ultimately all molecules, both in the Spacer and in the LigandSet are collections of Atom objects. The main feature in Biopool is that each AminoAcid object in the Spacer is connected to its neighbours by means of one rotational vector plus one translational vector. This implementation make ease the modification of the protein structure and lot of functions were implemented to modify/perturbate/transformate the residue relative position in an efficient way. Rotation and Translation vectors:

The object representation look like that:


Victor includes different packages: Biopool, Lobo and Energy. Every package is identified by a directory, starting with a capital letter, in the main Victor path. Inside each package you will find the Source folder containing the classes code and the APPS directory including useful utilities. In the main path you will find the data folder containing symbolic links to data files used by singular packages. In the main Victor path you should also find the bin directory containing most important programs simply copied from the APPS folders.

Parsing a PDB file (PdbLoader)

Biopool uses the PdbLoader class to load PDB files. By default it loads all standard residues and hetero atoms excluding nucleotides and water molecules. When possible it also tries to place hydrogen atoms to every amino acid included in the spacer and determine the secondary structure with the DSSP algorithm. The simplest way to load a PDB into a Protein object is:

  1.   #include <PdbLoader.h>
  2.   #include <Protein.h>
  3.   #include <iostream>
  5.   int main( int argc, char* argv[] ) {
  7.      string inputFile = "MyPdbFile.pdb";
  8.      ifstream inFile( inputFile.c_str() );
  9.      PdbLoader pl(inFile);    // creates the PdbLoader object
  11.      Protein prot;            
  12.      prot.load( pl );         // creates the Protein object
  13.   }

Modify the structure

Add hydrogen atoms

Get the secondary structure

There are 3 different ways in Victor to get the secondary structure. The first (inaccurate) is just parsing the HELIX and SHEET fields in the PDB file. The second method is to infer the secondary structure from torsional angles. The last choice is to use an implementation of the DSSP algorithm, consider that you can find little (negligible) differences compared to the original algorithm but it is the most accurate way to calculate the secondary structure.


Remember that before trying any of the following applications the environment variables should be set

export VICTOR_ROOT=/<your_folder>/victor2.0/  
export PATH=$PATH:/<your_folder>/victor2.0/bin/ 

How to obtain the solvation potential

pdb2solv is an application that creates a file containing all the frequencies of occurrence of residue a with burial r, that are needed to derived the solvation potentials for all the amino acids in the given PDB. A solvation potential for an amino acid residue a is defined as:

Solvation potential=R*T*ln(fa(r)/f(r)) 

where r is the degree of residue burial,fa(r) is the frequency of occurrence of residue a with burial r. and f(r) is the frequency of occurrence of all residues with burial r.

The degree of burial for a residue is defined as the number of other Cβ atoms located within 10 Å(non polar)/ 7 Å (polar)of the residue’s Cβ atom.

As input a PDB is needed

The output will depend on the given options, considering 30 maximum binds possible (by default test.out, use -o option to set a name)

Non polar output file format

total quantity of residues evaluated | AA type(3L) | frequencies 

Polar output file format

P |  total quantity of residues evaluated | AA type(3L) | frequencies | Polar frequency | 

To obtain the solv.par file used for pdb2energy, frst, etc applications, you need to use the following line with all the pdbs in the TOP500H database.

./pdb2solv -i ../samples/119L.pdb 

More reference "Victor/Frst function for model quality Estimation" GenTHREADER: an efficient and reliable protein fold recognition method for genomic sequences1 David T. Jones The TOP500H database was used to create the file (solv.par)

for a detailed example see pdb2solv example

How to obtain the torsion angles from the PDB residues

The application pdb2tor obtains the set of angle for each residue. As input it uses a PDB file and the corresponding chain, or a file with the PDB ids which can include the chain, if a chain is not included the application uses the first found chain.

Structure of the pdb filelist Uses the first chain for each pdb


To use the corresponding chain for each pdb, need to use the --complete option

PDBID(complete name of the corresponding file) chain 
PDBID chain 
PDBID chain 

if many chains from the same pdb are input, just repeat the PDBid and use a different chain

This application can be used also to generate the tor.par file used for TAP application. To generate it you need to use the following line with the TOP500H database.

./pdb2tor -I ../samples/filelist2_ --complete 

Output format (-A option, Give per residue phi, psi, omega, chi, pre-psi and pre-psi angle)

AA Type(one letter format) | Number | pre-phi | pre-psi | phi | psi | omega | chi1 | chi2

!Total file analyzed: Number of files analyzed

Output format (using -r option)

Numbers of lines in the file

phi | psi | AA type | pre phi | pre psi | omega | #carbons | chi1 | chi2

for a detailed example see pdb2tor example

How to obtain normalized energy from a PDB

The application pdb2torenergy calculates a pseudo-energy to evaluate the quality of a given protein structural model, as expressed in a single (real) number. This program allows you to obtain the normalized energy mentioned in TAP paper.

Input data by default

tor.par , created by pdb2tor using TOP500H database.

To calculate the normalized energy multiple PDBs and PDB chain(s) can be used

Output Depending of the options the energy can be calculated for all the chain residues or for each of them. Per residue, one energy for each of the residues in the pdb

./pdb2torenergy -i ../samples/119L.pdb --allchains -p 

Per pdb(one energy value)

./pdb2torenergy -i ../samples/119L.pdb --allchains 

For chain A in each model each model(many energy values as models in the pdb file)

./pdb2torenergy -i ../samples/1IHQ.pdb -c A 

for a detailed example see pdb2torenergy example

How to obtain FRST value from a PDB

The application frst allows to calculates the frst value using solvation potential, torsion angles, rapfdf . To use this application some input files are needed. All this mentioned files can be generated using another energy/lobo applications or you can use the already generated ones saved in the victor2.0/data folder.

Default Input files

tor.par, created by pdb2tor using TOP500H database
solv.par created by pdb2solv using TOP500H database

Output format

The application prints the value of frst for the given pdb if use the option -v it will print also the values of Rapdf energy, Solvation energy, Mainchain hydrogen bonds ,Torsion energy .

To calculate the average over a chain in a NMR ensemble

./frst -i ../samples/16PK.pdb  

To calculate the average over many pdb files

./frst -I ../samples/filelist

for a detailed example see frst example

How to obtain TAP value from a PDB

The pdb2tap application allows to evaluate the quality of a model, using TAP method (). Used for the evaluation of the quality of protein models determined by X-ray crystallography. The method is based on a relative pseudo-energy calculated from the side chain torsion angle propensities and the backbone, both then are normalized against the global minimum and maximum for the protein sequence under consideration.


Torsion angle potential (based on frst) 
Pseudo Energy i, maximum and minimum 
TAP = (E-Emin)/(Emax-Emin) 

Known as normalized torsion angle propensity, gives a indication of the degree of nativeness of the protein model.

Initial default data (can be created with pdb2tor)

The file tor.par is used to calculate the TAP value, this file can be created with the pdb2tor application,and by default is 
created using the TOP500H database.
tor.par: file containing all torsion angles available from TOP500H database. 

For more reference see:

For the database 
TOP500H is the list of 500 proteins used for the Ramachandran plot distributions, with File ID {PDB code + chainID 
(if not the full PDB  file) + H (to signify H's added), structure factor deposition status, resolution, and protein name. 
500High resolution xRay resolved to 1.8 A or more and less than 60%seq ident.609NMR structures(9578 models)
For method
Fine-grained statistical torsion angle potentials are effective in discriminating native protein structures. PMID: 16712465 
[PubMed - indexed for MEDLINE] 

Output format

A plain text file containing:

Numbers of lines in the file

phi | psi | AA type | pre phi | pre psi | omega | #carbons | chi1 | chi2

Output interpretation:

Value close to 1 for a native structure 
Value close to 0 for a largely incompatible sequence. 

Input data

The application can be used with one or many PDBs and PDB chains.

Single structure Xray using one chain:

./pdb2tap -i ../samples/102M.pdb -c A   

Output: Prints the tap value, as shown in http://www.biomedcentral.com/content/supplementary/1471-2105-8-155-s1.txt

Single structure Xray using all chains(all chains in pdb):

./pdb2tap -i ../samples/1A3W.pdb -P sal  --allchains as shown in 				

Output: Prints the tap value average value for all chains. http://www.biomedcentral.com/content/supplementary/1471-2105-8-155-s1.txt

Multiple models NMR using one chain:

./pdb2tap -i ../samples/1IHQ.pdb -P sal -c A --nmr 

Output: Prints the tap value for the selected for each model, the average tap value for all models, standard Deviation, minimum and maximum tap value.

Multiple models NMR using all chains(all chains in pdb):

./pdb2tap -i ../samples/1IHQ.pdb -P sal --allchains --nmr 

Output: Prints the tap value average value for all chains in each model, the average tap value for all models, standard Deviation, minimum and maximum tap value.

for a detailed example see pdb2tap example


Lobo is a Loop Modeling software that uses pre-calculated Look-Up Tables (LUTs) that represent loop fragments of various sizes to speed up calculation. LUTs can be generated once and stored, only requiring loading during loop modeling.

Conformations are produced by recursively dividing the segment until the backbone coordinates can be derived analytically.


Remember that before trying any of the following applications the environment variables should be set. Be careful to add the final "/" to the path.

export VICTOR_ROOT=/<your_folder>/victor2.0/  
export PATH=$PATH:/<your_folder>/victor2.0/bin/

How to create a LUT

The construction of the LUTs is separated from modelling and has to be executed only once. LoboLUT is the program necessary to create a look-up table of a specific length. To create a LUT to model loops of length N, first is necessary to create LUTs from size 2 to N/2. In any case the application would create a binary file containing the corresponding values for the selected length.

Create a first LUT of length 2:

loboLUT -A 1 -B 1 -O aa2.lt --table <destination path>/ -R data/tor.par

Add 1 residue:

loboLUT -A aa2.lt -B 1 -O aa3.lt --table <destination path>/ -R data/tor.par

Create a table of length 4 combining two smaller LUTs.

loboLUT -A aa2.lt -B aa2.lt -O aa4.lt --table <destination path>/ -R data/tor.par

To avoid the annoying task of creating all LUT tables by hand you can use LoboLUT_all that will do the task for you automatically.

N.B. Remember you set the VICTOR_ROOT path to select a convenient destination path.

How to create LUTs for a fragment of size N

LoboLUT_all is a perl script used to automatically generate all the necessary LUTs for modelling a fragment of length N. For example, to create LUTs for a fragment of length 5 you can run the following command:

loboLUT_all -c 5 

This will create LUTs for fragments of length 2, 3 and 5. For more details see also loboLUT_all example

How to identify loops in PDBs

CreateLoopTestset is a program that allows you to model a single loop. It gives the user full flexibility about the setting of parameters for ranking and modelling. It finds the starting and ending positions in a single o multiple PDB files. Its output can be used to model the loop with the LoopModelTest application. To obtain the list of starting and ending points:

createLoopTestset -o listLoops -i samples/filelist 

Where the content in filelist is for example:


The output will be:

index1 (-s): 9 index2 (-e) 13
index1 (-s): 44 index2 (-e) 49
index1 (-s): 52 index2 (-e) 57
index1 (-s): 62 index2 (-e) 70

Where the (-s) and (-e) are the starting and ending position respectively. For a detailed example see createLoopTestset example

Generate compatible plots

The LUT standard format is binary both for performance and space efficiency reasons. LoopTablePlot is a different application necessary generate compatible plots of protein entries for the Lobo algorithm based on the LUT. For example, to generate the corresponding plot for the LUT aa5.lt (created previously):

./LoopTablePlot -i aa5.lt  -o <plot output file> -s l 

The output file contains the list of values to plot. The s option allows to define the numerical precision (small=s, medium=m, large=l) of course strongly affecting the storage size.

for a detailed example see LoopTablePlot example

How to model a loop

LoopModelTest allows to generate possible loop conformations and creates a PDB file for each solution:

./LoopModelTest -i ../samples/<pdb_file.pdb> -c A -s X -e Y

Where X and Y are the start and end positions obtained by CreateLoopTestset and -c A tells the program to work on the chain A of an specific PDB file: Using the information obtained with the app CreateLoopTestset ./LoopModelTest -i ../samples/119L.pdb -c A -s 7 -e 14 Remember to create the lookup table for a 7 length fragment using ./loboLUT_all -c 7

The new pdbs files fill be created in the working path, and in the printed output will be shown the global RMS, end RMS, bond lenght, bond angle and torsion angle

Printed output Results: 1.35 121 180

 0   global RMS=  0.416   ( 0.366)	end-RMS=  0.234	    1.17     126     175 
 1   global RMS=  0.356   ( 0.295)	end-RMS= 0.0822	    1.38     121    -176 

for a detailed example see LoopModelTest example

How to obtain a PDB`s torsion angles

Loop2torsion is a c++ program that allows to obtain all the phi and psi angles of all the amino acids in a selected PDB chain .

To obtain the angles a PDB file is needed as input and also the chain should be specified

   ./loop2torsion -i ../samples/2R8O.pdb -c A  

The printed output is the list of the angles and the Bfactor of 1.

  -72.1     157    1.0 
   -165     142    1.0 
    122    -172    1.0 
   -126    98.1    1.0 

How to Clustering data

Using the tor file created in Energy package, ClusterRama, a c++ program clusters the data contained in a Ramachandran distribution file To obtain the clustered data using a cutoff value of 100

   ./ClusterRama -i ../data/tor.par -o outRama -c 100.0 

The output contains the number of the values found the angles values and the corresponding residue 12

-55.07    -44.61   GLY 
 76.11    -172.4   GLY 
-139.2       129   GLY 

for a detailed example see ClusterRama example

How to generate clustered lookup tables

Based in the clustered data the LoopTableTest c++ program generates tables of protein entries for the Lobo algorithm .
   ./LoopTableTest -A 1 -B 1 -O output.lt -R outRama -S s 
To create the Ramachandran input file that contains the clustered data use ClusterRama application. 

The output created is not a plan text file, use the LoopTablePlot application The printed output, includes the corresponding angle values (see figure) Min: EP: -4.126 ED: -1.281 N: -0.9997 MP: -1.582 MD: -0.4919 MN: -0.9949 EP: 2.6 ED: -1.332 N: -1 MP: 1.521 MD: 0.4671 MN: -0.8217 EP: -3.966 ED: -1.289 N: -0.9836 MP: -1.598 MD: -0.7378 MN: -0.5885 Max: EP: 3.437 ED: 1.022 N: 0.6597 MP: 0.9131 MD: 0.5203 MN: 0.8068 EP: 4.856 ED: 0.1761 N: 0.6105 MP: 2.486 MD: 0.9987 MN: 0.6888 EP: 3.592 ED: 1.27 N: 0.9813 MP: 1.307 MD: 0.8342 MN: 0.7185

Entry 0 EP: -2.737 ED: -0.01248 N: -0.02252 MP: -0.8014 MD: 0.2146 MN: 0.6219 EP: 2.699 ED: -1.172 N: 0.5104 MP: 1.879 MD: 0.921 MN: -0.3856 EP: 1.984 ED: -0.6955 N: -0.8596 MP: 1.022 MD: 0.3252 MN: 0.6816

for a detailed example see LoopTableTest example

How to generate lookup tables using Ramachandran`s clustered data

Based on a lookup table already created with LoboLUT/loboLUT_all and defining a cutoff value. The ClusterLoopTable program allows you to create the new clustered lookuptable. In this example, a cutoff of 10 is set, and it uses the lookup table for a length of 5.

   ./ClusterLoopTable -I ../data/aa5.lt -O ../data/aa5clustered.lt -C 10.0 

The created output is not a plain text file, to see the content use the LoopTablePlot application

for a detailed example see ClusterLoopTable example

How to analyze the backbone geometry of a PDB

BackboneAnalyzer is an application that allows to analyze a PDB file in terms of bond lengths and bond angles . As input it uses the PDB file and the chain to evaluate

      ./backboneAnalyzer -i ../samples/2R8O.pdb -c A 

The printed output includes the minimum, maximum, average bonds lengths and angles and the corresponding standard deviations.

Bond Lengths Bond Angles Num N->CA CA->C' C'->N N->CA CA->C' C'->N

Min: 1.4450 1.5019 1.3206 116.87 104.83 112.55 Max: 1.4804 1.5479 4.0701 158.03 118.34 158.56

Avg: 1.4636 1.5272 1.3505 121.58 111.71 116.73 SD: 0.0054 0.0067 0.2074 2.45 2.16 1.98

for a detailed example see backboneAnalyzer example