INSTALLATION AND IMPLEMENTATION OF I-TASSER SUITE
(Copyright 2022 by Zhang Lab, University of Michigan, All rights reserved)
(Version 5.2, 2022/03/24)

1. What is I-TASSER Suite?

The I-TASSER Suite is a composite package of programs for protein
structure prediction and function annotations. The Suite
includes the following programs:

a) I-TASSER: A hierarchical program for protein structure prediction
b) COACH: A function annotation program based on COFACTOR, TM-SITE and S-SITE
c) COFACTOR: A program for ligand-binding site, EC number & GO term prediction
d) TM-SITE: A structure-based approach for ligand-binding site prediction
e) S-SITE: A sequence-based approach for ligand-binding site prediction
f) MUSTER: A threading program for protein template identification
g) LOMETS: A meta-server approach consisting of multiple threading programs
h) SPICKER: A clustering program for structure decoy selection
i) HAAD: Quickly adding hydrogen atoms to protein heavy atom structure
j) EDTSurf: Construct triangulated surfaces of protein molecules
k) ModRefiner: Construct and refine atomic model from C-alpha traces
l) NWalign: Protein sequence alignments by Needleman-Wunsch algorithm
m) PSSpred: A program for Protein Secondary Structure PREDiction
n) ResQ: An algorithm to estimate B-factor and residue-level error of models

2. How to install the I-TASSER Suite?

a) download the I-TASSER Suite 'I-TASSER5.0.tar.bz2' from
http://zhanglab.ccmb.med.umich.edu/I-TASSER/download
and unpack 'I-TASSER5.0.tar.bz2 by
> tar -xvf I-TASSER5.0.tar.bz2
The root path of this package is called $pkgdir, e.g.
/home/yourname/I-TASSER5.0. You should have all the programs under this
directory. You can install the package at any location on your computer.

b) Download I-TASSER and COACH library files from
http://zhanglab.ccmb.med.umich.edu/library/
http://zhanglab.ccmb.med.umich.edu/BioLiP/
A script 'download_lib.pl' is provided in the package for automated
library download and update of the libraries.
We recommend putting the library files under the path /home/yourname/ITLIB.

c) Third-party software installation:

While the majority of programs in the package 'I-TASSER5.0.tar.bz2' are
developed in the Zhang Lab herein the permission of use is released,
there are some programs and databases (including blast, nr and GOparser)
which were developed by third-party groups. A default version of blast
and nr are included in the package. It is user's obligation to obtain
license permission from the developers for all the third-party software
before using them. A detailed list of addresses and guidance for install
these programs can be seen at
http://zhanglab.ccmb.med.umich.edu/I-TASSER/addition.
In addition, your system needs to have Java installed.

3. Bug report:

Please report and post bugs and suggestions at I-TASSER message board:
http://zhanglab.ccmb.med.umich.edu/bbs/?q=forum/2

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# 4. Installation and implementation of I-TASSER #
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4.1. Introduction of I-TASSER

I-TASSER is an integrated package for protein structure and function
predictions. For a given sequence, I-TASSER first identifies template proteins
from the Protein Data Bank (PDB) by multiple threading techniques (LOMETS).
The continuous fragments excised from the template alignments are used to
assemble full-length models by iterative Monte Carlo simulations. The best
models are then selected from the Monte Carlo trajectories by decoy
clustering. The final atomic models are rebuilt from the structure clusters
by atomic-level structural refinements.

For function annotation, the I-TASSER structure model is matched through
the function library (BioLiP) to identify functional template. The biological
insights (including ligand-binding, enzyme classification, and gene ontology)
are inferred from the functional templates by COACH based on the consensus
of predictions from COFACTOR, TM-SITE and S-SITE.

4.2. How to run I-TASSER?

a) Main script for running I-TASSER is $pkgdir/I-TASSERmod/runI-TASSER.pl.
Run it directly without arguments will output the help information.

b) The following arguments must be set (mandatory arguments). One example is:

"$pkgdir/I-TASSERmod/runI-TASSER.pl -libdir /home/yourname/ITLIB -seqname example -datadir /home/yourname/I-TASSER5.0/example"

-libdir means the path of the template libraries
-seqname means the unique name of your query sequence
-datadir means the directory which contains your sequence

c) Other arguments are optional whose default values have been set.
User can reset one or more of them. One example of command line is:

"$pkgdir/I-TASSERmod/runI-TASSER.pl -pkgdir /home/yourname/I-TASSER5.0 -libdir /home/yourname/ITLIB -seqname example -datadir /home/yourname/I-TASSER5.0/example -runstyle parallel -homoflag benchmark -idcut 0.3 -LBS true -EC true -GO true -java_home /usr"

-pkgdir means the path of the I-TASSER package. default is to
guess by the location of runI-TASSER.pl script
-java_home means the path contains the java executable "bin/java"
(your system needs to have Java installed)
-runstyle default value is "serial" which means running I-TASSER
simulation sequentially.
"parallel" means running parallel simulation jobs in the
cluster using PBS/torque job scheduling system.
"gnuparallel" means running parallel simulation jobs on
one computer with multiple cores using GNU parallel
-homoflag [real, benchmark],"real" will use all templates, "benchmark"
will exclude homologous templates
-idcut sequence identity cutoff for "benchmark" runs, default
value is 0.3, range is in [0,1]
-ntemp number of top templates output for each threading program,
default is 20, range is in [1,50]
-nmodel number of final models output by I-TASSER, default value
is 5, range is in [1,10]
-LBS [false or true], whether to predict ligand-binding site, default is false
-EC [false or true], whether to predict EC number, default is false
-GO [false or true], whether to predict GO terms, default is false
-restraint1 specify distance/contact restraints (read more at
http://zhanglab.ccmb.med.umich.edu/I-TASSER/option1.html )
-restraint2 specify template with alignment (read more at
http://zhanglab.ccmb.med.umich.edu/I-TASSER/option4.html )
-restraint3 specify template name without alignment (read more at
http://zhanglab.ccmb.med.umich.edu/I-TASSER/option2.html )
-restraint4 specify template file without alignment (read more at
http://zhanglab.ccmb.med.umich.edu/I-TASSER/option3.html )
-temp_excl exclude specific templates from template library (read more
at http://zhanglab.ccmb.med.umich.edu/I-TASSER/option6.html )
-traj this option means to deposit the trajectory files
-light this option means to run I-TASSER in fast mode (each
simulation runs by default 5 hours maximum)
-hours specify maximum hours of simulations (default=5 when -light=true)
-outdir where the final results should be saved (default value is set to data_dir)

d) To make HTML webpage for I-TASSER suite output, follow document at
$pkgdir/file2html/readme

NOTE:
a) Outline of steps for running I-TASSER by 'runI-TASSER.pl':
a1) standardize 'seq.fasta' to 'seq.txt' and get the sequence length
a2) run 'psiblast' to generate 'chk', 'out', 'pssm', 'mtx' files
run 'PSSpred' to get 'seq.dat', 'seq.dat.ss'
run 'solve' to get 'exp.dat'
run 'pairmod' to get 'pair1.dat' and 'pair3.dat'
a3) run threading programs sequentially
run 'mkinit.pl' to generate restraints
a4) run I-TASSER simulation
a5) run SPICKER clustering program
run 'get_cscore.pl' to get confidence score
run 'EMrefinement.pl' to get full-atomic models
run 'get_rsq_bfp.pl' to get local accuracy and B-factor estimations
a6) run 'runCOACH.pl' to generate ligand-binding sites, EC number and
GO terms predictions.
b) 'seq.fasta' is the query sequence file in FASTA format, which is the
only needed input file for running I-TASSER. This file should be
put in $datadir before running this job.
c) I-TASSER structure assembly simulations contains 14 independent
runs by default. This number can be modified if the user wants to run
more simulations, especially for big protein without good templates.
d) If working on a cluster with multiple nodes, it is recommended to set
$runstyle="parallel". You need have PBS server installed in your system.
Parallel jobs will run faster since jobs are distributed among different
nodes. The default setting $runstyle="serial" will run all the jobs on a
single computer.
e) If the job has been executed partially and encounter some error, you can
rerun the main script without modification. It will check the existing
files and start from the correct position.

4.3 System requirement:

a) x86_64 machine, Linux kernel OS, Free disk space of more than 60G.
b) Perl and java interpreters should be installed. GO:Parser should be installed
if you want to predict GO terms
c) Basic compress and decompress package should be installed to support:
tar and bunzip2.
d) If you are using computer clusters, job management software PBS server should
support 'qsub' and 'qstat'. If using other job management software, such as
SGE and Slurm, some changes should be made following the instructions at:
http://zhanglab.ccmb.med.umich.edu/bbs/?q=node/3561

4.4. How to cite I-TASSER and I-TASSER Suite?

If you are using the I-TASSER package, you can cite:

1. Y Zhang. I-TASSER server for protein 3D structure prediction.
BMC Bioinformatics, 9: 40 (2008).
2. A Roy, A Kucukural, Y Zhang. I-TASSER: a unified platform
for automated protein structure and function prediction.
Nature Protocols, 5: 725-738 (2010).
3. J Yang, R Yan, A Roy, D Xu, J Poisson, Y Zhang. The I-TASSER Suite: Protein structure
and function prediction. Nature Methods, 12: 7-8 (2015)

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# 5. Installation and implementation of MUSTER #
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5.1. Introduction of MUSTER

MUSTER (MUlti-Sources ThreadER) is a protein threading algorithm to
identify the template structures from the PDB library. It generates
sequence-template alignments by combining sequence profile-profile
alignment with multiple structural information.

5.2. How to install MUSTER program?

When you unpack the I-TASSER Suite, MUSTER program is already installed.

5.3. How to run MUSTER program?

The MUSTER main script is $pkgdir/I-TASSERmod/runMUSTER.pl. The running
option of this program is similar to that in runI-TASSER.pl. By running
the program without argument, you can print all the running options.

5.4. How to cite MUSTER?

If you are using the MUSTER program, you can cite:

S Wu, Y Zhang. MUSTER: Improving protein sequence profile-profile
alignments by using multiple sources of structure information.
Proteins, 72: 547-556 (2008).

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# 6. Installation and implementation of LOMETS #
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6.1. Introduction of LOMETS

LOMETS (Local Meta-Threading-Server) is meta-server approach to protein
fold-recognition. It consists of 8 individual threading programs: MUSTER,
PPA, dPPA, dPPA2, sPPA, wPPA, wdPPA, wMUSTER. The last 7 programs are
variances of MUSTER which includes different optimized energy terms.

6.2. How to install LOMETS program?

When you unpack the I-TASSER Suite, LOMETS programs are already installed.

6.3. How to run LOMETS program?

The LOMETS main script is $pkgdir/I-TASSERmod/runLOMETS.pl. The running
option of this program is similar to that in 'runI-TASSER.pl'. By running
the program without argument, you can print all the running options.

6.4. How to cite LOMETS?

If you are using the LOMETS program, you can cite:

S Wu, Y Zhang. LOMETS: A local meta-threading-server for protein
structure prediction. Nucleic Acids Research, 35: 3375-3382 (2007).

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# 7. Installation and implementation of SPICKER #
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7.1. Introduction of SPICKER

SPICKER is a clustering algorithm to identify the near-native models
from a pool of protein structure decoys.

7.2. How to install SPICKER program?

When you unpack the I-TASSER Suite, SPICKER program is already installed
at $pkgdir/I-TASSERmod/spicker45d

7.3. How to run SPICKER program?

To run SPICKER, you need to prepare following input files:
'rmsinp'---Mandatory, length of protein & piece for RMSD calculation;
'seq.dat'--Mandatory, sequence file, for output of PDB models.
'tra.in'---Mandatory, list of trajectory names used for clustering.
In the first line of 'tra.in', there are 3 parameters:
par1: number of decoy files
par2: 1, default cutoff, best for decoys from template-based
modeling;
-1, cutoff based on variation, best for decoys from
ab initio modeling.
par3: 1, closc from all decoys; -1, closc clustered decoys
From second lines are file names which contain coordinates
of 3D structure decoys. All these files are mandatory. See
attached 'rep1.tra1' for the format of decoys.
'CA'-------Optional, native structure, for comparison to native.

Output files of SPICKER include:
'str.txt'-----list of structure in cluster;
'combo*.pdb'--PDB format of cluster centroids;
'closc*.pdb'--PDB format of structures closest to centroids;
'rst.dat'-----summary of clustering results;

A detailed readme file can be found at
http://zhanglab.ccmb.med.umich.edu/SPICKER/readme

7.4. How to cite SPICKER?

If you are using the SPICKER program, you can cite:

Y Zhang, J Skolnick, SPICKER: Approach to clustering protein structures
for near-native model selection, Journal of Computational Chemistry,
25: 865-871 (2004).

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# 8. Installation and implementation of HAAD #
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8.1. Introduction of HAAD

HAAD is a computer algorithm for constructing hydrogen atoms from
protein heavy-atom structures. The hydrogen is added by minimizing
atomic overlap and encouraging hydrogen bonding.

8.2. How to install HAAD program?

When you unpack the I-TASSER Suite, HAAD program is already installed
at $pkgdir/abs/mybin/HAAD

8.3. How to run HAAD program?

Hydrogen atoms in a PDB file(xx.pdb) can be added by running
"./HAAD xx.pdb", the output is "xx.pdb.h".

In "xx.pdb.h", the label in column 57 presents the label for the atoms
that have been added by HAAD. When the value of the label is less
than 2, the position of the added atom has higher confidence.

8.4. How to cite HAAD?

If you are using the HAAD program, you can cite:

Y Li, A Roy, Y Zhang, HAAD: A Quick Algorithm for Accurate Prediction
of Hydrogen Atoms in Protein Structures, PLoS One, 4: e6701 (2009).

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# 9. Installation and implementation of EDTSurf #
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9.1. Introduction of EDTSurf

EDTSurf is a program to construct triangulated surfaces for macromolecules.
It generates three major macromolecular surfaces: van der Waals surface,
solvent-accessible surface and molecular surface (solvent-excluded
surface). EDTsurf also identifies cavities which are inside of
macromolecules.

9.2. How to install EDTSurf program?

When you unpack the I-TASSER Suite, EDTSurf program is already installed
at $pkgdir/bin/EDTSurf

9.3. How to use EDTSurf program?

EDTSurf -i inputfile ...
Specific options:
-o prefix of output files (default is the prefix of inputfile)
-t triangulation type, 1-MC 2-VCMC (default is 2)
-s surface type, 1-VWS 2-SAS 3-MS (default is 3)
-c color mode, 1-pure 2-atom 3-chain (default is 2)
-p probe radius, float point in [0,2.0] (default is 1.4)
-h inner or outer surface for output, 1-inner and outer 2-outer
3-inner (default is 1)
-f scale factor, float point in (0,20.0] (default is 4.0)

Molecule is scaled by this factor to fit in a bounding box. Scale
factor is the larger the better, but will increase the memory use.
Our strategy is first enlarging the molecule to check if it exceeds
the maximum bounding box. If yes, then reset a proper scale factor
to fit the molecule in the maximum bounding box.

By running EDTSurf itself, it will print out a brief description on how
to use the program. A detail description of EDTSurf is available at
http://zhanglab.ccmb.med.umich.edu/EDTSurf/

9.4. How to cite EDTSurf?

If you are using the EDTSurf program, you can cite:

D Xu, Y Zhang, Generating Triangulated Macromolecular Surfaces by Euclidean
Distance Transform. PLoS ONE 4: e8140 (2009).

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# 10. Installation and implementation of ModRefiner #
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10.1. Introduction of ModRefiner

ModRefiner is a standalone program for atomic-level protein structure
construction and refinement. It includes two steps: (1) construct
main-chain models from C-alpha trace; (2) build side-chain models
and atomic-level structure refinement.

10.2. How to install ModRefiner program?

When you unpack the I-TASSER Suite, ModRefiner program is already installed
at $pkgdir/I-TASSERmod/ModRefiner.pl

10.3. How to use ModRefiner program?

ModRefiner supports following four options:

a) add side-chain heavy atoms to main-chain model without refinement
> ModRefiner.pl 1 ID MD IM ON

b) build main-chain model from C-alpha trace model
> ModRefiner.pl 2 ID MD IM RM ON

c) build full-atomic model from main-chain model
> ModRefiner.pl 3 ID MD IM RM ON

d) build full-atomic model from C-alpha trace model
> ModRefiner.pl 4 ID MD IM RM ON

ID: the path of the I-TASSER package, e.g. '/home/yourname/I-TASSER5.0'
MD: directory which contains the initial model, e.g. '/home/yourname/I-TASSER/5.0/example'
IM: the initial model to be refined, e.g. 'mode1.pdb'
RM: reference model that refined model is driven to, e.g. 'combo1.pdb'.
Only CA trace is needed and the length can be not full which will make
the refinement of the missing region flexible. If you don't have the
reference model, use the name of IM instead.
ON: the output name of the refined model, e.g. 'model1_ref.pdb'

By running the program without argument, you can print a brief description
of how to use the program.

10.4. How to cite ModRefiner?

If you are using the ModRefiner program, you can cite:

D Xu, Y Zhang. Improving the Physical Realism and Structural Accuracy of
Protein Models by a Two-step Atomic-level Energy Minimization.
Biophysical Journal, 101: 2525-2534 (2011)

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# 11. Installation and implementation of NWalign #
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11.1. Introduction of NWalign

NW-align is simple and robust alignment program for protein
sequence-to-sequence alignments based on the standard Needleman-Wunsch
dynamic programming algorithm. The mutation matrix is from BLOSUM62
with gap opening penalty=-11 and gap extension penalty=-1.

11.2. How to install NWalign program?

When you unpack the I-TASSER Suite, NWalign program is already installed
at $pkgdir/bin/align.

11.3. How to use NWalign program?

> align F1.fasta F2.fasta (align two sequences in fasta file)
> align F1.pdb F2.pdb 1 (align two sequences in PDB file)
> align F1.fasta F2.pdb 2 (align Sequence 1 in fasta and 2 in pdb)
> align GKDGL EVADELVSE 3 (align sequences typed by keyboard)
> align GKDGL F.fasta 4 (align Seq-1 by keyboard and 2 in fasta)
> align GKDGL F.pdb 5 (align Seq-1 by keyboard and 2 in pdb)

By running the program itself, it will print out the usage options of
the program.

11.4. How to cite NWalign?

There is no published paper associated with this program. If you are using
the NWalign program, you can cite it as

Y Zhang, http://zhanglab.ccmb.med.umich.edu/NW-align

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# 12. Installation and implementation of PSSpred #
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12.1 Introduction of PSSpred

PSSpred (Protein Secondary Structure PREDiction) is a simple neural network
training algorithm for accurate protein secondary structure prediction. It first
collects multiple sequence alignments using PSI-BLAST. Amino-acid frequency and
log-odds data with Henikoff weights are then used to train secondary structure,
separately, based on the Rumelhart error back propagation method. The final
secondary structure prediction result is a combination of 7 neural network
predictors from different profile data and parameters.

12.2 How to install PSSpred program?

When you unpack the I-TASSER Suite, NWalign program is already installed
at $pkgdir/PSSpred

12.3 How to use PSSpred program?

$pkgdir/PSSpred/mPSSpred.pl seq.txt $pkgdir $libdir

Please note that 'seq.txt' should be in current directory and the script will
generate two files 'seq.dat' and 'seq.dat.ss' in the current folder. Here,
$pkgdir is the root path of I-TASSER package.

12.4 How to cite PSSpred?

If you are using the PSSpred program, you can cite:
http://zhanglab.ccmb.med.umich.edu/PSSpred

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# 13. Installation and implementation of COFACTOR #
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13.1 Introduction of COFACTOR

COFACTOR is a structure-based method for biological function annotation of
protein molecules. COFACTOR threads the structure through three comprehensive
function libraries by local and global structure matches to identify functional
sites and homology. Functional insights, including ligand-binding site,
gene-ontology terms and enzyme classification, will be derived from the best
functional homology template. The COFACTOR algorithm was ranked as the best
method for function prediction in the community-wide CASP9 experiments.

13.2 How to install COFACTOR program?

When you unpack the I-TASSER Suite, COFACTOR program is already installed
at $pkgdir/COFACTOR

13.3 How to use COFACTOR program?

$pkgdir/I-TASSERmod/runCOFACTOR.pl

13.4 How to interpret the results

If your input data is at $datadir/model1.pdb, the output of COFACTOR will be at
$datadir/model1/cofactor:
(1)List of similar structures in PDB: similarpdb_model1.lst. The columns are
(PDB_ID, TM-score, RMSD, Cov, Seq_id)
(2)Ligand-binding sites: BSITE_model1/Bsites_model1.dat. The columns are
(Rank, C-score, PDB_ID, TM-score, RMSD, Seq_id, Cov, Lig_name, SITE_num,
BS-score, LTM, BS_ID, BS_cov,BS_err, BS_ID1,BS_ID2, Binding residues)
(3)EC number: ECsearchresult_model1.dat The columns are
(PDB_ID, TM-score, RMSD, Seq_ID, Cov, EC-score, EC number,
Active site residues)
(4)GO terms: GOsearchresult_model1.dat. The columns are
(PDB_ID, TM-score, RMSD, Seq_ID, Cov, GO-score, GO terms)

13.5 How to cite COFACTOR?

If you are using the COFACTOR program, you can cite:

1. A Roy, J Yang, Y Zhang. COFACTOR: An accurate comparative algorithm for
structure-based protein function annotation.
Nucleic Acids Research, 40:W471-W477 (2012).
2. J Yang, A Roy, Y Zhang. BioLiP: a semi-manually curated database for
biologically relevant ligand-protein interactions.
Nucleic Acids Research, 41: D1096-D1103 (2013).

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# 14. Installation and implementation of COACH #
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14.1 Introduction of COACH

COACH is a meta-server approach to protein function annotations.
Starting from given structure of target proteins, COACH will generate
complementary ligand binding site predictions using two comparative methods:
TM-SITE and S-SITE, which recognize ligand-binding templates from
the BioLiP protein function database by binding-specific substructure and
sequence profile comparisons. These predictions will be combined with results
from COFACTOR to generate multiple function annotations, including
ligand-binding sites, enzyme commission and gene ontology terms.

14.2 How to install COACH program?

When you unpack the I-TASSER Suite, COACH program is already installed
at $pkgdir/COACH

14.3 How to use COACH program?

$pkgdir/I-TASSERmod/runCOACH.pl

14.4 How to interpret the results

If your input data is at $datadir/model1.pdb, the output of COACH will be at
$datadir/model1/coach:

(1) Ligand-binding sites: Bsites.dat. The columns are
(C-score, cluster_densitiy, product_of_top_templates_zscore,
Binding residues)
(2) Detailed clustering information: Bsites.inf, Bsites.clr, which list
the templates used in the cluster that generates the prediction in (1).
(3) Ligand-protein complex structures are with name: CH_complex*.pdb
(4) Predicions from COFACTOR, TM-SITE, and S-SITE are at, respectively:
$datadir/model1/cofactor
$datadir/model1/tmsite
$datadir/ssite

14.5 How to cite COACH?

If you are using the COACH program, you can cite:

1. J Yang, A Roy, Y Zhang. Protein-ligand binding site recognition using
complementary binding-specific substructure comparison and sequence profile
alignment. Bioinformatics, 29:2588-2595 (2013).
2. J Yang, A Roy, Y Zhang. BioLiP: a semi-manually curated database for
biologically relevant ligand-protein interactions.
Nucleic Acids Research, 41: D1096-D1103 (2013).

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# 15. Installation and implementation of TM-SITE #
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15.1 Introduction of TM-SITE

TM-SITE is a structure-based approach to protein-ligand binding site prediction.
Structure alignment between query and BioLiP templates is performed on
binding-specific substructure using TM-align. The final ligand-binding sites
are collected based on the clustering of multiple templates.

15.2 How to install TM-SITE program?

When you unpack the I-TASSER Suite, TM-SITE program is already installed
at $pkgdir/COACH

15.3 How to use TM-SITE program?

$pkgdir/I-TASSERmod/runTMSITE.pl

15.4 How to interpret the results

If your input data is at $datadir/model1.pdb, the output of TM-SITE will be at
$datadir/model1/tmsite:
(1)Ligand-binding sites: Bsites.dat. The columns are
(C-score, top_templates_zscore, JSD_score, cluster_density,
Binding residues)
(2)Detailed clustering information: Bsites.inf, Bsites_lig.clr, which lists
the templates used in the cluster that generates the prediction in (1).
(3)Ligand-protein complex structures are with name: complex*.pdb

15.5 How to cite TM-SITE?

If you are using the TM-SITE program, you can cite:

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# 16. Installation and implementation of S-SITE #
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16.1 Introduction of S-SITE

S-SITE is a sequence-based approach to protein-ligand binding site prediction.
Binding-specific sequence profile-profile alignment is used to recognize
homologous templates in BioLiP. The ligand-binding sites predictions are
collected from the clustering of multiple homologous templates.

16.2 How to install S-SITE program?

When you unpack the I-TASSER Suite, S-SITE program is already installed
at $pkgdir/COACH

16.3 How to use S-SITE program?

$pkgdir/I-TASSERmod/runSSITE.pl

16.4 How to interpret the results

If your input data is at $datadir/seq.fasta, then the output of S-SITE will
be at $datadir/ssite:

(1)Ligand-binding sites: Bsites_fpt.dat. The columns are
(C-score, top_templates_zscore, cluster_density, cluster_density1,
JSD_score, Binding residues)
(2)Detailed clustering information: Bsites_fpt.clr, which list the templates
used in the cluster that generates the prediction in (1).

16.5 How to cite S-SITE?

If you are using the S-SITE program, you can cite:

#######################################################
# #
# 17. Installation and implementation of ResQ #
# #
#######################################################

17.1 Introduction of ResQ

ResQ is a method for estimating B-factor and residue-level quality in protein
structure prediction, based on local variations of modelling simulations and
the uncertainty of homologous alignments. Given a protein structure model,
ResQ first identifies a set of homologous and/or analogous templates from
the PDB by threading and structure alignment techniques. The residue-level
modeling errors are then derived by support vector regression that was
trained on the local structural and alignment variations of the templates,
with the B-factor of each residue deduced from the experimental records of
the top homologous proteins.

17.2 How to install ResQ program?

When you unpack the I-TASSER Suite, ResQ program is already installed at
$pkgdir/ResQ.

17.3 How to use ResQ program?

There are two methods to run ResQ depending on how your models were generated.
1) If your models were generated by I-TASSER, you can run the script of
$pkgdir/ResQ/runResQ_IT.pl to predict B-factor and local structure errors.
The only argument required is the directory of the I-TASSER decoys. You
can read more at the head of this script to get more information about
its input.

2) If your models were not generated by I-TASSER, you can run the script
$pkgdir/ResQ/runResQ.pl to predict B-factor and local structure errors.
It will automatically run LOMETS to generate the threading alignment
file 'init.dat'. LOMETS is included in this package.

17.4 What is the output of ResQ?

For I-TASSER models, the output of ResQ is:
rsq_bfp_new.dat

For other models, the output of ResQ is:
1) global.txt for global accuracy estiamtion
2) local.txt for local error and B-factor estimation

17.4 How to cite ResQ?

If you are using the ResQ program, you can cite:

1. J Yang, Y Wang, Y Zhang. ResQ: Approach to unified estimation of B-factor
and residue-specific error in protein structure prediction,
Journal of Molecular Biology, 428: 693-701 (2016).