Case study (ref)
PSI meta-server used
Computer drive drug design process
Step Input Tools Output / result
Selection of ligand compound
sequence
PubChem structure
structure Open Babel required file format
ADMET studies sequence Pre-ADMET Provide drug-likeliness, ADME
profile and toxicity analysis for the
ligand.
Receptor
characterization
sequence GOR IV Text data result
Select Template sequence BLAST Identity, similarity, expectation
value & alignment scores
Homology modeling protein sequences Modeller pdb file
Visualizing pdb file PyMol visualized model
Model validation pdb file
PROCHECK Parameters(covalent bond
distances and angles,
stereochemical
validation and atom
nomenclature)
ERRAT The overall quality factor of non-
bonded interactions between
different atoms types
DaliLite mean square deviation (RMSD)
between the set of targets and
template protein to check
deviation of modelled protein
from the template protein
structure.
Docking studies PDB, PDBQ, PDBQT, SYBYL
mol2 or PQR format
AutoDock 4.2 PDBQT format and include special
keywords establishing the
torsional flexibility
Data Preparation and Analysis
The world wide Protein Data Bank: The single archive of experimental
marcomolecular structural data. [RCSB PDB] (USA); [PDBe] (Europe); [PDBj]
(Japan)
CATH: A manually curated hierarchical domain classification of protein structures
in the Protein Data Bank.
UniProt: Protein Knowledgebase. A comprehensive, high-quality and freely
accessible database of protein sequence and functional information.
RefSeq: NCBI Reference Sequence. A collection of curated, non-redundant
genomic DNA, transcript (RNA), and protein sequences produced by NCBI.
SBKB: Structural Biology Knowledgebase. A portal to protein structures,
sequences, functions and methods.
Structure Modelling
Template Search/Fold Recognition
BLAST/PSI-BLAST: Local alignment search
tools.
HHpred: Server for homology detection
and structure prediction by HMM-HMM
comparison.
Homology Modeling
New prediction
yes
no
HHpred: Server for homology detection and structure prediction by
HMM-HMM comparison.
I-Tasser: I-TASSER is a server for protein structure and function
predictions. 3D models are built based on multiple-threading
alignments by LOMETS and iterative TASSER assembly simulations.
M4T: Comparative Modelling using a combination of multiple templates
and iterative optimization of alternative alignments.
ModWeb: A web server for automated comparative modeling that relies
on PSI-BLAST, IMPALA and MODELLER.
SWISS-MODEL: Fully automated protein structure homology-modeling
server accessible via the ExPASy web server, or from the program
DeepView (Swiss Pdb-Viewer).
Homology Modeling
Structure Modeling
Swiss-model
identification
of structural
template
alignment of target
sequence &
template structure
model
building
model quality
evaluation
InterPro Domain Scan:
InterPro, Pfam, TIGRFAMs,
PROSITE, SUPERFAMILY,
ProDom,
PRINTS, SMART, PROSITE
PsiPred Secondary Structure
Prediction:
PSIPRED
DISOPRED Disorder
Prediction:
DISOPRED
MEMSAT:
MEMSAT
using BLAST query against the
ExPDB template library extracted
from PDB.
When no suitable templates are
identified, using Iterative Profile
Blast. Which is the template library
is searched with PSI-BLAST (Altschul
et al.) using an iteratively
generated sequence profile based
on NR (Wheeler et al.).
HHSearch: To detect distantly
related template structures (Söding
et al.)
Display of template identification
results
DeepView:
http://www.expasy.org/spdbv/
Protein Structure & Model Assessment
Tools:
ANOLEA
QMEAN, The global QMEAN4 scoring function
( Benkert et al. 2008), The global QMEAN6
scoring function (Benkert et al. 2008), The
local version of the QMEAN scoring function
(Benkert et al. 2009),
DFIRE
GROMOS
What Check
PROCHECK
PROMOTIF
DSSP
QMEAN4 global scores
Local Model Quality Estimation: Anolea / QMEAN / Gromos:
Alignment
Modelling Log
Template Selection Log
Quaternary Structure Modeling Log
Ligand Modeling Log
Structure Modelling
The "automated mode" is suited for cases where the target-template
similarity is sufficiently high to allow for fully automated modeling.
This submission requires only the amino acid sequence or the UniProt
accession code of the target protein as input data.
Depending on the planned model application, it can be necessary to
select a different structural template than the one ranked first in the
automated process. Please make sure that this file contains only a single
protein chain, and does not contain chemically modified amino acids,
hereto atoms, ligands, etc.
Automated Mode
If the three-dimensional structure is known for at least one of the members, this
alignment can be used as starting point for comparative modelling using the
"alignment mode".
The "alignment mode" allows the user to test several alternative alignments and
evaluate the quality of the resulting models in order to achieve an optimal result.
1. Prepare a multiple sequence alignment.
2. Submit your alignment to the Workspace Alignment Mode.
3. Select Target and Template.
4. Check Alignment and Submit.
The server pipeline will build the model purely based on this alignment. During the
modeling process, implemented as rigid fragment assembly in the SWISS-MODEL
(Schwede et al.) pipeline, the modeling engine might introduce minor heuristic
modifications to the placement of insertions and deletions.
Alignment Mode
In difficult modeling situations, where the correct alignment between
target and template cannot be clearly determined by sequence based
methods, visual inspection and manual manipulation of the alignment
can significantly help improving the quality of the resulting model.
Project files contain the superposed template structures, and the
alignment between the target and template. Project files can be
generated inside the program DeepView (Swiss-PdbViewer Guex et al.),
by the workspace template selection tools, and are also the default
output format of the modeling pipeline. This allows analyzing and
iteratively improving the models generated by the "Automated mode"
and "Alignment mode" modeling approaches.
Project Mode
M4T
Output:
pdb file
pir file
ana file
Energy profile
Structure Modelling
I-TASSER
tries retrieve template
proteins of similar folds
from the PDB library
by LOMETS
Structure assemblycontinuous
fragments
by replica-exchange Monte
Carlo simulations with the
threading unaligned regions
(mainly loops) built by ab
initio modeling
low free-energy states are
identified by SPICKER
Structure Re-assembly
Retrieve from cluster
LOMETS & TM-align
lowest
energy
structures
are selected.
final full-atomic models
(Remo H-Bond
optimization)
function predictions
TM-align
search
TM-score
Outputs:
Predicted Secondary Structure
Predicted Solvent Accessibility
pdb file
Top 10 templates
Proteins with highly similar structure in PDB
Function Prediction
Predicted GO terms
Predicted Binding Site
Structure Modellingsubmit an amino
acid sequence
HHpred
Select input format
MSA Generation Method
More Options
Max. MSA Generation
iterations
Score secondary
structure
Realign with MAC
algorithm
Alignment mode
Select HMM databases
Entering a single query sequence
Entering a multiple alignment
Proteomes
Pdb70,Scop70,CDD,Int
erPro,PfamA,SMART,P
ANTHER, TIGRFAMs,
PIRSF, SUPERFAMILY,
CATH/Gene3D,
COG/KOG, PfamB
HBlits : Download pdf file
PSI-Blast : View Article
E-value threshold for MSA Generation
Min. coverage of MSA hits
Min. sequence identity of MSA hits with
query
MAC realignment threshold (0.0:global,
>=0.1:local)
Compositional bias correction
Show sequences per HMM
Width of alignments
Min. probability in hit list
Max. number of hits in hit list
Output:
pdb file
Structure Modelling
Modeler
Searching for
structures related to
TvLDH
Selecting a template
Model evaluation Model building
Aligning TvLDF with
the template
target TvLDH sequence
profile.build()
automodel
Output:
pdb file
Structure Modeling
New prediction
When no suitable template structure can be identified, de
novo (a.k.a. ab initio) structure prediction methods can be
used to generate three-dimensional protein models without
relying on a homologus template structure:
Robetta: Full-chain protein structure prediction server based
on the Rosetta method.
Rosetta: De novo protein structure prediction software.
Structure Modeling
Hybrid techniques
The goal of hybrid techniques is to contribute to a comprehensive
structural characterization of biomolecules ranging in size and
complexity from small peptides to large macromolecular
assemblies. Detailed structural characterization of assemblies is
generally impossible by any single existing experimental or
computational method. This barrier can be overcome by hybrid
approaches that integrate data from diverse biochemical and
biophysical experiments:
CS-ROSETTA: System for chemical shifts based protein structure
prediction using ROSETTA.
IMP: software for a comprehensive structural characterization of
biomolecules.
Structure Modelling
Confidence Estimation
Validation and Quality estimation
Example: Verify3D
Tools Input Output
Verify 3D pdb 3D-1D average score, raw data, raw average data,
Whatcheck pdb Detial text report, TeX file
Prove pdb An pdf file with Z–score and analysis of residues, and an
text file
Errat pdb An pdf file with overall quality factor, error value in each
residue
PROCHECK pdb comprise a number of plots, in PostScript format
MolProbity pdb can view in pdf or KiNG, can choose lots of output
ProSA pdb Z-Score, knowledge based energy, sequence position
Confidence Estimation
Application
Structure
Visualization &
Analysis
PyMol: A Python based open-source viewer for
visualization of macromolecular structures.
AutoDock: A suite of
automated docking tools.
Molecular Interactions
Molecular Motions DynDom: Protein Domain Motion Analysis.
molmovdb.org: Gallery of morphs.
molmovdb.org: Molecular Movements
Database.

Session ii g2 overview metabolic network modeling mcc

  • 1.
    Case study (ref) PSImeta-server used Computer drive drug design process
  • 2.
    Step Input ToolsOutput / result Selection of ligand compound sequence PubChem structure structure Open Babel required file format ADMET studies sequence Pre-ADMET Provide drug-likeliness, ADME profile and toxicity analysis for the ligand. Receptor characterization sequence GOR IV Text data result Select Template sequence BLAST Identity, similarity, expectation value & alignment scores Homology modeling protein sequences Modeller pdb file Visualizing pdb file PyMol visualized model Model validation pdb file PROCHECK Parameters(covalent bond distances and angles, stereochemical validation and atom nomenclature) ERRAT The overall quality factor of non- bonded interactions between different atoms types DaliLite mean square deviation (RMSD) between the set of targets and template protein to check deviation of modelled protein from the template protein structure. Docking studies PDB, PDBQ, PDBQT, SYBYL mol2 or PQR format AutoDock 4.2 PDBQT format and include special keywords establishing the torsional flexibility
  • 4.
    Data Preparation andAnalysis The world wide Protein Data Bank: The single archive of experimental marcomolecular structural data. [RCSB PDB] (USA); [PDBe] (Europe); [PDBj] (Japan) CATH: A manually curated hierarchical domain classification of protein structures in the Protein Data Bank. UniProt: Protein Knowledgebase. A comprehensive, high-quality and freely accessible database of protein sequence and functional information. RefSeq: NCBI Reference Sequence. A collection of curated, non-redundant genomic DNA, transcript (RNA), and protein sequences produced by NCBI. SBKB: Structural Biology Knowledgebase. A portal to protein structures, sequences, functions and methods.
  • 5.
    Structure Modelling Template Search/FoldRecognition BLAST/PSI-BLAST: Local alignment search tools. HHpred: Server for homology detection and structure prediction by HMM-HMM comparison. Homology Modeling New prediction yes no
  • 6.
    HHpred: Server forhomology detection and structure prediction by HMM-HMM comparison. I-Tasser: I-TASSER is a server for protein structure and function predictions. 3D models are built based on multiple-threading alignments by LOMETS and iterative TASSER assembly simulations. M4T: Comparative Modelling using a combination of multiple templates and iterative optimization of alternative alignments. ModWeb: A web server for automated comparative modeling that relies on PSI-BLAST, IMPALA and MODELLER. SWISS-MODEL: Fully automated protein structure homology-modeling server accessible via the ExPASy web server, or from the program DeepView (Swiss Pdb-Viewer). Homology Modeling Structure Modeling
  • 7.
    Swiss-model identification of structural template alignment oftarget sequence & template structure model building model quality evaluation InterPro Domain Scan: InterPro, Pfam, TIGRFAMs, PROSITE, SUPERFAMILY, ProDom, PRINTS, SMART, PROSITE PsiPred Secondary Structure Prediction: PSIPRED DISOPRED Disorder Prediction: DISOPRED MEMSAT: MEMSAT using BLAST query against the ExPDB template library extracted from PDB. When no suitable templates are identified, using Iterative Profile Blast. Which is the template library is searched with PSI-BLAST (Altschul et al.) using an iteratively generated sequence profile based on NR (Wheeler et al.). HHSearch: To detect distantly related template structures (Söding et al.) Display of template identification results DeepView: http://www.expasy.org/spdbv/ Protein Structure & Model Assessment Tools: ANOLEA QMEAN, The global QMEAN4 scoring function ( Benkert et al. 2008), The global QMEAN6 scoring function (Benkert et al. 2008), The local version of the QMEAN scoring function (Benkert et al. 2009), DFIRE GROMOS What Check PROCHECK PROMOTIF DSSP QMEAN4 global scores Local Model Quality Estimation: Anolea / QMEAN / Gromos: Alignment Modelling Log Template Selection Log Quaternary Structure Modeling Log Ligand Modeling Log Structure Modelling
  • 8.
    The "automated mode"is suited for cases where the target-template similarity is sufficiently high to allow for fully automated modeling. This submission requires only the amino acid sequence or the UniProt accession code of the target protein as input data. Depending on the planned model application, it can be necessary to select a different structural template than the one ranked first in the automated process. Please make sure that this file contains only a single protein chain, and does not contain chemically modified amino acids, hereto atoms, ligands, etc. Automated Mode
  • 9.
    If the three-dimensionalstructure is known for at least one of the members, this alignment can be used as starting point for comparative modelling using the "alignment mode". The "alignment mode" allows the user to test several alternative alignments and evaluate the quality of the resulting models in order to achieve an optimal result. 1. Prepare a multiple sequence alignment. 2. Submit your alignment to the Workspace Alignment Mode. 3. Select Target and Template. 4. Check Alignment and Submit. The server pipeline will build the model purely based on this alignment. During the modeling process, implemented as rigid fragment assembly in the SWISS-MODEL (Schwede et al.) pipeline, the modeling engine might introduce minor heuristic modifications to the placement of insertions and deletions. Alignment Mode
  • 10.
    In difficult modelingsituations, where the correct alignment between target and template cannot be clearly determined by sequence based methods, visual inspection and manual manipulation of the alignment can significantly help improving the quality of the resulting model. Project files contain the superposed template structures, and the alignment between the target and template. Project files can be generated inside the program DeepView (Swiss-PdbViewer Guex et al.), by the workspace template selection tools, and are also the default output format of the modeling pipeline. This allows analyzing and iteratively improving the models generated by the "Automated mode" and "Alignment mode" modeling approaches. Project Mode
  • 11.
    M4T Output: pdb file pir file anafile Energy profile Structure Modelling
  • 12.
    I-TASSER tries retrieve template proteinsof similar folds from the PDB library by LOMETS Structure assemblycontinuous fragments by replica-exchange Monte Carlo simulations with the threading unaligned regions (mainly loops) built by ab initio modeling low free-energy states are identified by SPICKER Structure Re-assembly Retrieve from cluster LOMETS & TM-align lowest energy structures are selected. final full-atomic models (Remo H-Bond optimization) function predictions TM-align search TM-score Outputs: Predicted Secondary Structure Predicted Solvent Accessibility pdb file Top 10 templates Proteins with highly similar structure in PDB Function Prediction Predicted GO terms Predicted Binding Site Structure Modellingsubmit an amino acid sequence
  • 13.
    HHpred Select input format MSAGeneration Method More Options Max. MSA Generation iterations Score secondary structure Realign with MAC algorithm Alignment mode Select HMM databases Entering a single query sequence Entering a multiple alignment Proteomes Pdb70,Scop70,CDD,Int erPro,PfamA,SMART,P ANTHER, TIGRFAMs, PIRSF, SUPERFAMILY, CATH/Gene3D, COG/KOG, PfamB HBlits : Download pdf file PSI-Blast : View Article E-value threshold for MSA Generation Min. coverage of MSA hits Min. sequence identity of MSA hits with query MAC realignment threshold (0.0:global, >=0.1:local) Compositional bias correction Show sequences per HMM Width of alignments Min. probability in hit list Max. number of hits in hit list Output: pdb file Structure Modelling
  • 14.
    Modeler Searching for structures relatedto TvLDH Selecting a template Model evaluation Model building Aligning TvLDF with the template target TvLDH sequence profile.build() automodel Output: pdb file Structure Modeling
  • 15.
    New prediction When nosuitable template structure can be identified, de novo (a.k.a. ab initio) structure prediction methods can be used to generate three-dimensional protein models without relying on a homologus template structure: Robetta: Full-chain protein structure prediction server based on the Rosetta method. Rosetta: De novo protein structure prediction software. Structure Modeling
  • 16.
    Hybrid techniques The goalof hybrid techniques is to contribute to a comprehensive structural characterization of biomolecules ranging in size and complexity from small peptides to large macromolecular assemblies. Detailed structural characterization of assemblies is generally impossible by any single existing experimental or computational method. This barrier can be overcome by hybrid approaches that integrate data from diverse biochemical and biophysical experiments: CS-ROSETTA: System for chemical shifts based protein structure prediction using ROSETTA. IMP: software for a comprehensive structural characterization of biomolecules. Structure Modelling
  • 17.
    Confidence Estimation Validation andQuality estimation Example: Verify3D
  • 18.
    Tools Input Output Verify3D pdb 3D-1D average score, raw data, raw average data, Whatcheck pdb Detial text report, TeX file Prove pdb An pdf file with Z–score and analysis of residues, and an text file Errat pdb An pdf file with overall quality factor, error value in each residue PROCHECK pdb comprise a number of plots, in PostScript format MolProbity pdb can view in pdf or KiNG, can choose lots of output ProSA pdb Z-Score, knowledge based energy, sequence position Confidence Estimation
  • 19.
    Application Structure Visualization & Analysis PyMol: APython based open-source viewer for visualization of macromolecular structures. AutoDock: A suite of automated docking tools. Molecular Interactions Molecular Motions DynDom: Protein Domain Motion Analysis. molmovdb.org: Gallery of morphs. molmovdb.org: Molecular Movements Database.