Homology Modeling I Basel, September 30, 2004 Torsten Schwede - - PDF document
Swiss Institute of Bioinformatics EMBnet course: Introduction to Protein Structure Bioinformatics Homology Modeling I Basel, September 30, 2004 Torsten Schwede Biozentrum - Universitt Basel Swiss Institute of Bioinformatics Klingelbergstr
Swiss Institute of Bioinformatics Torsten Schwede Biozentrum - Universität Basel Swiss Institute of Bioinformatics Klingelbergstr 50-70 CH - 4056 Basel, Switzerland Tel: +41-61 267 15 81
EMBnet course: Introduction to Protein Structure Bioinformatics
Basel, September 30, 2004
[ PDB: http://www.pdb.org ]
100 1'000 10'000 100'000 1'000'000 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004
TrEMBL SwissProt PDB
No experimental structure for most sequences
Many proteins fold spontaneously to their native structure Protein folding is relatively fast (nsec – sec) Chaperones speed up folding, but do not alter the structure
MNIFEMLRID EGLRLKIYKD TEGYYTIGIG HLLTKSPSLN AAKSELDKAI GRNCNGVITK DEAEKLFNQD VDAAVRGILR NAKLKPVYDS LDAVRRCALI NMVFQMGETG VAGFTNSLRM LQQKRWDEAA VNLAKSRWYN QTPNRAKRVI TTFRTGTWDA YKNL
= + =
N i N i j ij j i ij ij ij ij ij torsions N angles i i i bonds i i i
1 1 6 12 2 , 2 ,
[ http://www.research.ibm.com/bluegene/ ]
Physical time for simulation 10–4 seconds Typical time-step size 10–15 seconds Number of MD time steps 1011 Atoms in a typical protein and water simulation 32’000 Approximate number of interactions in force calculation 109 Machine instructions per force calculation 1000 Total number of machine instructions 1023 BlueGene capacity (floating point operations per second) 1 petaflop (1015)
Blue Gene will need 1-3 years to simulate 100 µsec.
Helix position Amino acid statistics
David Baker group Find sequence patterns that strongly correlate with protein structure at the local level to create a library of fragments (I- sites). E.g. „amphipathic helix“:
http://isites.bio.rpi.edu
http://isites.bio.rpi.edu
PDB submissions per year Year Already known folds New folds
0.0 2.5 0.5 1.5 2.0 1.0 100 50
Percent identical residues in core Rmsd of backbone atoms in core
[ Chothia & Lesk (1986) ]
Common core = all residues that can be superposed in 3D For proteins > 60% identical residues, the core contains > 90 % of all residues deviating less than 1.0 Å.
20 40 60 80 100 50 100 150 200 250 ide ntity
Number of residues aligned Percentage sequence identity/similarity
(B.Rost, Columbia, NewYork)
Sequence identity implies structural similarity Don’t know region .....
20 40 60 80 100 50 100 150 200 250 ide ntity sim ila rity
Number of residues aligned Percentage sequence identity/similarity
(B.Rost, Columbia, NewYork)
Don’t know region ..... Sequence identity implies structural similarity
= Comparative protein modeling = Knowledge-based modeling Idea: Using experimental 3D-structures of related family members (templates) to calculate a model for a new sequence (target).
Known Structures (Templates) Target Sequence Template Selection Alignment Template - Target Structure modeling Structure Evaluation & Assessment Homology Model(s)
Known Structures (Templates) Target Sequence Template Selection Alignment Template - Target Structure modeling
Structure Evaluation & Assessment
Homology Model(s)
http://www.pdb.org
(models)
Known Structures (Templates) Target Sequence Template Selection Alignment Template - Target Structure modeling
Structure Evaluation & Assessment
Homology Model(s)
Template selection: 1. Sequence Similarity / Fold recognition 2. Structure quality (resolution, experimental method) 3. Experimental conditions (ligands and cofactors)
Known Structures (Templates) Target Sequence Template Selection Alignment Template - Target Structure modeling
Structure Evaluation & Assessment
Homology Model(s)
for pairs > 40% identity
templates to guide sequence alignment of target
template and targets
Known Structures (Templates) Target Sequence Template Selection Alignment Template - Target Structure modeling
Structure Evaluation & Assessment
Homology Model(s)
alignment result in bad models
modeling and evaluation
choose best.
Known Structures (Templates) Target Sequence Template Selection Alignment Template - Target Structure modeling
Structure Evaluation & Assessment
Homology Model(s)
I. Manual Model building
assembly – Composer (Sybyl, Tripos) – SWISS-MODEL
– Modeller (Insight II, MSI) – CPH-Models
[ http://www.expasy.org/spdbv/ ]
Find structurally conserved core regions
… by averaging core template backbone atoms (weighted by local sequence similarity with the target sequence). Leave non-conserved regions (loops) for later ….
Loop (insertion) modeling
Use the “spare part” algorithm to find compatible fragments in a Loop- Database, or “ab-initio” rebuilding (e.g. Monte Carlo, MD, GA, etc.) to build missing loops.
Side Chain placement
Find the most probable side chain conformation, using
Rotamer Libraries
Only a small fraction of all possible side chain conformations is observed in experimental structures Rotamer libraries provide an ensemble of likely conformations The propensity of rotamers depends on the backbone geometry: g+ trans g- p(g+ | phi) p(t | phi) p(g- | phi) p(g+ | psi) p(t | psi) p(g- | psi) Phe,Tyr, His
modeling method will produce unfavorable contacts and bonds Energy minimization is used to
extensive energy minimization will move coordinates away from real structure ⇒ keep it to a minimum SWISS-MODEL is using GROMOS 96 force field for a steepest descent
M A T E A F T S G Q
Some features of a protein structure: R resolution of X-ray experiment r amino acid residue type Φ, Ψ main chain angles t secondary structure class M main chain conformation class Χ i,, ci side chain dihedral angle class a residue solvent accessibility s residue neighborhood difference d Ca - Ca distance ∆d difference between two Ca - Ca distances
a protein (e.g. X-ray resolution) residues (e.g. solvent accessibility) pairs of residues (e.g. Ca - Ca distance)
A restraint is defined as probability density function (pdf) p(x):
1 2
x x
with
a) 11 Cys residues Chi-1 angles b) smoothed distribution from a) c) 297 Cys Chi-1 angles as control
Derive pdfs from frequency tables by smoothing:
4 . ' 2 . < < s 4 . ' ' 2 . < < s 4 . ' 2 . < < s 6 . ' ' 4 . < < s 4 . ' ' 2 . < < s 6 . ' 4 . < < s
Satisfaction of spatial restraints Find the protein model with the highest probability Variable target function: Start with a linear conformation model or a model close to the template conformation At first, use only local restraints minimize some steps using a conjugate gradient optimization repeat with introducing more and more long range restraints until all restraints are used
EVA Evaluation of Automatic protein structure prediction
[ Burkhard Rost, Andrej Sali, http://cubic.bioc.columbia.edu/eva/ ]
CASP Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction
http://PredictionCenter.llnl.gov
Evaluation of Automatic protein structure prediction
[ Burkhard Rost, Andrej Sali, http://cubic.bioc.columbia.edu/eva/ ] Target Sequence
MNIFEMLRID EGLRLKIYKD TEGYYTIGIG HLLTKSPSLN AAKSELDKAI GRNCNGVITK
New PDB Release Prediction Servers e.g. Evaluation of prediction accuracy 1 2 3
e.g. GROMOS, CHARMM, AMBER, ...
empirical force filed?
Ramachandran Plot of backbone angles (ϕ,ψ)
favored regions generously allowed regions disallowed regions Amino acids with special properties:
Solvent exposed / buried Hydrophobic / polar environment Electrostatic interactions Secondary structure etc.
+, Ile86 III, Ala182 II, Phe134 I, Val13 *, Met80 I II III * Val13 Met80 Phe134 Ala182
+
Distance Å MFP kcal/mol Methyl-Methyl pairs Cysteine S-S-pairs Distance Å
ANOLEA : (Atomic Non-Local Environment Assessment)
http://protein.bio.puc.cl/cardex/servers/anolea/ http://swissmodel.expasy.org/anolea/ Correct Structure: PDB: 1GES Model with wrong alignment: Detects local packing errors Errors in alignments
Checks the stereo-chemical quality of a protein structure, producing a number of plots analyzing its overall and residue-by-residue geometry.
Laskowski R A, MacArthur M W, Moss D S & Thornton J M (1993). PROCHECK: a program to check the stereochemical quality of protein structures. J. Appl. Cryst., 26, 283-291. Morris A L, MacArthur M W, Hutchinson E G & Thornton J M (1992). Stereochemical quality of protein structure coordinates. Proteins, 12, 345-364.
WHAT IF I check my structure? Imagine ...
already?" In a WHAT_CHECK report, each reported fact has an assigned severity: error: severe errors encountered during the analyses. Items marked as errors are considered severe problems requiring immediate attention. warning: Either less severe problems or uncommon structural features. These still need special attention. note: Statistical values, plots, or other verbose results of tests and analyses that have been performed.
WHAT IF: A molecular modeling and drug design program. G.Vriend, J. Mol.
Errors in protein structures. R.W.W. Hooft, G. Vriend, C. Sander, E.E. Abola, Nature (1996) 381, 272-272.
# 49 # Note: Summary report for users of a structure This is an overall summary of the quality of the structure as compared with current reliable structures. This summary is most useful for biologists seeking a good structure to use for modelling calculations. The second part of the table mostly gives an impression of how well the model conforms to common refinement constraint values. The first part of the table shows a number of constraint-independent quality indicators. Structure Z-scores, positive is better than average: 1st generation packing quality : -2.550 2nd generation packing quality : -5.472 (bad) Ramachandran plot appearance : -1.898 chi-1/chi-2 rotamer normality : -1.433 Backbone conformation : -2.173 RMS Z-scores, should be close to 1.0: Bond lengths : 0.905 Bond angles : 1.476 Omega angle restraints : 0.921 Side chain planarity : 2.681 (loose) Improper dihedral distribution : 1.771 (loose) Inside/Outside distribution : 1.333 (unusual)
ANOLEA : (Atomic Non-Local Environment Assessment)
ProCheck
WhatCheck
Verify3D
Biotech Validation Suite for Protein Structures
Save Zone Twilight Zone Midnight Zone
Reference: Discovery of a potent and selective protein kinase CK2 inhibitor by high-throughput docking. Vangrevelinghe E, Zimmermann K, Schoepfer J, Portmann R, Fabbro D, Furet P. Oncology Research, Novartis Pharma, Basle, J Med Chem. 2003 Jun 19;46(13):2656-62.
In silico docking of a virtual library of 400‘000 compounds Distributed Computing on PC Grid
Goal: Most of the sequences in a genome database should match at least one structure with a sufficient sequence identity allowing for reliable modeling.
Range of sequence space that can be modeled with acceptable accuracy.
The modeling error determines selection of targets for structural genomics.
SWISS-MODEL http://swissmodel.expasy.org Modeller http://www.salilab.org WhatIf http://www.cmbi.kun.nl/whatif/ 3D-JIGSAW
http://www.bmm.icnet.uk/people/paulb/3dj/form.html
CPHmodels
http://www.cbs.dtu.dk/services/CPHmodels/
SDSC1 http://cl.sdsc.edu/hm.html