Protein Structure Prediction and Analysis Tools Jianlin Cheng, PhD
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1 Protein Structure Prediction and Analysis Tools Jianlin Cheng, PhD Assistant Professor Department of Computer Science & Informatics Institute University of Missouri, Columbia 2011
2 Sequence, Structure and Function AGCWY Cell
3 Protein Folding Movie
4 Alpha-Helix Jurnak, 2003
5 Beta-Sheet Anti-Parallel Parallel
6 Non-Repetitive Secondary Structure Beta-Turn Loop
7 myoglobin haemoglobin
8 Quaternary Structure: Complex G-Protein Complex
9 Protein Structure Determination X-ray crystallography Nuclear Magnetic Resonance (NMR) Spectroscopy X-ray: any size, accurate (1-3 Angstrom (10-10 m)), sometime hard to grow crystal NMR: small to medium size, moderate accuracy, structure in solution
10 Pacific Northwest National Laboratory's high magnetic field (800 MHz, 18.8 T) NMR spectrometer being loaded with a sample. Wikipedia, the free encyclopedia
11 Storage in Protein Data Bank Search database
12 Search protein 1VJG
13 PDB Format (2C8Q, insulin)
14
15 Structure Visualization Rasmol ( m) MDL Chime (plug-in) ( Protein Explorer ( Jmol: Pymol:
16 J. Pevsner, 2005
17 Rasmol (1VJG)
18 Structure Analysis Assign secondary structure for amino acids from 3D structure Generate solvent accessible area for amino acids from 3D structure Most widely used tool: DSSP (Dictionary of Protein Secondary Structure: Pattern Recognition of Hydrogen-Bonded and Geometrical Features. Kabsch and Sander, 1983)
19 DSSP server: DSSP download: DSSP Code: H = alpha helix G = 3-helix (3/10 helix) I = 5 helix (pi helix) B = residue in isolated beta-bridge E = extended strand, participates in beta ladder T = hydrogen bonded turn S = bend Blank = loop
20 DSSP Web Service
21 Amino Acids Secondary Structure Solvent Accessibility
22 Solvent Accessibility Size of the area of an amino acid that is exposed to solvent (water). Maximum solvent accessible area for each amino acid is its whole surface area. Hydrophobic residues like to be Buried inside (interior). Hydrophilic residues like to be exposed on the surface.
23 Structure Comparison (Alignment) Are the structures of two protein similar? Are the two structure models of the same protein similar? Different measures (RMSD, GDT-TS (Zemla et al., 1999), MaxSub (Siew et al., 2000), TM score (Zhang and Skolnick,2005))
24 Superimposition David Baker, 2005
25 Useful Structure Alignment Tools CE ( DALI ( dali/) TM-Align: atics.ku.edu/tm-align/
26
27 Notation: protein structure 1D, 2D, 3D B. Rost, 2005
28 Goal of structure prediction Epstein & Anfinsen, 1961: sequence uniquely determines structure INPUT: OUTPUT: sequence 3D structure and function B. Rost, 2005
29 CASP Olympics of Protein Critical Assessment of Techniques of Protein Structure Prediction 1994,1996,1998,2000,20 02,2004,2006, 2008, 2010 Blind Test, Independent Evaluation CASP9: 116 targets Structure Prediction
30 1D Structure Prediction Secondary structure Solvent accessibility Disordered regions Domain boundary
31 1D: Secondary Structure Prediction Helix MWLKKFGINLLIGQSV Coil Neural Networks + Alignments CCCCHHHHHCCCSSSSS Strand Cheng, Randall, Sweredoski, Baldi. Nucleic Acid Research, 2005
32 Widely Used Tools (~78-80%) SSpro 4.1: Distill: PSI-PRED: software is also available SAM: PHD:
33 1D: Solvent Accessibility Prediction Exposed MWLKKFGINLLIGQSV Neural Networks + Alignments Buried eeeeeeebbbbbbbbeeeebbb Accuracy: 79% at 25% threshold Cheng, Randall, Sweredoski, Baldi. Nucleic Acid Research, 2005
34 Widely Used Tools (78%) ACCpro 4.1: software: SCRATCH: PHD: Distill:
35 1D: Disordered Region Prediction Using Neural Networks Disordered Region MWLKKFGINLLIGQSV 1D-RNN OOOOODDDDOOOOO 93% TP at 5% FP Deng, Eickholt, Cheng. BMC Bioinformatics, 2009
36 Tools PreDisorder: A collection of disorder predictors: Deng, Eickholt, Cheng. BMC Bioinformatics, 2009
37 1D: Protein Domain Prediction Using Neural Networks Boundary MWLKKFGINLLIGQSV + SS and SA 1D-RNN HIV capsid protein NNNNNNNBBBBBNNNN Inference/Cut Domain 1 Domain 2 Domains Top ab-initio domain predictor in CAFASP4 Cheng, Sweredoski, Baldi. Data Mining and Knowledge Discovery, 2006.
38 Tools DOMAC: Cheng, Nucleic Acids Research, 2007
39 Web:
40
41 Project 1 Predict Secondary Structure, Solvent Accessibility, Disorder Regions of soybean transcription factors Data: du/marc/muii_7005/seq_ TFP_90_2500.txt Select 10 proteins to make predictions
42 2D: Contact Map Prediction 3D Structure i n 2D Contact Map j..... n Distance Threshold = 8A o Cheng, Randall, Sweredoski, Baldi. Nucleic Acid Research, 2005
43 Contact Prediction SVMcon: NNcon: SCRATCH: SAM:
44 Tegge, Wang, Eickholt, Cheng, Nucleic Acids Research, 2009
45 Two Methodologies for 3D Structure Prediction AB Initio Method (physical-chemical principles / molecular dynamics, knowledge-based approaches) Template-Based Method (knowledge-based approaches)
46 Two Approaches Ab Initio Structure Prediction Physical force field protein folding Contact map - reconstruction Template-Based Structure Prediction MWLKKFGINLLIGQSV Simulation Select structure with minimum free energy Query protein MWLKKFGINKH Fold Recognition Alignment Protein Data Bank Template
47 Protein Energy Landscape C. Park, 2005
48 Markov Chain Monte Carlo Simulation
49 Template-Based Structure Prediction 1. Template identification 2. Query-template alignment 3. Model generation 4. Model evaluation 5. Model refinement Notes: if template is easy to identify, it is often called comparative Modeling or homology modeling. If template is hard to identify, it is often called fold recognition.
50 A. Fisher, 2005
51 Modeller Need an alignment file between query and template sequence in the PIR format Need the structure (atom coordinates) file of template protein You need to write a simple script (Python for version 8.2) to tell how to generate the model and where to find the alignment file and template structure file. Run Modeller on the script. Modeller will automatically copy coordinates and make necessary adjustments to generate a model. See project step 5-8 for more details.
52 An PIR Alignment Example Template id Structure determination method Start index End index >P1;1SDMA structurex:1sdma: 1: : 344: : : : : KIRVYCRLRPLCEKEIIAKERNAIRSVDEFTVEHLWKDDKAKQHMYDRVFDGNATQDDVFEDTKYL VQSAVDGYNVCIFAYGQTGSGKTFTIYGADSNPGLTPRAMSELFRIMKKDSNKFSFSLKAYMVELY QDTLVDLLLPKQAKRLKLDIKKDSKGMVSVENVTVVSISTYEELKTIIQRGSEQRHTTGTLMNEQS SRSHLIVSVIIESTNLQTQAIARGKLSFVDLAGSERVKKEAQSINKSLSALGDVISALSSGNQHIP YRNHKLTMLMSDSLGGNAKTLMFVNISPAESNLDETHNSLTYASRVRSIVNDPSKNVSSKEVARLK Query sequence id Template structure file id KLVSYWELEEIQDE* >P1;bioinfo : : : : : : : : : NIRVIARVRPVTKEDGEGPEATNAVTFDADDDSIIHLLHKGKPVSFELDKVFSPQASQQDVFQEVQ ALVTSCIDGFNVCIFAYGQTGAGKTYTMEGTAENPGINQRALQLLFSEVQEKASDWEYTITVSAAE IYNEVLRDLLGKEPQEKLEIRLCPDGSGQLYVPGLTEFQVQSVDDINKVFEFGHTNRTTEFTNLNE HSSRSHALLIVTVRGVDCSTGLRTTGKLNLVDLAGSERVGKSGAEGSRLREAQHINKSLSALGDVI AALRSRQGHVPFRNSKLTYLLQDSLSGDSKTLMVV QVSPVEKNTSETLYSLKFAER VR*
53 Structure File Example (1SDMA.atm) ATOM 1 N LYS N ATOM 2 CA LYS C ATOM 3 C LYS C ATOM 4 O LYS O ATOM 5 CB LYS C ATOM 6 CG LYS C ATOM 7 CD LYS C ATOM 8 CE LYS C ATOM 9 NZ LYS N ATOM 10 N ILE N ATOM 11 CA ILE C ATOM 12 C ILE C ATOM 13 O ILE O ATOM 14 CB ILE C ATOM 15 CG1 ILE C ATOM 16 CG2 ILE C ATOM 17 CD1 ILE C ATOM 18 N ARG N ATOM 19 CA ARG C ATOM 20 C ARG C ATOM 21 O ARG O ATOM 22 CB ARG C ATOM 23 CG ARG C ATOM 24 CD ARG C ATOM 25 NE ARG N ATOM 26 CZ ARG C ATOM 27 NH1 ARG N ATOM 28 NH2 ARG N ATOM 29 N VAL N ATOM 30 CA VAL C ATOM 31 C VAL C ATOM 32 O VAL O ATOM 33 CB VAL C ATOM 34 CG1 VAL C ATOM 35 CG2 VAL C
54 Modeller Python Script (bioinfo.py) # Homology modelling by the automodel class from modeller.automodel import * # Load the automodel class Where to find structure file log.verbose() # request verbose output env = environ() # create a new MODELLER environment to build this model in # directories for input atom files env.io.atom_files_directory = './:../atom_files' a = automodel(env, alnfile = 'bioinfo.pir', # alignment filename knowns = '1SDMA', # codes of the templates sequence = 'bioinfo') # code of the target a.starting_model= 1 # index of the first model a.ending_model = 1 # index of the last model # (determines how many models to calculate) a.make() # do the actual homology modelling PIR alignment file name Template structure file id Query sequence id
55 Output Example Command: mod8v2 bioinfo.py
56 Organism Homology modelling for entire genomes 0 5,000 10,000 15,000 20,000 H sapiens(chr. 22) H sapiens D melanogaster C elegans S cerevisiae U urealyticum T pallidum S PCC6803 R prowazekii N meningitidis M tuberculosis M pneumoniae M genitalium H pylori H influenzae E coli C trachomatis C pneumoniae C jejuni B burgdorferi B subtilis A aeolicus T maritima D radiodurans P horikoshii P abyssi M thermoautotrophicu M jannaschii A fulgidus A pernix Number of ORFs Number of ORFs with PDB hit 0 5,000 10,000 15,000 20,000 Number of proteins B. Rost, 2005
57 Sequence Identity and Alignment Quality in Structure Prediction Superimpose -> RMSD %Sequence Identity: percent of identical residues in alignment RMSD: square root of average distance between predicted structure and native structure.
58 3D Structure Prediction Tools MULTICOM ( ) I-TASSER ( HHpred ( Robetta ( 3D-Jury ( FFAS ( Pcons ( Sparks ( FUGUE ( FOLDpro ( SAM ( Phyre ( 3D-PSSM ( mgenthreader (
59 Protein Model Quality Assessment
60 APOLLO Output
61 Application of Structure Prediction Structure prediction is improving Template-based structure become more and more practical. Particularly, comparative / homology modeling is pretty accurate in many cases. Comparative modeling has been widely used in drug design. Protein structure prediction (both secondary and tertiary) has become an indispensable tool of investigating function of proteins and mechanisms of biological processes.
62 Baker and Sali (2000) J. Pevsner, 2005
63 Project 2 Select 5 soybean proteins Predict 3D structures Visualize the structures (data: /marc/muii_7005/seq_tfp_90_2500.txt)
Structure Tools and Visualization
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