Presentation is loading. Please wait.

Presentation is loading. Please wait.

Genome Annotation of Protein Function using Structural Data: Catalytic Residue Information Janet Thornton European Bioinformatics Institute ISMB/ECCB 2004.

Similar presentations

Presentation on theme: "Genome Annotation of Protein Function using Structural Data: Catalytic Residue Information Janet Thornton European Bioinformatics Institute ISMB/ECCB 2004."— Presentation transcript:

1 Genome Annotation of Protein Function using Structural Data: Catalytic Residue Information Janet Thornton European Bioinformatics Institute ISMB/ECCB 2004 Glasgow

2 From Structure to Functional Annotation

3 From Structure To Biochemical Function Gene Protein 3D Structure Function Given a protein structure: n Where is the functional site? n What is the multimeric state of the protein? n Which ligands bind to the protein? n What is biochemical function?

4 Automated Structure Comparison n The most powerful method for assigning function from structure is global or partial 3D structure comparison (e.g. Dali, SSAP; SSM) n Hidden Markov Models derived from structural domains can often recognise distant relatives from sequence

5 Predicting Binding Site Binding-site analysis: cutA Most likely binding site Surface clefts Residue conservation Conserved surface patches

6 Identifying Binding Site Function Using Motifs - 3D enzyme active site structural motifs (Craig Porter) - Catalytic Site Atlas - Identification of catalytic residues (Gail Bartlett, Alex Gutteridge) - Metal binding sites (Malcolm MacArthur) - Binding site features (Gareth Stockwell) - Automatically generated templates of ligand-binding and - DNA binding motifs (Sue Jones, Hugh Shanahan) - Reverse templates (Roman Laskowski) JESS – fast template search algorithm (Jonathan Barker)

7 Using information on Catalytic Residues derived from Structures n Catalytic Site Atlas n Using info for annotation of enzymes in genomes n 3D Templates

8 The Catalytic Site Atlas: a resource of catalytic sites and residues identified in enzymes using structural data. Craig T. Porter, Gail J. Bartlett, and Janet M. Thornton Nucl. Acids. Res : D129-D133.

9 Catalytic Site Information Enzyme reports from primary literature information -lactamase Class A EC: PDB: 1btl Reaction: -lactam + H2O -amino acid Active site residues: S70, K73, S130, E166 Plausible mechanism:

10 n Annotates catalytic residues in the PDB n Based on a dataset of 514 enzyme families u Representative catalytic site for each family u Homologues assigned by Psi-BLAST u Limited substitution allowed. u Homologues updated monthly. n Literature references n Data also available via MSDsite

11 CSA Coverage 512 Representative Sites 9075 PDB Files Catalytic Sites Class In CSA In PDB E.C Oxidoreductases. 194 / 271 E.C Transferases. 151 / 280 E.C Hydrolases. 221 / 421 E.C Lyases. 96 / 122 E.C Isomerases. 44 / 63 E.C Ligases. 33 / 58 Total 739 / 1215 (Current 512 Enzyme Dataset)

12 Metal Site Atlas n Annotates Metal Sites in PDB n Similar to CSA database n Searchable by: u PDB code u Swiss-Prot code u Homologues. n Dataset includes: u Copper, Zinc, Calcium, Iron (excl. hemes), Cobalt, Magnesium, Manganese, Molybdenum, Nickel and Tungsten.

13 Metal Site Atlas Contents Templates: 46 Cu 195 Zn 270 Ca 83 Fe 6 Co 86 Mg 45 Mn 10 Mo 7 Ni 4 W 752 Total Templates Sites in MSA: 6301 PDB Files Metal Binding Sites





18 Comparison of CSA v1.0 with Swiss-Prot and PDB Site Annotations

19 CSA v1.0 - Literature EC Wheels CSA v1.0 – plus homologues

20 iCSA: Using Functional Residue Conservation to Improve Function Annotation n Starting with over 500 enzymes from the CSA, with EC numbers and high quality catalytic site information n Retrieve homologues from Biopendium TM n Align homologues with query enzyme, using u PSI-BLAST profiles u CLUSTAL W multiple alignments u Smith and Waterman pairwise alignments n Check for conservation of catalytic residues n If all residues are conserved, assign EC from annotated enzyme to homologue u Also deals with mutation, etc. if necessary

21 Testing the iCSA Method n Searches with 517 CSA sites retrieved over Swiss- Prot sequences within four iterations of PSI-BLAST n These were assigned three digit EC numbers using the iCSA method n The assigned EC numbers were then compared with the EC annotation given in the Swiss-Prot database n The accuracy of EC assignment was compared with the accuracy achieved using sequence homology (i.e. PSI- BLAST) CSA query enzyme Swiss-Prot Homologues iCSA filtered homologues Homology search Function assignment by homology Function assignment using CSA iCSA filter

22 EC Assignment Accuracy CSA Correct EC assigned An EC assigned

23 Improvement in EC Assignment Accuracy, Compared with Homology Alone 48% overall Accuracy iCSA -Accuracy Homology Accuracy Homology

24 iCSA vs. Sequence Homology Alone n The accuracy of EC assignment is improved by using iCSA u The improvement in accuracy is more pronounced with more distant homologues: from 7% at iteration 1 to 88% at iteration 4 u Overall, EC assignment accuracy is improved by 48% u Overall, EC assignment accuracy using iCSA is 86% (vs. 58% using sequence homology alone)

25 iCSA EC Coverage % coverage PSI-BLAST iteration Correct EC assigned Homologues with correct EC

26 iCSA vs. Sequence Homology Alone n iCSA coverage is 78% overall u The iCSA is right to reject many of these homologues even though they have the same EC as the CSA site used as the query F EC covered by more than one specific catalytic site F Incorrect EC assignment in Swiss-Prot u But misaligned sequences are also possible, especially with more distant homologues

27 iCSA Correctly Rejects Homologues n The iCSA accuracy with the CSA trypsin site is 100% n The benefits of the iCSA method can be seen in the homologues not assigned the trypsin EC n Trypsin homologues that do not pass the catalytic residue checks in iCSA include several haptoglobin proteins u Haptoglobin is closely related to trypsin, but is a known non- enzyme n Sequence homology alone would assign these haptoglobin sequences the trypsin EC, but iCSA can correctly identify that the residues for catalysis are not present

28 Human Genome Annotation n We applied iCSA to the human ENSEMBL sequence database n The iCSA directly annotated 2064 sequences with an EC u Only 64% of these have an equivalent Swiss-Prot protein F at least 90% pairwise sequence identity and a difference in length of less than 10% of the shorter sequence u So 743 sequence annotations have been efficiently expanded n A further 2257 homologues did not have a conserved site and an EC was not assigned u 73% of the equivalent Swiss-Prot sequences had an alternative EC number to the iCSA query u Homology-based functional assignments in these cases could prove incorrect

29 Summary n iCSA methodology developed n Database currently contains: u 7013 PDBs (11710 chains) u Swiss-Prot sequences u 4321 Human ENSEMBL sequences u 4227 Mouse ENSEMBL sequences

30 Poster E-37 Session 1 (Sunday)

31 3D Templates to Characterise Functional Sites Template searches (189 enzyme active site templates) (~600 Metal binding site templates)

32 GARTfase Cholesterol oxidase IIAglc histidine kinase Carbamoylsarcosine amidohhydrase Dihydrofolate reductase Ser-His-Asp catalytic triad … Database of enzyme active site templates 189 templates

33 MCSG structure BioH – unknown function involved in biotin synthesis in E.coli An example Structure: Rossmann fold, hence many structural homologues Expected to be an enzyme Sequence contains two Gly-X-Ser-X-Gly motifs typical of acyltransferases and thioesterases

34 Ser-His-Asp catalytic triad of the lipases with rmsd=0.28Å (template cut-off is 1.2Å) CSA template search One very strong hit Experimentally confirmed by hydrolase assays Novel carboxylesterase acting on short acyl chain substrates

35 Generation of 3D Active Site Templates for Enzymes in the Catalytic Site Atlas Gail J Bartlett *, James W Torrance, Craig T Porter, Jonathan A Barker, Alex Gutteridge, Malcolm W MacArthur, Janet M Thornton EMBL Outstation - European Bioinformatics Institute (EBI), Hinxton, Cambridge CB10 1SD, UK * Centre For Bioinformatics, Biochemistry Building, Imperial College London, South Kensington Campus, London SW7 2AZ, UK 1. Introduction Structural templates can be used to search protein structures for particular patterns of residues, such as catalytic sites. Structural templates are thus a tool for predicting protein function. There are many methods that employ structural templates, but no reliable template libraries. The Catalytic Site Atlas 1 is a database of catalytic residues within proteins of known structure. This information can be used to create a template library. We hope to use this library to uncover cases of convergent evolution and to predict function from structure. 2. Objectives To use the Catalytic Site Atlas to create a library of structural templates representing catalytic sites To assess the effectiveness of these templates for identifying proteins with a particular catalytic function EBI Home Page 4. Results No correlation between RMSD of template atoms and percentage pairwise sequence identity found within homologous enzyme families Majority of RMSD values between templates from homologous family members were below 1Å Templates distinguish related enzymes well in most families, with > 75% of relatives having RMSDs better than that of any random match. Some families showed wide variation of catalytic residue geometry, making prediction difficult. Templates based on C / C atoms performed slightly better than those which used functional atoms. 3. Methods Template generation and analysis of active site geometry Two types of template were created (atoms used are highlighted in ball form): Templates within the same homologous enzyme family were superposed and the distribution of RMSDs examined. Assessing template effectiveness The Jess template-matching method 2 was used to query all the templates against a non-redundant subset of the PDB. Hits were scored using both RMSD and a statistical significance measure. The effectiveness of hits was measured by comparing scores of hits between relatives with scores from random hits identified in the PDB. Telephone+44(0) Fax+44(0) C and C atoms Three functional atoms 7. Conclusions Structural templates representing catalytic sites effectively distinguish between family members and random hits. The lack of correlation between RMSD and pairwise % sequence identity within families is a result of catalytic residue position being affected not only by evolutionary divergence, but also by factors such as presence or absence of ligand, ligand type, and possible functional variation. 8. References 1. Porter, C.T., Bartlett, G.J., Thornton, J.M. (2004) The Catalytic Site Atlas: a resource of catalytic sites and residues identified in enzymes using structural data. Nucleic Acids Res 32, D Barker, J.A., Thornton, J.M. (2003) An algorithm for constraint-based structural template matching: application to 3D templates with statistical analysis. Bioinformatics 19, A bad template - fructose 1,6-bisphosphatase It is difficult to construct a sensitive template for fructose 1,6-bisphosphatase because one catalytic residue is on a flexible loop that moves when AMP binds at an allosteric site. 5. A good template - aldolase A Aldolase A relatives superpose well (below right) and there is a clear separation between these and random hits to PDB (below left). Superposition of homologous family templates Open form Closed form Catalytic residues Flexible loop AMP Loop closed Structures of open form Structures of closed form ° Distribution of RMSDs of hits to aldolase template (based on PDB 1ald) ° Distribution of RMSDs of hits to fructose 1,6-bisphosphatase template (based on PDB 1eyi) Poster Number I76 - Monday

36 Template databases n HAND CURATED u Enzyme active sites (PROCAT) – 189 templates F Currently being extended u Metal-binding sites – 600 templates n AUTOMATED u Ligand-binding sites – 10,000 templates u DNA-binding sites – 800 templates

37 Automatically generated templates 1. Ligand-binding templates b. Identify residues interacting with ligand (via H-bonds or non- bonded contacts) c. Templates generated from overlapping local groups of 3- residue clusters a. For each Het Group in the PDB extract a non-homologous data set of proteins binding that Het Group d. Gives over 10,000 ligand-binding templates

38 Automatically generated templates 2. DNA-binding templates b. Identify residues interacting with DNA/RNA (via H-bonds or non-bonded contacts) c. Templates generated from overlapping local groups of 3- residue clusters a. Extract a non-homologous data set of DNA/RNA-binding proteins from the PDB d. Gives over 800 DNA/RNA- binding templates

39 Problems with automated template methods WITH A LARGE NUMBER OF TEMPLATES: Too many hits (usually tens, and often hundreds) Use of rmsd rarely discriminates true from false positives Local distortion in structure may give a large rmsd Top hit rarely the correct hit – even in obvious cases

40 An example PDB code: 1hsk UDP-N-acetylenolpyruvoylglucosamine reductase (MURB) E.C Contains the 3D template that characterises this enzyme class Sequence identity to templates representative structure (1mbb) is 28% Ser Arg Glu

41 Enzyme active site templates Hits for 1hsk 102. E.C Å UDP-N-acetylmuramate dehydrogenase Hit E.C number Rmsd Enzyme 1. E.C Å Acyl-CoA dehydrogenase 2. E.C Å Tryptophan synthase α-subunit 3. E.C Å Glycosyl hydrolases, family E.C Å Glycosyl hydrolases, family E.C Å Fructose-bisphosphate aldolase (class I) … … … 386. … 3.94Å … Arg Glu Ser rmsd=2.19Å

42 Template structure – 1mbb Comparison of template environments Arg Glu Ser Similar residues in neighbourhood: Target structure – 1hsk

43 Template structure – 1mbb Comparison of template environments Arg Glu Ser Match to template: Target structure – 1hsk

44 Template structure – 1mbb Comparison of template environments Arg Glu Ser Match to template: Target structure – 1hsk

45 Score equivalent grid-points using Dayhoff matrix and taking voids into account Environment similarity score Template structure Slices through 10Å sphere centred on template match 1mbb Target structure 1hsk Total similarity score obtained from sum of all grid-point scores

46 Results for 1hsk 1. E.C UDP-N-acetylmuramate dehydrogenase 2. E.C Chitinase A chitodextrinase 1,4-beta-poly-N-acetylglucosaminidase coly-beta-glucosaminidase 3. E.C Turkey lysozyme 4. E.C Hen lysozyme 5. E.C Aspartylglucosylaminidase 6. E.C Glucan 1,4-alpha-glucosidase Hit E.C number Rmsd Score Enzyme

47 Residue conservation Hit E.C number Rmsd Signif Enzyme 1. E.C Å 98.3% UDP-N-acetylmuramate dehydrogenase 2. E.C Å 98.3% Penicillin acylase 3. E.C Å 98.3% Topoisomerase Ia/II 4. E.C Å 98.3% Mandelate racemase 5. E.C Å 97.8% Topoisomerase Ia/II … … … … Rank template hits according to conservation scores of the matched residues

48 Residue conservation and cleft proximity Hit E.C number Rmsd Signif Enzyme 2. E.C Å 98.3% UDP-N-acetylmuramate dehydrogenase 1. E.C Å 98.4% Mandelate racemase 3. E.C Å 98.3% Penicillin acylase 4. E.C Å 98.3% Topoisomerase Ia/II 5. E.C Å 97.8% Topoisomerase Ia/II … … … … Rank by conservation and proximity to proteins two largest clefts

49 1hsk Reverse templates 1hsk … 3-residue templates

50 Template structure – 1mbb Comparison of template environments Identical residues in neighbourhood: Target structure – 1hsk

51 Reverse templates Search each template vs PDB (or representative subset) Typically get templates from a single structure Non-homologous dataset of 2,500 protein chains Focused search (eg top DALI hits) Locate known PDB entries with closest local similarity Program called: the Protein SiteSeer Times for search vs 2,500 set JESS – 30 minutes SiteSeer – 3 hours

52 ProFunc – function from 3D structure Homologous sequences of known function Binding site identification and analysis Homologous structures of known function Functional sequence motifs Q-x(3)-[GE]-x-C-[YW]-x(2)-[STAGC] Enzyme active site 3D-templates HTH-motifs Electrostatics Surface comparison … etc DNA-, ligand- binding and reverse templates Residue conservation analysis

53 Acknowledgements CSA: Craig Porter, Gail Bartlett, Alex Gutteridge, Malcolm MacArthur (EBI), Neera Borkakoti Genome Annotation: Ruth Spriggs, Richard George, Mark Swindells, B. Al-Lazikhani (Inpharmatica) ProFunc: Roman Laskowski; James Watson (EBI)

Download ppt "Genome Annotation of Protein Function using Structural Data: Catalytic Residue Information Janet Thornton European Bioinformatics Institute ISMB/ECCB 2004."

Similar presentations

Ads by Google