1. Deriving Principles of Protein Structure
Eric Blanc
Nicola Kerrison
Eugene Schuster
The Molecular Basis of Life Understanding Biology, Disease & Evolution through Protein Structure
Jonathan Ward
Jonathan Barker
Mike Stevens
Enzymes & Pathways
Deriving Principles of Protein Structure
Functional Annotation of genomes, proteins and structures
Functional Genomics Analysis of Ageing
Pilar Ortega
Shiri Freilich
Matthew Bashton
Tim Massingham
Roman Laskowski
Rafi Najmanovich
James Torrance
Victor Chiskoff
Fabian Glaser
Alex Gutteridge
Thornton Group
James Watson
Gaby Reeves

2. Enzyme Structure, Function and Evolution
Alex Gutteridge
Malcolm MacArthur
James Torrance
Ruth Spriggs
Richard George
Irilenia Nobeli
Shiri Freilich
Gareth Stockwell
Outstanding Questions:
How is catalysis performed - Principles of catalysis?
How do enzymes evolve?
What is the enzyme complement in different organisms?
Can we predict enzyme function from structure?
Can we design new enzymes?

3. Percentages of entries in Data Resources annotated as enzymes
No. enzymes No. in database %-tage
PDB (all entries) , ,
PDB (non-redundant) , ,
UniProt , ,
Reactome (human) ( ) Trivial search
" (via UniProt)
Roman Laskowski

4. Ligand Selectivity
Conformational Change
Templates
Metabolome
Catalytic Site Atlas
Binding Site Diversity
Spherical Harmonics

5. Enzymes Catalytic Residues – Catalytic Site Atlas
Mechanisms of catalysis
Annotation using CSA
Nature’s Catalytic Toolkit
The enzyme complement in various organisms

6. The Class A β-Lactamase Mechanism

7. -lactamase Class A; EC 3.5.2.6; PDB: 1btl
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.
-lactamase Class A; EC ; PDB: 1btl
Reaction: -lactam + H2O  -amino acid
Active site residues: S70, K73, S130, E16

8. Propensity of residues to have a catalytic function
Alex Gutteridge

9. CSA Coverage (Current 514 Enzyme Dataset) Craig Porter & Gail Bartlett
# Representative Sites = 512
# PDB Files = 9,075
# Catalytic Sites = 20,001
Class # CSA/ # PDB
E.C Oxidoreductases / 271
E.C Transferases / 280
E.C Hydrolases / 421
E.C Lyases / 122
E.C Isomerases / 63
E.C Ligases / 58
Total / 1215
Craig Porter & Gail Bartlett

10. Comparison of CSA, SwissProt & PDB
Figure 2. A comparison of residue annotation between the CSA and SwissProt (left) and PDB (right) for the ‘original’ enzyme dataset, in Venn diagram form. The number of residues annotated by each database is given, along with the number of identical residues found in both databases.
Craig Porter & Gail Bartlett

11. iCSA: using Residue Conservation to Improve Function Annotation
Starting with over 500 enzymes from the CSA, with EC numbers and high quality catalytic site information
Retrieve homologues from BiopendiumTM
Align homologues with query enzyme, using
PSI-BLAST profiles
CLUSTAL W multiple alignments
Smith and Waterman pairwise alignments
Check for conservation of catalytic residues
If all residues are conserved, assign EC from annotated enzyme to homologue
Richard George & Ruth Spriggs

12. EC Assignment Accuracy
Correct EC assigned
An EC assigned
iCSA
Richard George & Ruth Spriggs

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

14. MACiE

15. Catalytic Units – Nature’s catalytic Toolkit
Favourable interactions provide enhanced catalytic power.
We expect common units to have evolved many times.
Alex Gutteridge

16. Catalytic Units The triad comprises two different units:
Carboxylate-Histidine (forms base)
Histidine-Hydroxyl (forms nucleophile)
Both units can be used independently of the other…
…and have evolved separately many times
Alex Gutteridge

17. Interaction Dataset 191 structures:
non-redundant
annotated by CSA
< 2A resolution
Occupancy = 1
Polar only
Interaction where atom-atom <4A.
Alex Gutteridge

18. This figure shows the number of interactions where only one of the residues has to be annotated as catalytic.
Again, few polar-polar interactions are observed.
More interactions between charged residues and charged residues with polar.
We see more carboxylate-carboxylate interactions than we would expect - useful for raising pKa.
Alex Gutteridge

19. Common Interactions Some are seen more often than expected…
Alex Gutteridge

20. Common Interactions Some are seen more often than expected…
…some less often
Alex Gutteridge

21. Complement of enzymes in 3 domains of life
Examine
Number of enzymes in different species as % of the proteome
Reaction composition in different species
Previous Work:
Van Nimwegen et al, 2003: metabolic genes occupy a roughly constant,though not necessarily common, fraction of the genome within the three domains of life
Cases et al, 2003: Proteins involved in “small molecule metabolism” are clearly over-represented in small genomes
Shiri Freilich

22. Relating the number of enzymes to proteome size
Permissive set
KEGG assignments
Conservative set
human
mouse
worm
fly
Shiri Freilich, Ruth Spriggs & Richard George

23. Future Catalytic Mechanisms – Macie Database
with Mitchell, Goodman, Glen & Murray-Rust in Chemistry Informatics Centre at Cambridge
Evolution of enzymes, pathways & metabolism in different organisms & tissues
Substrate recognition from structure
Design??

24. Functional Genomic Analysis of Ageing
Eric Blanc
Eugene Schuster
Nicola Kerrison
Jonathan Ward
Good afternoon ladies (are there any?) and gentlemen.
Our proposal is for functional genomic analysis of ageing.
There are 6 applicants, and we are all here.

25. Bioinformatics The Collaboration UCL & EBI
Oxidative damage and metabolism
Brand
Gems
Ageing
Worms
IIS/CR
Ageing
Mouse
IIS/CR
Humans
Leevers
Ageing
Flies
Partridge
Withers
Thornton
Bioinformatics

26. Comparative Functional Genomics
Caenorhabditis elegans
Drosophila melanogaster
Mus musculus
Our approach to discovering and understanding mechanisms of ageing is comparative functional genomics. We consider this to be a powerful generic approach to analysing complex biological traits such as ageing.
*We start with two invertebrate model organisms, the nematode worm C. elegans and the fruit fly Drosophila, both of which have completed genome sequences, which are essential for this approach to work.
We find and analyse mechanisms of ageing that these two evolutionarily very diverged organisms have in common, because this provides us with candidate mechanisms that may regulate ageing in mammals.
To do this we take a two-pronged approach. First, we shall identify and study single gene mutations that slow the ageing process. There are already about 100 such mutations in the worm and about 10 in Drosophila that have proved highly informative. We shall identify further such mutations using a bioinformatic approach - comparative genomics and by mutagenesis in the worm. Second, we shall use whole-genome transcript-profiling to identify genes that mediate the effects of environmental interventions that slow ageing, and downstream elements of pathways from mutants.
Throughout this process, we are reliant on *bioinformatics to identify homologues in these two organisms, and to get information about new genes from the transcription profiles.
Then, for those pathways that are conserved between these two invertebrate organisms, we use bioinformatics to identify homologous genes and pathways in the *mouse, and we then determine if they modulate the rate of ageing. If they pass this test then we again use bioinfnormatics to identify homologues in *humans that could be targets for beneficial interventions.
Bioinformatics
Whole genomes
Mutants
Transcriptomes
Pathways
Evolutionary conservation
Genes

27. Population projections for the UK
By 2050 life expectancy at birth will be 87
By 2020 one fifth of the UK population will be over 65
By 2020 the health care demand will double

28. Interventions that slow ageing in diverse organisms
Reduced insulin/IGF-like signalling
Caloric restriction
Caloric restriction
And
Reduced insulin/IGF signalling

29. Caloric Restriction yeast rhesus C. elegans rat Daphnia mouse
Drosophila
medfly
mouse
During caloric restriction the animal is put on a diet - to about 50% of voluntary intake.
This extends lifespan in organisms ranging from yeast to mammals, probably including primates.
It does it in our 3 model organisms.
It decreases the incidence of virtually all age-related damage and disease.
D. Gems et al.
Genetics 1998
T. Chapman & L. Partridge
Proc. Roy. Soc. 1996
A. Bartke et al.
Nature 2001

30. Downstream Mechanisms of Ageing: The Free Radical Theory
Superoxide activates mitochondrial
uncoupling proteins.
K.S. Echtay, M.D. Brand et al. Nature 2002 c I IV
ADP
+ Pi
NADH 2
Succinate
Fumarate
III II
ATP H +
NAD O2
H2O
CoQ e-
Uncoupling
Matrix
O2.-
We also wish to understand the mechanisms by which these interventions and pathways modulate the impact of ageing-related damage. The leading candidate mechanism here is damage from free radicals, particularly superoxide and its derivatives. The main site of superoxide production in cells is thought to be at the electron transfer chain in the inner membrane of the mitochondrion.
Modulations of the impact of oxidative damage could occur either by adjustment of the various form of endogenous defence mechanisms or of the rate at which they are generated in mitochondria. The evidence on this point is somewhat sparse, and comes mainly from comparison of species with different rates of ageing.

31. Programme of Research FlyBase Gene Ontology Affymetrix whole-
genome chips
CALORIC
RESTRICTION
AGE
EXPRESSION LEVEL
SURVIVAL
MORTALITY
AGE
CLUSTER ANALYSIS A3
R-7
R-14
R-28
C-23
C-28
C-7
C-18
R-64
R-69
R-47
R-55
R-74
C-42
C-47
FlyBase
Gene Ontology
The first part will be handling data from transcript profiles. We have done this so far in the context of a microarray profile of the effects of chronic caloric restriction in Drosophila, using whole-genome Affymetrix arrays. The survival and mortality profiles for the flies are shown top left, with the times at which we sampled. 5 chips per point, 75 chip experiment, times abut 14,000 genes. We found we had a lot of statistical power - using replication and temporal information - give some details. This allows us to cluster the profiles as shown bottom right - and one of the main findings of the study was that CR slows ageing-related changed in transcript profile - the chips cluster by physiological age rather than treatment. And some of the many patterns of change in expression are shown on the bottom left - with CR slowing them.
And we connect out data base to Gene Ontology in Fly Base to get functional and process ontology, to get a handle on what biologicla processes are affected by age and by our intervention - generates hypotheses for studies using RNAi, overexpression, mutants.
Within this project, there’ll be a lot more of this - time courses for CR, downstream effects of mutants, biomarkers etc. And we anticipate the development of new methods as the programme proceeds.
We shall also have a lot of other types of data -survival, metabolic, Tissue-and stage-specificity of effects and so on.

32. Programme of Research
Mechanisms by which Caloric Restriction and reduced Insulin/IGF-like signalling slow ageing:
Mutant screens
Global genomic transcript profiles of transitions
Ligands: detection, deletion, binding proteins
Identify responding tissues
The receptor & Signalling from the receptor
Interaction in determination of mortality
The role of reactive oxygen and nitrogen species:
Defence: drugs and endogenous:
Production of reactive oxygen species
Role of insulin/IGF signalling in mammalian ageing:
Loss-of-function mutants:
So, what are WE going to do? The experimental part of our programme can be divided into 4 part.
First, we shall investigate heading investigate mechanisms by which caloric restriction and reduced insulin/IGF-like signalling low ageing in flies and worms. For CR the initial aim is to identify the genes that mediate the response, whereas for IIS we shall characterise the molecular mechanisms underlying this pathway’s effects.
And we shall also investigate the extent to which the mechanisms underlying these two interventions overlap.

33. What is ageing ? 1 -1 20 30 40 50
0.9
-1.5 c
0.8 -2
0.7
-2.5
0.6
Survivorship -3
Ln mortality (µx)
0.5
-3.5
0.4 -4
0.3
-4.5
Fully Feed Flies
Fully Fed
0.2 -5
0.1
Calorie Restricted Flies
Dietary Restriction
-5.5 10 20 30 40 50 60 70 80 -6
Age/ days
Days
Is the increase in lifespan due to a shift or change in slope?
A change in slope means that the flies will die at a different rate and a shift in the slop means that the flies will die at a the same rate but will start to die at a later date.
Ln mortality = ln (risk of dying)= ln (no. dead/total at time dt)
Mair,W et al. Science 2004

35. How to extend lifespan?
Lifespan can be manipulated, but how does this work?
Popular theories:
Reduce oxidative damage
Reduce production of reactive oxygen species like superoxide.
Increase defence against damage by reactive oxygen species.
Increase disposal of “waste” – endobiotic and xenobiotic substances (Green theory).
Increase DNA repair (mitochondrial DNA, telomeres).
Improve immune response.

36. AgeBase: a QC tool for microarray experiments
Web site for storage and processing microarray data
Simple repository for data prior to deposition
A QC report is generated at every processing step (raw data, normalisation, p-values computation, gene list generation)
Check that the processing step has been successful, and that the hypothesis for the next processing step are fulfilled
Eric Blanc & Gene Schuster

37. Comparative transcriptomics of longevity
Are there common gene expression patterns in long-lived animals of different species, or between different tissues in a long-lived individual?
Liver
Muscle
Colon
Worm
Fly
Mouse
Nicola Kerrison

38. Summary of results Hypothalamus
 Hormone-mediated signalling
↓ Development / morphogenesis / organogenesis
Colon
Liver
 Ion transport
 Rhythmic / circadian behaviour
 Cell growth / maintenance / proliferation
 Ion transport
 Rhythmic / circadian behaviour
 Mitochondrial function
 Fatty acid metabolism
↓ Steroid / sterol / cholesterol biosynthesis
↓ Amino acid/ amine biosynthesis
Muscle
 Fatty acid metabolism
↓ Intracellular protein transport
↓ Macromolecule / protein metabolism
↓ Collagen
↓ Blood vessel development

39. Thanks to Funding from:
Wellcome Trust
BBSRC/DTI
MRC
Dept of Energy, US
NIH; US
Inpharmatica
EMBL

40. Thornton Group Eric Blanc Nicola Kerrison Jonathan Barker Pilar Ortega
Rafi Najmanovich
Fabian Glaser
James Watson
Jonathan Ward
Roman Laskowski
Gareth Stockwell
Thornton Group
Eugene Schuster
Thomas Funkhouser
Victor Chiskoff
Mike Stevens
Tim Massingham
Alex Gutteridge
Malcolm MacArthur
Hannes Ponstingl
Shiri Freilich
Matthew Bashton
Irilenia Nobeli
James Torrance
Ruth Spriggs
Richard George