COMPUTER SIMULATION TO UNDERSTAND HOW … SIMULATION TO UNDERSTAND HOW ENZYMES WORK. Carme Rovira....
Transcript of COMPUTER SIMULATION TO UNDERSTAND HOW … SIMULATION TO UNDERSTAND HOW ENZYMES WORK. Carme Rovira....
COMPUTER SIMULATION TO UNDERSTAND HOW ENZYMES WORK
Carme RoviraUniversitat de Barcelona, ICREA &
Institute of Theoretical and Computational Chemistry, Spain
What are enzymes?
Adapted from https://www.ebi.ac.uk/training/online/course/introduction-protein-classification-ebi/protein-classification
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What are enzymes?
• Most enzymes are proteins
• Enzymes serve as catalyst to accelerate biochemical reactions
• Enzymes are not changed in this process
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Saliva: amylase
Stomach:proteases
Small intestine:lipases,amylase, lactase
Picture fromwww.divavillage.com
DIGESTIVE ENZYMES
sugar units(monosaccharides)
Long carbohydrate molecule
digestion
GLYCOSIDASESCarme Rovira
Starch is our main source of energy
Starchy foodsglycosidic bonds
(≈ 1/3 of our daily food intake)
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R. Wolfenden & M. J. Snider.Acc. Chem. Res. 2001, 34, 938-945
The power of enzymes as catalysts
t1/2 = 1 billion years
t1/2 = 1 million years
t1/2 = 1 thousand years
t1/2 = 1 year
t1/2 = 1 day
t1/2 = 1 minute
age of the earth
O-glycoside hydrolysis 5-8 million years
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How enzymes work
PASS
AB
© 2010 Nature Education All rights reserved.
Without enzyme With enzyme
Ener
gy
Reaction pathway
Activationenergy
A
B
A
B
Enzymes lower the activation energyof the biochemical reaction
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How enzymes work
PASS
AB
GLYCOSIDASE
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Enzymes are very specific
Example: α-1,4-glucosidase “cuts” glycosidic bondsbetween atoms 1 and 4 of the α-glucose units of glycogen
n
1 4
...OH OH OH OH
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Lack of lactase causeslactose intolerance
GALACTOSE GLUCOSE
Enzymes and disease
Lack of α-1,4-glucosidase causes accumulation of glycogen in the liver, leading to the Pompe disease
GLYCOGEN
LACTOSE
GLUCOSE UNITS
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Knowing how enzymes work isimportant for drug design
Relenza Tamiflu
Synthesis of molecules that inhibit a disease-related enzyme
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Computer simulation to understandhow enzymes work
• Computer simulation provide molecular details of enzyme action
• Short-lived states (e.g. transition states) can be identified
• Important for inhibitor (drug) design
Reaction pathway
A
B
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Impact of High Performance Computing
• The large increase of computer power in recent years has contributed enormously to the progress of computer simulation of enzymes (computational enzymology)
• Better models and precise methods can be used
• Meaningful predictions can be made
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Clarifying mechanisms of enzymesthat process carbohydrates
Gas2 glucosidase, an antifungal target
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Simulation performed in MareNostrum (BSC)Raich et al. J. Am. Chem. Soc. 138, 3325 (2016)
Clarifying mechanisms of enzymesthat process carbohydrates Carme Rovira
(Newton’s equations)
Molecular dynamics
Initial conditions:
• Atomic positions (e.g. crystal structure): {ri}• Atomic velocities (e.g. random velocities scaled to desired T): { }iv
Motion of atoms from
ri (t)i
2i
2
rr
dEd
tddmi −=
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at t = t + ∆t
i2
i2
rr
dEd
tddmi −=
Molecular dynamics
Solve
{ } { }ii andnew vr
t = 0
{ } { }ii and:velocitiesandpositionsinitial vr
∆t ≈ 1 fs (10-15 seconds)single time step
compute forcesi
i ddEr
F −=
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Classical MD
E = Ebond + Eang + Edih + EvdW + Eelec
Energy from a force-field
{ }[ ]I(r)ρ
Rρ(r),EminE = Density Functional Theory
Molecular dynamics
Computer codes: GROMACS, NAMD, AMBER, …
Energy from quantum mechanics
Ab initio MD
Computer codes: CPMD, CP2K, QUANTUM EXPRESSO, …
Biarnés, Nieto, Planas, RoviraJ. Biol. Chem. 281, 1432–1441 (2006)
C. RoviraMethods Mol. Biol. 305, 527 (2005)
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Classical MD
E = Ebond + Eang + Edih + EvdW + Eelec
Energy from a force-field
{ }[ ]I(r)ρ
Rρ(r),EminE =
Energy from quantum mechanics
Density Functional Theory
Molecular dynamics
Ab initio MDCarme Rovira
Active center
(quantum mechanics)Rest of the system
(molecular mechanics)
Multiscale methods
“for thedevelopment of multiscale modelsfor complexchemical systems”
The quantum mechanics / molecular mechanics (QM/MM) approach
ab initio MD classical MD
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Carbohydrate degradation by glycosidases
glycosidic bondcleavage
sugar units(monosaccharides)
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Carbohydrates are very flexible
Slide from Lluís Raich(University of Barcelona)
Sugar shapes
Chair
Most abundantfor a free sugar
Envelope Boat
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Boat-likeconformation
O
Sugars change shape when they bindto enzymes
O
WHY?
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Biarnés et al. J. Biol. Chem. 2006 Biarnés et al. J. Am. Chem. Soc. 2011
Sugar distortion facilitates thebiochemical reaction
Sugars change shape when they bindto enzymes
twistedboat
O
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Biarnés et al. J. Biol. Chem. 2006 Biarnés et al. J. Am. Chem. Soc. 2011
Sugars change shape when they bindto enzymes
Sugar distortion facilitates thebiochemical reaction
Ener
gy
Reaction pathway
ActivationenergyA
B
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http://biology.tutorvista.com
Example: Golgi α-mannosidase II
Golgi complex
Cell
mannose2
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Mechanism of action
Golgi α-mannosidase II
Petersen et al. J. Am. Chem. Soc. 132, 8291 (2010)
boat
Initialcomplex
O
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Petersen et al. J. Am. Chem. Soc. 132, 8291 (2010)Williams et al. Angew. Chem. Int. Ed. 53, 1087 (2014)
Golgi α-mannosidase IIMechanism of action
anticancer inhibitors
transitionstate
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Sugar shape
• Important for inhibitor design
BUT
• The structure of the enzyme for most
glycosidase enzymes is not known
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OS2 3,OB
3S1
B1,4
1S5
B2,5
1,4B
1S3
B3,0 2SO
2,5B
5S1
4C1
OH1
OH54H5
4H32H3
2H1
Ardèvol et al. J. Am. Chem. Soc. 2010, 132, 16058
Mapping sugar shape
Metadynamics
Laio and Parrinello, PNAS 2002
mannoseEnergy map
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G. J. Davies, A. Planas, C. Rovira, Acc. Chem. Res. 45, 308 (2012).Iglesias-Fernández et al. Chem. Sci. 6, 1167 (2015).
Sugar fingerprintsEXP
glucose mannose xylose
Mapping sugar shapeCarme Rovira
Privateer software: conformational validation of carbohydrate structures Agirre, Iglesias-Fernández, Rovira, Davies, Wilson, Cowtan. Nat. Struct. Mol. Biol. 22, 833 (2015)
Structural validation
wrong conformation correct conformation
(high energy)
β α
(low energy)
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Carbohydrate synthesis
glycosidic bondformation
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Outsideof cell
Cellmembrane
Insideof cell
(cytoplasm)
virusbacteria
Sugars on the cell surface
Special Issue.March 2001: Vol. 291. no. 5512.
Carbohydratesand
Glycobiology
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Problems associated to a failure of cell-cell communication
Outsideof cell
Cellmembrane
Insideof cell
(cytoplasm)
virusbacteria
Inflammation
Autoinmune
diseases:
asthma
diabetes
allergies
multiple sclerosis
Infection
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Abnormal glycosilation: cancer
cancer cells
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• GalNAc-T2 attaches one sugar (GalNAc, a galactose derivative) to proteins
• It initiates protein glycosylation
N-acetylgalactosaminyltransferase 2 (GalNAc-T2)
GalNAc-T2
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Structure of GalNAc-T2
Catalyticdomain
Lectin domain
Linker
enzymeactive site
Collaboration with:R. Hurtado-Guerrero (U. Zaragoza)F. Corzana (Logroño)H. Clausen (Denmark)P. Bernadó (Montpellier)
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Structure of GalNAc-T2
enzymeactive site
Collaboration with:R. Hurtado-Guerrero (U. Zaragoza)F. Corzana (Logroño)H. Clausen (Denmark)P. Bernadó (Montpellier)
proteinfragment
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Metadynamics simulation
The lectin domain “catches” the peptide and brings it to the catalytic site.
Lira-Navarrete et al. Nat. Commun. 2015, 6, 6937.
Peptide binding to GalNAc-T2
Computer simulation
Atomic Force Microscopy
Lira-Navarrete et al. Nat. Commun. 2015, 6, 6937.
Computationalmicroscope
Adapted from:DOI: 10.1021/acs.jcim.5b00249(A. Magistrato)
GalNAc-T2 biochemical reaction
PEPTIDE
UDP
SUGAR
Angew. Chem. Int. Ed. 2014, 53, 8206
SUGAR TRANSFER
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hydrogen peroxide
(H2O2)
Catalase enzymes
catalase
water(H2O)
oxygen(O2)
Giorgio et al. Nature Rev. 8,722-28 (2007)
Hydrogen peroxide:• biological toxin• byproduct of metabolism
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Catalase-peroxidase (KatG)
• Antitubercular target• KatG mutations cause drug resistance to the
INH drug
Isoniazid (INH)Movie by Peter Loewen(Universty of Manitoba, Canada)
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Catalase-peroxidase (KatG)
Movie by Peter Loewen(Universty of Manitoba, Canada)
FeIV
O
Fe
M = Pt, Ru, IrYoungblood et al. J. Am. Chem. Soc. 2009, 131, 926–927D. Balcells, Adv. Org. Chem. 2016
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Summary
- Sugars have many shapes, and enzymes take advantage of this to accelerate
catalysis.
- Protein glycosylation is governed by a flexible enzyme that captures the
target protein.
- Enzymes can be redesigned to produce energy.
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Acknowledgments
Current and former group membersXevi Biarnés (IQS, Barcelona)Víctor Rojas-Cervellera (Barcelona)Albert Ardèvol (MPI, Frankfurt)Javier Iglesias-Fernández (KCL, London)Lluís Raich (UB, Barcelona)Mercedes Alfonso-Prieto (UB, Barcelona)Pietro Vidossich (UAB, Barcelona)Theoretical collaboratorsAgustí Lledós (UAB, Barcelona)Peter Reilly (Iowa State University)
Experimental collaborators:Antoni Planas (IQS, Spain)Ignacio Fita (CSIC, Spain)Peter C. Loewen (U. Manitoba, Canada)Gideon J. Davies (U. York, UK)Spencer Williams (Melbourne U, Australia)Henrik Clausen (U. Copenhaguen, Denmark)David Vocadlo (SFU, Canada)Ramón Hurtado-Guerrero (BIFI, Spain)