1 Ion Channels are the Valves of Cells Ion Channels are the Main Controllers of Biological Function Chemical Bonds are lines Surface is Electrical Potential Red is negative (acid) Blue is positive (basic) Selectivity Different Ions carry Different Signals Figure of ompF porin by Raimund Dutzler ~30 Å 0.7 nm = Channel Diameter + Ions in Water are the Liquid of Life 3 Å K + Na + Ca ++ Hard Spheres
93
Embed
Ion Channels are the Valves of Cells Ion Channels are the Main Controllers of Biological Function
+. ~ 30 Å. Ion Channels are the Valves of Cells Ion Channels are the Main Controllers of Biological Function. Ions in Water are the. Selectivity Different Ions carry Different Signals. Liquid of Life. Na +. Hard Spheres. Ca ++. Chemical Bonds are lines - PowerPoint PPT Presentation
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
1
Ion Channels are the Valves of CellsIon Channels are the Main Controllers of Biological Function
Chemical Bonds are linesSurface is Electrical Potential
Red is negative (acid)Blue is positive (basic)
Selectivity
Different Ions carry
Different Signals
Figure of ompF porin by Raimund Dutzler
~30 Å
0.7 nm = Channel Diameter
+
Ions in Water are the
Liquid of Life
3 Å
K+
Na+
Ca++
Hard Spheres
2
Ion Channels are the Valves of CellsIon Channels are the Main Controllers of Biological Function
Chemical Bonds are linesSurface is Electrical Potential
Red is negative (acid)Blue is positive (basic)
Selectivity
Different Ions carry
Different Signals
Life occurs in
~130 mM salt solutions
Figure of ompF porin by Raimund Dutzler
~30 Å
Flow time scale is 0.1 msec to 1 min
0.7 nm = Channel Diameter
+
Averaging is in time, from 10-16 atomic scale to 10-4 biological scale!
Averaging is in number over 1012 water molecules needed to
specify 10-7M concentrationsand other ‘thermodynamic’ variables
Multiscale
3 Å
K+
Na+
Ca++
Hard Spheres
3
Multiscale Issuesmore later
Biological Scales Occur Togetherso must be
Computed TogetherThis may be impossible in simulations
Physicists and Engineers have not tried
Computational Scale
Biological Scale
Ratio
Time 10-15 sec 10-4 sec 1011
Space 10-11 m 10-5 m 106
Spatial Resolution 1018
Solute Concentration 1011
Three Dimensional (106)3
4
Natural nano-valves* for atomic control of biological function
Ion channels coordinate contraction of cardiac muscle, allowing the heart to function as a pump
Ion channels coordinate contraction in skeletal muscle
Ion channels control all electrical activity in cells
Ion channels produce signals of the nervous system
Ion channels are involved in secretion and absorption in all cells: kidney, intestine, liver, adrenal glands, etc.
Ion channels are involved in thousands of diseases and many drugs act on channels
Ion channels are proteins whose genes (blueprints) can be manipulated by molecular genetics
Ion channels have structures shown by x-ray crystallography in favorable cases
*nearly pico-valves: diameter is 400 – 900 picometers
Ion Channels are Biological Devices
~30 Å
K+
Thousands of Molecular Biologists
Study Channels every day,
One protein molecule at a timeThis number is not an exaggeration.
We have sold >10,000 AxoPatch amplifiers
5
Ion Channel Monthly
AxoPatch 200B
Channels are parts of Machines, e.g., Excitation-Contraction Coupling
L type Ca Channel RyR ryanodine receptor
L-type Ca Channel
RyR
Thanks for the figure toLászló Csernoch, Debrecen, HungaryIsabelle Marty, Grenoble, France
2Ca
7
Function of SINGLE isolated RyR Channelsin Artificial Planar Lipid Bilayers
AxoPatchPatch-Clamp
Amplifier
ExperimentalChamber
PlanarBilayer
80-100 µMDiameter
TeflonSepta
FusedVesicle
Ca
Single Channel Current
open
closed
Designed at Rush
Slide from Mike Fill
Thanks!
.
Open
ClosedCurrent
Amplitudein Picoamps (pA)
OpenDuration
in Milliseconds (ms)
current
# e
ven
ts
log time
ClosedDuration
in Milliseconds (ms)
log time
time time
# e
ven
ts
# e
ven
ts
# e
ven
ts
# e
ven
ts
Gating is Time Behavior
Selectivity,Permeation
are Amplitude
Gating and Permeation
9
1 100
2
4
6
8
10
Open Duration /ms
Ope
n Am
plitu
de, p
ALowpass Filter = 1 kHz Sample Rate = 20 kHz
Ca2+ Release Channel of Inositol Trisphosphate Receptor : slide and data from Josefina Ramos-Franco. Thanks!
Typical Raw Single Channel Records
Current vs. time Amplitude vs. Duration
Channel Structure Does Not Changeonce the channel is open
5 pA
100 ms
10
3 Å
K+
Na+
Ca++
Channels are SelectiveDifferent Ions Carry Different Signals through Different Channels
Figure of ompF porin by Raimund Dutzler
~30 ÅFlow time scale is 0.1 msec to 1 min
0.7 nm = Channel Diameter
+
ompF porin
11
Different Types of Channelsuse
Different Types of Ions for
Different Information
Channels are Selective
Central Problem*
How does the channel control selectivity?
*an example of “Reverse Engineering”
12
For Modelers and Mathematicians: This is an inverse problem!
13
Goal:
Understand Selectivity well enough to
Fit Large Amounts of Data* and to
Make a Calcium Channel
*from many non-ideal solutions
Atomic Scale Macro Scale
14
Mutants of ompF Porin
30 60
-30
30
60
0
pA
mV
LECE (-7e)
LECE-MTSES- (-8e)
LECE-GLUT- (-8e)ECa
ECl
WT (-1e)
Calcium selective
Experiments have built
Two Synthetic Calcium Channels
As density of permanent charge increases, channel becomes calcium selective Erev ECa
Unselective
Wild Type
built by Henk Miedema, Wim Meijberg of BioMade Corp.,Groningen, Netherlands
Miedema et al, Biophys J 87: 3137–3147 (2004)
MUTANT ─ Compound
Glutathione derivativesDesigned by Theory
Atomic Scale
Macro Scale
Central Problem*
How does the channel control selectivity?
“Reverse Engineering”
15
This is an inverse problem
Closely related inverse problemshave been solved by mathematics used to design blast furnaces
Burger, Eisenberg, and Engl (2007) SIAM J Applied Mathematics 67:960-989
Selective Binding CurveL type Ca channel
16
Wolfgang Nonner
Inverse Problem for SelectivityBadly posed,
simultaneously over and under determined
with noise and systematic error
has actually been solvedusing methods for the
Inverse Problem of a Blast Furnace
17
Burger, Eisenberg and Engl (2007) SIAM J Applied Math 67: 960-989
For Modelers and Mathematicians: This is reverse engineering!
18
Channels are only HolesWhy can’t we understand and build them?
Helpful to know physical basis of functionif we want to build one and improve it
Where do we start?
Not with Molecular Mythology
Not with gas phase models of traditional channologyLiquids are not Gases; biological solutions are not ideal
Not with guesses about trajectories of structural biologistsCounting, Statistics, and Averaging are Essential
19
Why can’t we understand and build channels?
Uncalibrated Simulations will not make devices that
actually work
Unpopular view because Calibration is Hard Work
20
Multiscale Issuesare the key
if we want to actually build channels that work
Computational Scale Biological Scale Ratio
Time 10-15 sec 10-4 sec Action Potential 1011
Space 10-11 m 10-5 m Side Chains of Proteins 106
Spatial Resolution 1018
Solute Concentration 10-11 to 20 Molar 1012
Three Dimensional (106)3
21
Multiscale Issues
Biological Scales Occur Togetherso scales must be
CALIBRATED TOGETHERin real biological solutions
that are
MIXTURES OF IONS
Computational Scale Biological Scale Ratio
Time 10-15 sec 10-4 sec Action Potential 1011
Space 10-11 m 10-5 m Side Chains of Proteins 106
Spatial Resolution 1018
Solute Concentration 10-11 to 20 Molar 1012
Three Dimensional (106)3
22
Multiscale Issues
Calibrations of Molecular Dynamics
in Real Solutions are just starting!
Unpopular Reality: hard work
It may not be possible to deal with scale ratios of1011 , 106 ,1018 , 1012 all at once
23
Physicists and Engineers do not even try!
It may not be possible to deal withRatios of Scales
of
1011 106 1018 1012
all at once
Multiscale Issues
24
Channels are only HolesWhy can’t we understand and build them?
Where do we start?
Science as Usual
Guess and Check
25
Working Hypothesis
Biological Adaptation is
Crowded Ions and Side Chains
Active Sites of Proteins are Very Charged 7 charges ~ 20 M net charge
Selectivity Filters and Gates of Ion Channels are
Active Sites
= 1.2×1022 cm-3
-
+ + + ++
--
-
4 Å
K+
Na+
Ca2+
Hard Spheres
26
Figure adapted from Tilman
Schirmer
Pure water is 55 M OmpF Porin
Physical basis of function
Induced Fit of
Side Chains
Ions are Crowded
K+ Na+
27
Working Hypothesis
Biological Adaptation is
Crowded Ions and Side Chains
Everything interactsClassical Models and Force Fields of Molecular Dynamics
assume no interactions with ion concentrations
28
Finite Size EffectsWorking Hypothesis
‘Primitive Implicit Solvent Model’ learned from Doug Henderson, J.-P. Hansen, Stuart Rice, among others…
Thanks!
Chemically Specific Properties
of ions (e.g. activity = free energy per mole) come from interactions of their
Diameter and Charge
and dielectric ‘constant’ of ionic solutionAtomic Detail
29
Ions in Water are the Liquid of Life. They are not ideal solutions
Chemically Specific Properties of Ionic Solutions come from
Interactions
Molecular Dynamics Force Fields are Calibrated assuming no interactions with concentrations
Force Fields must be REcalibrated in each Biological Solution
30
Ions in Water are the Liquid of Life. They are not ideal solutions
Chemically Specific Properties of Ionic Solutions come from
Interactions
Chun Liu’s Energetic Variational Principle deals with Interactions
EnVarA
12 0
E
Dissipative 'Force'''Conservative Force
x u
31
Everything Interacts
with
Everything
Ions in Water are the Liquid of Life
They are not ideal solutions
For Modelers and MathematiciansTremendous Opportunity for Applied Mathematics
Chun Liu’s Energetic Variational Principle EnVarA
32
Ions in Water not ideal solutions
Chemically Specific Properties Come from Interactions
12 0
E
Dissipative 'Force'''Conservative Force
x u
Variational Principles Deal with Multiple Scales and Interactions Consistently and Automatically
Chun Liu’s Energetic Variational Principle deals with Interactions
EnVarA
33
12 0
E
Dissipative 'Force'''Conservative Force
x u
Variational Principles Deal with Multiple Scales Consistently and Automatically
New Component or Scaleof Energy or Dissipation implies
New Field Equations (Euler Lagrange)
by Algebra AloneNo new Assumptions
EnVarA
Page 34
Energetic Variational ApproachEnVarA
Chun Liu, Yunkyong Hyon, and Bob Eisenberg
Mathematicians and Modelers: two different ‘partial’ variationswritten in one framework, using a ‘pullback’ of the action integral
12 0
E
'' Dissipative 'Force'Conservative Force
x u
Action Integral, after pullback Rayleigh Dissipation Function
Field Theory of Ionic Solutions that allows boundary conditions and flow and deals with Interactions of Components self-consistently
Composite
Variational Principle
Euler Lagrange Equations
Page 35
Energetic Variational Analysis EnVarA
being developed by Chun Liu with
creates a newMultiscale Field Theory of Interacting Components
that allows boundary conditions and flow and deals with
Ions in solutions self-consistently
(1) Yunkyong Hyon, Bob Eisenberg. Ions in Channels
(2) Rolf Ryham, Bob Eisenberg and Fred Cohen. Virus fusion to Cells
(3) Yoichiro Mori and Bob Eisenberg. Water flow in Tissues
Multiple Scales
Page 36
We have already established that the
Implicit Solvent (“Primitive”) Model of
Ionic SolutionsDescribes Calcium and Sodium Channels
quite well at Equilibriumwithout
Preformed Structure
Structure is the Computed Consequence of the Model
37
O½
Selectivity Filter
Selectivity Filter Crowded with Charge
Wolfgang Nonner
+
++
L type Ca Channel
“Side Chains”
38
Dielectric Protein
Dielectric Protein
6 Å
μ μmobile ions mobile ions =
Ion ‘Binding’ in Crowded Channel
Classical Donnan Equilibrium of Ion Exchanger
Side chains move within channel to their equilibrium position of minimal free energy. We compute the Tertiary Structure as the structure of minimal free energy.