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Understanding Calcium Channel Selectivity: Crowding, Charge, and Protein Properties

This presentation explores how calcium channels select calcium ions over sodium ions, focusing on the role of crowding, charge, and protein properties. It also discusses the importance of protein measures and induced fit in determining selectivity. The presentation concludes with a discussion on the computation of structures that determine selectivity and the potential applications of this knowledge in creating calcium channels using molecular genetics techniques.

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Understanding Calcium Channel Selectivity: Crowding, Charge, and Protein Properties

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  1. Dear Susan, The following slides (until the next black one) should answer your question “How DOES the channel select calcium?

  2. Selectivity comes from Crowding Other Properties of Ion Channels are likely to involve more subtle physics including orbital delocalization and chemical binding Selectivity apparently does not! Nonner and Eisenberg

  3. Ionic Selectivity in Protein Channels Crowded Charge Mechanism Simplest Version: MSA How qualitatively doesCrowded Charge give Selectivity? (Real answer is the equations, of course.)

  4. Ionic Selectivity in Protein Channels Crowded Charge Mechanism 4 Negative Chargesof glutamates of protein DEMAND 4 Positive Chargesnearby either 4 Na+ or 2 Ca++ Nonner and Eisenberg

  5. 2 Ca++ areLESS CROWDEDthan 4 Na+ Nonner and Eisenberg

  6. Ionic Selectivity in Protein Channels Crowded Charge Mechanism Simplest Version: MSA 2 Ca++ areLESS CROWDEDthan 4 Na+, Ca++SHIELDS BETTERthan Na+, so Protein Prefers Ca++because Ca++ is less crowded Nonner and Eisenberg

  7. What does the protein do? Protein provides Mechanical StrengthVolume of PoreDielectric Coefficient/BoundaryPermanent ChargePrecise Arrangement of Atoms is not involved in the model, to first order. butParticular properties (‘measures’) of the protein are crucial! Nonner and Eisenberg

  8. What does the protein do? Certain MEASURES of structure are PowerfulDETERMINANTSof Functione.g., Volume, Dielectric Coefficient, etc. Induced Fit Model of SelectivityAtomic Structure is not pre-formedAtomic Structure is an important output of the simulation Nonner and Eisenberg

  9. What does the protein do? Protein maintains Mechanical Forces*Volume of PoreDielectric Coefficient/BoundaryPermanent Charge Induced Fit Model of Selectivity * Driving force for conformation changes ?? Nonner and Eisenberg

  10. Binding Sites* are outputsof our Calculations Our model has no preformedstructural binding sites but Selectivity is very Specific *Selectivity is in the Depletion Zone,NOT IN THE BINDING SITEof the DEKA Na Channel

  11. Induced Fit Model • Selectivity depends on Induced Fit of Side Chains and Ions • Induced Fit is the Self-Organized Structure withMinimal Free Energy Energy and Entropy

  12. Induced Fit Model • Monte Carlo computes the Structure of Minimal Free Energy • Monte Carlo computes the Induced Structure ‘perfectly’* *but the model itself is far from perfect Energy and Entropy

  13. Selectivity Depends Sensitively on Self-organized Structure and their Flexibility Induced Structure is Different in Different Solutions so Structure must be Computed! Rate constants are variables that change dramatically with conditions

  14. Computation Starts From Crystal Structure when available but Crystal Structures cannot determine Selectivity because 1) Crystal Structures are measured in only one unphysiological solution 2) Crystal Structures are not accurate enough 3) Crystal Structures do not give entropy

  15. Miracle We can actually compute the Structures that determine Selectivity

  16. Specificity “There is only one word that matters in biology and that is specificity.The truth is in the details, not the broad sweeps.”* if the detail is computed with the correct broad sweeps of physics† †Bob Eisenberg’s opinion*Aaron Klug quoted in the first sentence of Pearson Nature (2008) 455:160–164

  17. Selectivity can be understood by Reduced Models KchannelsBenoît Roux Susan Rempe Na & Ca channelsNonner,et al, RyRchannelsGillespie & Meissner Best Evidence Conclusion

  18. How can we use the theory? Make a Calcium Channel using techniques of molecular genetics, site-directed Mutagenesis George Robillard, Henk Mediema, Wim Meijberg BioMaDe Corporation, Groningen, Netherlands

  19. Dear Susan, The following slides give my story with the math and detailed experiments left out.

  20. Chemist’s View IonChannelsProteins with a Hole All Atoms View Chemical Bonds are lines Surface is Electrical Potential Red is negative = acid Blue is positive = base ~30 Å Figure by Raimund Dutzler

  21. Ion Channels are Biological Devices,the Valves* of Cells Main Controllers of Biological Function K+ Flow time scale is 0.1 msec to min ~30 Å Chemical Bonds are lines Surface is Electrical Potential Redis negative (acid) Blueis positive (basic) *Pun: Valve=VacuumTube≈PNPTransistor≈FET Transistor BritSpeak Figure of ompF porin by Raimund Dutzler

  22. Ions in Water are theLiquid of Life Life Occurs in ~130 mM salt solutions Ionic Solutions are NOT ideal. Chemically Specific Properties of Ionic solution are their DEVIATION from IDEAL

  23. K+ ~30 Å Ion Channels are Biological Devices Natural nano-valves* for atomic control of biological function Ion channels coordinate contraction in the heart, allowing the heart to function as a pump Ion channels coordinate contraction in skeletal muscle Ion channels control all electrical activity in cellsIon 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 pico-meters

  24. Goal: Understand Selectivity Selectivity Differsin Different Types of Channels Wolfgang Nonner, Dirk Gillespie, Douglas Henderson, Dezső Boda

  25. Selectivity of Different Channel Types Studied in Many Solutions RyR Channel CalciumChannel Sodium Channel Synthetic Ca Channel Selectivity filter DDDD 4− charges Selectivity filter EEEE 4− charges Selectivity filter DEKA 2−, 1+ charge Selectivity filter Variousmany − charges PNP/DFT PNP/DFT Monte Carlo Monte Carlo PNP/DFT RyR model of Gillespie is best worked out for ~ 120 solutions Selectivity of K Channel is studied in ~1 solution K channel of Benoît Roux has much more detail than our modelsQuantum Water/K+ of Susan Rempe has much more detail than our models Nonner, Gillespie, Henderson, Boda

  26. “There is only one word that matters in biology and that isSpecificity ....” Aaron Klug quoted in the first sentence of H. Pearson, Nature (2008) 455:160-164

  27. Goal: Understand Selectivity well enough toFit Large Amounts of Data and to Make a Calcium Channel

  28. Channels are only Holes Why can’t we understand and build them? Must have high quality measurements Must know physical basis of function Where do we start?Not with gas phase models of traditional channology Liquids are not Gases Not with guesses about trajectories of structural biologistsCounting and Statistics are essential

  29. Active Sites of Proteins are VeryCharged 7 charges ~ 20 M net charge = 1.2×1022 cm-3 Pure water is 55 M Induced Fit of Side Chains + + + 1 nM=10Å + - + K+ K+ - Induced Fit of Side Chains - - Selectivity Filters and Gates of Ion Channels are Active Sites OmpF Porin Ions are Crowded Figure adapted from Tilman Schirmer

  30. Ions in Water are the Liquid of Life Life Occurs in ~130 mM salt solutions Ionic Solutions are NOT ideal Chemically Specific Properties of Ionic solution are their DEVIATION from IDEAL

  31. Finite Size EffectsWorking Hypothesis Chemically Specific Properties of ions (e.g. activity= free energy per mole) come from their Diameter and Charge and dielectric ‘constant’ of ionic solution Learned from Doug Henderson, J.-P. Hansen, Stuart Rice, among others…Thanks!

  32. Selective Binding Curve L type Ca Channel Wolfgang Nonner

  33. Selectivity FilterCrowded with Charge Selectivity Filter O½ Wolfgang Nonner L type Ca Channel + ++ “Side Chains”

  34. large mechanical forces

  35. Crowded Ions Snap Shots of Contents Radial Crowding is Severe ‘Side Chains’are SpheresFree to move inside channel 6Å Parameters are Fixed in all calculations in all solutions for all mutants Experiments and Calculations done at pH 8 Boda, Nonner, Valisko, Henderson, Eisenberg & Gillespie

  36. Selectivity Filter is aSelf-Organized Structure with Side Chains at position of Minimum Free Energy The Protein Fits the Substrate “Induced Fit Model of Selectivity”

  37. Mutation Na Channel Ca Channel Same Parameters E E E A D E K A Charge -3e Charge -1e 1 0.004 Na+ Ca2+ Na+ Occupancy (number) 0.5 0.002 Ca2+ 0 0 -6 -4 -2 0 0.05 0.1 log (Concentration/M) Concentration/M EEEE has full biological selectivityin similar simulations Boda, et al

  38. Calcium Channelhas been examined in ~32 papers, e.g., Most of the papers are available athttp://www2.phys.rush.edu/RSEisenberg/physioeis.html Now, the Sodium Channel

  39. Today, the Sodium Channel specifically, the Aspartate DAcid Negative Glutamate EAcid Negative Lysine KBasicPositive Alanine A Aliphatic Neutral DEKASodium Channel 6 Å

  40. DEKASodium Channel has very different properties from Ca channel,e.g., ‘binding’ curve,Na+ vs Ca++ selectivity Na+ vs K+ selectivity

  41. Mutation Na Channel Ca Channel Same Parameters E E E A D E K A Charge -3e Charge -1e 1 0.004 Na+ Ca2+ Na+ Mutation Occupancy (number) 0.5 0.002 Same Parameters Ca2+ 0 0 -6 -4 -2 0 0.05 0.1 log (Concentration/M) Concentration/M EEEE has full biological selectivityin similar simulations Boda, et al

  42. DEKA Na Channel SelectsNa+vs. K+Nothing was changedfrom the EEEA Ca channelexcept the amino acids Calculations and experiments done at pH 8

  43. Binding SitesNa+ SelectivityNot in binding Na+ Na+ Selectivity Filter K+ K+ Na Selectivity because 0 K+in Depletion Zone Depletion Zone Size Selectivity is in the Depletion Zone Na+vs. K+ Occupancy Channel Protein [NaCl] = 50 mM[KCl] = 50 mM Concentration [Molar] Calculations and experiments done at pH 8 of the DEKA Na Channel, 6 Å Boda, et al

  44. Size Selectivity log C/Cref Selectivity Filter Na vs K Size Selectivity is in Depletion Zone BLACK=Depletion=0 *Binding Sites are outputs of our INDUCED FIT Model of Selectivity, not structural inputs Binding Sites NOT selective Selectivity Filter Selectivity Filter [NaCl] = [KCl] = 50 mM Selectivity Filter Selectivity Filter Selectivity Filter Selectivity Filter Lys or K Selectivity Filter D or E Boda, et al

  45. Control Variablesare obvious in simulations of the Na channel,but not the Ca channel

  46. Control Variablesin DEKA Na channel • SelectivityNa+ vs K+ depends only on pore diameter Diameter controls Selectivity

  47. Na+ 2.00 Å K+ Na+ K+ 2.66 Å 6 8 10 Small Channel Diameter Largein Å Boda, et al Na+ vs K+(size) Selectivity (ratio)Depends on Channel Size,not ProteinDielectric Coefficient* Selectivity for small ion *inDEKA Na Channel

  48. Control Variables in DEKA Na channel • SelectivityNa+ vs K+ depends only on pore diameter • Conductance* depends on protein polarization Protein Dielectric Coefficient controls Conductance *Gillespie & Boda (2008) Biophysical Journal 95:2658

  49. Na+  410-5 210-5 Control VariableOccupancy depends on Protein Dielectric Occupancy# (Na) 20 60 Dielectric Coefficient of Protein Boda, et al,

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