Combined Isothermal Titration and Differential Scanning Calorimetry Define. Three-State Thermodynamics of fals-associated Mutant Apo SOD1 Dimers

Size: px
Start display at page:

Download "Combined Isothermal Titration and Differential Scanning Calorimetry Define. Three-State Thermodynamics of fals-associated Mutant Apo SOD1 Dimers"

Transcription

1 Supporting Information for: Combined Isothermal Titration and Differential Scanning Calorimetry Define Three-State Thermodynamics of fals-associated Mutant Apo SOD1 Dimers and an Increased Population of Folded Monomer Helen R. Broom, 1 Kenrick A. Vassall, 1,2 Jessica A.O. Rumfeldt, 1 Colleen M. Doyle, 1 Ming Sze Tong, 1 Julia M. Bonner, 1,3 and Elizabeth M. Meiering 1* 1 Department of Chemistry, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada 2 Present address: Department of Molecular and Cellular Biology, University of Guelph, Guelph, Ontario, N1G 2W1, Canada 3 Present Address: Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA Corresponding Author * Department of Chemistry, University of Waterloo, Waterloo, ON N2L 3G1, Canada. Tel.: , Ext ; Fax: ; meiering@uwaterloo.ca 1

2 Supplementary Methods Models Used for Thermodynamic Analysis of Homodimeric Protein Folding. The simplest model for the unfolding mechanism of a homodimeric protein is a reversible two-state transition with concerted dissociation and unfolding of the native dimer (N 2 ) to unfolded monomers (U), which can be expressed as: N 2 K(T) 2U (S1) [N 2 ] = P dimer (1 α) [U] = 2P dimer (α) (S2) (S3) where K(T) is the equilibrium constant for unfolding at any temperature T, P dimer is the total protein concentration in M dimer and α is the extent of the unfolding reaction. K(T) is defined as: K(T) = [U]2 = 4P dimerα 2 [N 2 ] (1 α) (S4) To determine the extent of the unfolding reaction at any temperature, eq S4 can be rearranged as: α = K(T)+ K(T)(K(T)+16P dimer) 8P dimer (S5) The heat capacities of the native ( C p N 2 ) and unfolded (C p U ) protein are usually taken to vary linearly with temperature 1-4 (see Material and Methods): C p N 2 = A + Bt (S6a) C p U = E + Ft (S6b) where A (E) and B (F) are the intercept and slope of the folded (unfolded) baseline and t is the temperature in C. The change in heat capacity of unfolding ( C p ) can be determined at any temperature: C p (t) = (E A) + (F B)t (S7) 2

3 The specific calorimetric enthalpy of the unfolding transition in cal (g protein) -1 as a function of temperature can be written as: h cal (t) = t t ref C p dt = h cal (t ref ) + (E A)(t t ref ) + 1 (F B)(t 2 2 t 2 ref ) (S8) where t ref is a reference temperature typically set at the temperature of half completion and h cal (t ref ) is the h cal at t ref. Note that when the pre and post transition baselines have the same slope, the C p is constant with temperature and eq S8 simplifies to h cal (t) = h cal (t ref ) + (E A)(t t ref ) which has been shown to be a reasonable approximation over 1, 3, 5, 6 modest temperature intervals. For fitting, h cal (t) is extrapolated to 0 C to give: h 0 = h cal (t ref ) (E A)(t ref ) 1 (F B)(t 2 2 ref) (S9) Now h cal can be calculated at any temperature t using: h cal (t) = h 0 + (E A)t (F B)t (S10) 2 The temperature-dependence of K is given by the van t Hoff equation: dlnk(t) dt = H vh(t) RT 2 = β h cal(t) RT 2 (S11) where β = H vh (T) h cal (T) and R is the gas constant, T is the temperature in units of Kelvin, and ΔH vh is the van t Hoff enthalpy for the change in enthalpy for unfolding. Note that ΔH vh has units of cal (mol cooperative unit) -1 which, for this model, is cal (mol dimer) -1 and is distinct from the calorimetrically determined change in enthalpy H cal = h cal. ΔH vh reflects the steepness of the transition and H cal is proportional to the area under the endothermic peak. Here, β is used as a fitting parameter to allow these two terms to differ. In a strictly two-state transition the ratio of 3

4 ΔH vh to H cal is unity and β is equal to the molecular weight of the cooperative unit, in this case the dimer. In non-2 state transitions, for example involving intermediate formation, the ratio < 1; if samples are not normalized correctly for protein concentration the ratio can be higher or lower than 1. To obtain K as a function of temperature, eq S10 can be substituted into eq S11, integrated and rearranged giving: T d ln K(T) = ln K = β T ref K ref R T T ref h cal (T) T 2 dt (S12) R β ln (K(T) K ref ) = AA ( 1 T 1 T ref ) + BBln ( T T ref ) + CC(T T ref ) (S13) where: AA h (E A) 1 2 (273.15)2 (F B) BB (E A) (273.15)(F B) CC 1 (F B) 2 T = t Solving for K gives, K(T) = K ref exp {[AA ( 1 T 1 T ref ) + BBln ( T T ref ) + CC(T T ref )] R β } (S14) The total measured heat capacity (C p,total ) corresponds to a baseline heat capacity (C p, baseline ) plus the transition excess heat capacity resulting from the absorption of heat which drives the unfolding reaction (C p,excess ): C p,total = C p,baseline + C p,excess (S15) C p, baseline is given by: C p,baseline = (1 α(t))c p N 2 + α(t)c p U (S16) 4

5 The C p,excess is given by: C p,excess = ( α T ) h cal(t) (S17) The partial derivative α can be solved analytically at any T (substituting K with eq S4): T dlnk(t) dt = H vh(t) RT 2 = β h cal (T) RT 2 = 2 dα + 1 dα α dt 1 α dt (S18) which can be rewritten as: dα = β h cal(t) α(1 α) dt RT 2 2 α (S19) Note that parameters such as h cal are defined at a specific temperature regardless of the temperature units so that h cal (T) is the same value as h cal (t). Combining S19 and S17, the excess specific heat can be written as: C p,excess = β h 2 cal (t) α(1 α) RT 2 2 α (S20) Dimer Three-State with Monomer Intermediate Unfolding Model. For homodimeric proteins, more complex unfolding transitions may be observed. While many different unfolding mechanisms are possible, thermal unfolding is often described using a three-state transition model with a folded monomeric intermediate (M). This three-state transition model involves two steps: (1) dimer dissociation, followed by (2) monomeric intermediate unfolding: K 1 (T) N 2 2M K 2(T) 2U (S21) [N 2 ] = P dimer (1 α 1 ) [M] = 2P dimer α 1 (1 α 2 ) [U] = 2P dimer α 1 α 2 (S22) (S23) (S24) 5

6 where K 1 (T) and α 1, and K 2 (T) and α 2 are the equilibrium constant and extent of the unfolding reaction at any temperature for the first (N 2 2M) and second (M U) unfolding transitions, respectively. K 1 (T) = [M]2 = 4P α 2 1 (1 α 2 ) 2 [N 2 ] dimer 1 α 1 K 2 (T) = [U]2 α 1 = = α 2 2 [M] 2 (1 α 2 ) P dimer K 1 (T)(1+ K 2 (T)) 2 (S25a) (S25b) (S26a) α 2 = K 2(T) 1+ K 2 (T) (S26b) The specific heat capacity for M is assumed to be linear with temperature as for N 2 and U in eqs S6a and S6b. C p M = C + Dt (S27) where C and D are the intercept and slope of the folded (unfolded) baseline. The change in heat capacity of dimer dissociation (ΔC p,n2 2M) and monomer unfolding (ΔC p,m U ) can be determined at any temperature: ΔC p,n2 2M (t) = (C A) + (D B)t ΔC p,m U (t) = (E C) + (F D)t (S28a) (S28b) Using the same procedure outlined in eqs S8-S14, the equations for K 1 and K 2 as a function of temperature are: K 1 (T) = K ref 1 exp {[AA1 ( 1 1 ) + BB1ln ( T ) + CC1(T T T T ref 1 T ref 1 )] R } (S29a) ref 1 β K 2 (T) = K ref 2 exp {[AA2 ( 1 1 ) + BB2ln ( T ) + CC2(T T T T ref 2 T ref 2 )] R } (S29b) ref 2 β where: 6

7 AA1 h (C A) 1 2 (273.15)2 (D B) BB1 (C A) (273.15)(D B) CC1 1 (D B) 2 AA2 h (E C) 1 2 (273.15)2 (F D) BB2 (E C) (273.15)(F D) CC2 1 (F D) 2 and K ref-1 and K ref-2 are the equilibrium constants at the reference temperatures for dimer dissociation and monomer unfolding, respectively (which in the present study we take to be the experimental temperature for measurement of K ref-1 i.e. 37 C, and the temperature of the midpoint for monomer unfolding where K ref-2 =1, respectively, see below and Table S1). Using eqs S18, S25a and S25b: dα 1 dt = (β 1 h cal1 (T) RT 2 + α 2β 2 h cal2 (T) RT 2 ) α 1(1 α 1 ) 2 α 1 (S30a) dα 2 dt = β 2 h cal2 (T) 2RT 2 α 2 (1 α 2 ) (S30b) For simplicity the subscripts 1 and 2 were used for the parameters and h cal as well as, to refer to dimer dissociation and monomer unfolding, respectively, so that h cal1 h caln2 2M and h cal2 h calm U. Also: C p,excess = dα 1 dt h cal1 (t) + (dα 1 dt α 2 + dα 2 dt α 1) h cal2 (t) C p,baseline = f N2 C p N 2 + f M C p M + f U C p U (S31) (S32) where f N2, f M and f U are the fractions of native dimer, monomer intermediate and unfolded monomer, respectively, and can be calculated using: 7

8 f N2 =(1 α 1 ) f M=α1 (1 α 2 ) f U=α1 α 2 (S33a) (S33b) (S33c) where f N2 + f M + f U = 1 (S33d) Methods for Simplifying the Dimer Three-State with Monomer Intermediate Unfolding Model. Due to the additional parameters in the three-state model compared to the two-state model, fitting individual thermograms to eq 3 resulted in high uncertainties in the fitted values. Accordingly, multiple datasets were fit globally (Matlab R2013b, The MathWorks Inc.) using shared parameters. The slopes of the monomer intermediate and unfolded monomer baselines were set equal to that of the native baseline (i.e., B=D=F), making the common assumption that ΔC p of unfolding is temperature independent (Figure S3), 1, 3, 5 which has been shown to be reasonable over limited temperature ranges as used here. 7 The intercepts of the intermediate (C) and unfolded (E) baselines were defined relative to the intercept of the native baseline using temperature-independent values for the change in heat capacity upon dimer dissociation to monomer intermediate (ΔC p,n2 2M) and the change in heat capacity upon monomer intermediate unfolding (ΔC p,m U ): C= A + ΔC p,n2 2M (S34a) E= A + ΔC p,n2 2M + ΔC p,m U (S34b) ΔC p,n2 2M was set to 1.7 kcal (mol dimer) -1 C -1 (and the corresponding value in units of kcal g -1 C -1 obtained by dividing by the molecular weight of the dimer), the average value measured 8

9 using Kirchoff analysis of ITC data for SOD1 variants where the enthalpy of dimer dissociation was measured as a function of temperature. 4, 8, 9 For the three-state model, ΔC p,n2 2M + ΔC p,m U = ΔC p.n2 2U (total ΔC p of apo SOD1 unfolding from folded dimer to unfolded monomers); the value of ΔC p,m U was obtained by subtracting ΔC p,n2 2M from the experimentally determined value for ΔC p,n2 2U of 3.3 kcal (mol dimer) -1 C -1, 1 which gives a value of 1.6 kcal (mol dimer) -1 C -1 or 0.8 kcal (mol monomer) -1 C -1. This approach is consistent with the observations that 4, 10 mutations typically cause little change in ΔC p and that the average directly fitted values of ΔC p,n2 2U for apo SOD1 mutants (Table 1) are close to the value of 3.3 kcal (mol dimer) -1 C -1 determined for pwt and G93 mutants. 11, 12 Of note, lower values of ΔC p,n2 2U for A4V and V148G (Table 1) are likely related to increased monomer formation, which is most pronounced for these dimer interface mutants (Figure 1). To further simplify the fitting, the parameters of the first transition (dimer dissociation) were fixed to values determined by ITC (Figure S1). 10 Specifically, the K ref-1 was set to the value measured by ITC, K d,n2 2M, and the associated t ref-1 (T ref-1 ) was fixed to 37 C ( K), the temperature where ITC was performed. The h cal1 (t ref 1 ) was fixed to the value determined by ITC at 37 C, h caln2 2M. Thus, in fitting data to eqs S31 and S32, the globally shared fitted parameters were: t ref 2, h cal2 (t ref 2 ) (same as h calm U (t ref 2 )), β1 = β2, and parameters defining the slope and intercept of the native baselines. Two-State Monomer Unfolding Model. DSC data for apo mutants showing evidence for significant monomer formation (A4V, H46R, and V148G) were also analyzed using a monomer two-state unfolding model describing a reversible transition from folded monomer (M) to 9

10 unfolded monomers (U), M U. 4 Individual thermograms were fit (using Origin 5.0, Microcal Inc) to eq S35: C p = (C + Dt)(1 α) + (E + Ft)α + β h 2 cal (t0.5 )α(1 α) (S35) RT 2 where C p is the total specific heat absorption at temperature t (in C); C and E are the intercepts of the folded and unfolded baselines, respectively; D and F are the slopes of the folded and unfolded baselines, respectively; R is the universal gas constant; β is the ratio of van t Hoff to calorimetric enthalpy multiplied by the molecular weight of the SOD dimer; Δh cal is the specific calorimetric enthalpy of unfolding at t; α is the extent of the unfolding reaction; and t 0.5 is the temperature at which unfolding is half complete (i.e α =0.5). Predicting ΔC p,n2 2M Based on Changes in Solvent Accessible Surface Area (ΔASA). The polar and non-polar contributions to ΔASA (ΔASA p andδasa np, respectively) between dimer and dissociated monomers were determined using the crystallographic structures for apo SOD1 wildtype (1HL4) using: ΔASA p = ASA mona-p + ASA monb-p ASA dimer-p (S36a) ΔASA np = ASA mona-np + ASA monb-np ASA dimer-np (S36b) where ASA mona-p and ASA monb-p are the polar, ASA mona-np and ASA monb-np are the non-polar solvent accessible surface areas of the folded monomers A and B, respectively, which together make up the dimer in the crystal structure, and ASA dimer-p and ASA dimer-np are the polar and non-polar solvent accessible surface areas, respectively, of the folded dimer. These values were calculated using InterProSurf. 1 10

11 equations: The ΔC p,n2 2M can be predicted using ΔASA p and ΔASA np and the empirically derived ΔC p,n2 2M = x ΔASA np x ΔASA p 13 (S37a) ΔC p,n2 2M = x ΔASA np x ΔASA p 14 (S37b) ΔC p,n2 2M = x ΔASA np x ΔASA p 15 (S37c) ΔC p,n2 2M = x ΔASA np x ΔASA p 5 (S37d) An average ΔC p,n2 2M value of 0.45 ± 0.12 kcal (mol dimer) -1 C -1 was determined based on eqs S37a-d and using predicted ΔASA np and ΔASA p of 1262 Å 2 and 258 Å 2, respectively. 16 Calculation of Thermodynamic Parameters. Assuming a temperature-independent ΔC p, which has been shown to be a reasonable approximation over modest temperature intervals 17 the ΔH as a function of temperature is: H(T) = H(T ref ) + C p (T T ref ) (SA1) where T ref is a reference temperature in degrees Kelvin, and ΔH(T ref ) and ΔH(T) are the change in enthalpy of unfolding at T ref and T, respectively, noting again that T t and ΔH(T ref ) is the same value as ΔH(t ref ). The temperature-dependence for the change in entropy for unfolding, S, is given by: S(T) = S ref + C p ln ( T T ref ) (SA2) The above equations can be combined to give the Gibbs-Helmholtz equation: G(T) = RT ln K(T) = H(T ref ) (1 T ) + C T p [T (T ref ) T ln ( T )] ref T ref (SA5) 11

12 The calculations for figures and tables were performed as follows using information in Table S1. 1. H cal at t ref in cal (mol dimer) -1 was calculated by multiplying h cal (t ref ) by the corresponding. 2. G as a function of temperature was calculated using eq SA5 and the associated H cal and C p.(refer to Table S1). 3. Fractions (f) were calculated by solving the quadratic equations using equilibrium constants for the associated transitions (K 1, K 2 ) calculated as a function of temperature using the corresponding G values. For each temperature, f U (two-state) or f M (three-state) were determined by solving the quadratic equation using the equilibrium constants K (two -state) or K 1 and K 2 (three-state) which were calculated from G at each temperature using equation SA5 and a given protein concentration. For the three-state model, f U was then calculated knowing f U = f M K 2. The fraction of the final species f U (two -state) and f N2 (three-state) were determined knowing they add to As a check, fractions were also calculated for the dimer three-state model using eqs S33a-c, S26a,b and S29a,b using the appropriate fitted or fixed parameters given in Table S1. For the dimer two-state model, fractions can also be calculated by using the values and eqs S5 and S14 where f N2 = (1 α) and f U = α. 12

13 Supplementary Results We used several approaches to assess the uncertainties in monomer stability as well as total protein stability for the three-state fits. Because the ΔC p,n2 2M could not be measured for all SOD1 variants due to low heats of dissociation at low temperature, the data were also fit with the maximum ΔC p,n2 2M determined experimentally (2.2 kcal (mol dimer) -1 C -1 ) 1, 3, 5 corresponding to an estimated upper limit of mutational effects, to evaluate how changes in ΔC p may impact monomer stability. In general, mutations have been found to have little effect on ΔC p for global protein unfolding (ΔC p,n2 2U), 10 and ITC experiments show that ΔC p,n2 2M also varies little upon 4, 7, 11, 12 mutation of SOD1. Highly non-conservative substitutions at buried positions of hydrophobic residues by hydrophilic residues or vice versa have, however, been reported to change ΔC p by up to ~40%. 10 We found that comparable increase in ΔC p,n2 2M (by ~0.6 kcal (mol dimer) -1 C -1 with simultaneous decrease of ΔC p,m U by 0.3 kcal (mol monomer) -1 C -1 to keep ΔC p,n2 2U constant as 3.3 kcal (mol dimer) -1 C -1 ) has relatively small effects on ΔG M U calculated at the t avg of 51.2 C (on average ±0.1 kcal (mol monomer) -1 ) and at 37 C (on average ±0.2 kcal (mol monomer) -1 ). Because dimer dissociation was measured at 37 C, changes in ΔC p,n2 2M have no effect on ΔG N2 2M(37 C), whereas ΔG N2 2M(t avg ) is decreased by ~0.2 kcal (mol dimer) -1. Thus, for three-state fitting of DSC data, treating ΔC p as a constant is further substantiated as reasonable, and changes in ΔC p have little impact on monomer stability. We also confirmed that potential aggregation at high temperature, which we also examined previously, 18 has little effect on fitted values, by varying the amounts of fitted data beyond the peak of the unfolding endotherm from a maximum of the apparent end of the endotherm peak to a minimum of ~25% of the high temperature side of the endotherm. Fitting 13

14 various amounts of the endotherm to the three-state model has little impact on total stability: ± kcal (mol dimer) -1 at t avg, and ± kcal (mol dimer) -1 at 37 C. Also, similar stability values were obtained when ΔH vh and ΔH cal were set to equal to each other (Table S1). Based on these analyses, effects of aggregation can be effectively minimized by excluding high temperature data from the fit, with little effect on the measured stability. 14

15 Table S1. Treatment of parameters for DSC data fitting to dimer unfolding models a parameters two-state three-state N 2 2U N 2 2M (1) M U (2) t ref C t 0.5, fit a 37 C t 0.5, fit h cal (t ref ) cal g -1 fit fit fit g mol -1 fit MW dimer MW dimer or fit with 1 = 2 or fit with 1 = 2 A cal g -1 C -1 fit fit na B cal g -1 C -1 fit fit na C cal g -1 C -1 fit A + ΔC p,n2 2M A + ΔC p,n2 2M D cal g -1 C -1 B B B E cal g -1 C -1 na b na C + ΔC p,m U F cal g -1 C -1 na na B c P dimer M dimer fixed fixed fixed For calculations: K ref d C p 2P dimer K ITC 1 kcal (mol dimer) -1 C = 4P dimer (f U ) 2 + K(f U ) - K 4P dimer (f M ) 2 + K 1 (1+K 2 )f M K 1 f U = f M K 2 1 = f N2 + f U f N2 + f M + f U a The parameters for global fits using the dimer two-state or the dimer three-state with monomeric intermediate models were set to defined values or allowed to float and so fit as specified above. b na indicates not applicable. c Protein concentration fixed to values determined by UV absorbance. Although endotherms were normalized by g protein, the fitting equation uses units of M dimer. The molecular weight of SOD1 used for pwt and mutants (MW dimer ) was g/mol. d The K ref is not a fit parameter but is defined for each model. 4,6 15

16 Table S2. Thermodynamic parameters for apo SOD1 determined from global three-state fits using different shared parameters. H N2 2M G N2 2M H t M U G M U G M U G M U SOD1 0.5, M U (kcal (mol (kcal (mol variant a ( C) c (kcal (mol (kcal (mol (kcal (mol (kcal (mol dimer) -1 ) dimer) -1 ) monomer) -1 ) monomer) -1 ) monomer) -1 ) monomer) -1 ) 37 C b 37 C b c,d t avg 37 C e,f d, f d,g t avg t avg pwt c,h na 10.2 ± 0.7 na na 3.4 ± 0.5 na na pwt (30.8 ± 8.8) (10.3 ± 0.5) 59.5 ± ± (3.0, 1.9) 1.2 (1.3, 0.7) na pwt i 8.8 ± ± ± ± na V148I (11.4 ± 2.2) (8.9 ± 0.2) 60.1 ± ± (5.7, 4.2) 2.3 (2.4, 1.6) -1.2 V148I i 7.5 ± ± ± ± nd G93S (17.6 ± 4.6) (8.4 ± 0.3) 49.2 ± ± (2.0, 1.5) -0.4 (-0.3, -0.6) 1.5 H46R (16.2 ± 4.4) (8.4 ± 0.4) 62.5 ± ± (5.4, 4.7) 2.6 (2.6, 2.3) -1.4 H46R i 25.0 ± ± ± ± nd E100G (16.0 ± 4.8) (8.0 ± 0.4) 48.0 ± ± (1.6, 2.1) -0.5 (-0.4, -0.3) 1.7 G37R (7.8 ± 1.8) (7.6 ± 0.2) 50.3 ± ± (1.8, 3.0) -0.2 (-0.3, -0.3) 1.4 G37R i 42.7 ± ± ± ± nd H43R (23.0 ± 1.4) (7.5 ± 0.0) 47.6 ± ± (1.7, 1.9) -0.6 (-0.6, -0.6) 1.8 G93A (14.0 ± 2.0) (7.2 ± 0.3) 47.4 ± ± (1.7, 1.7) -0.7 (-0.6, -0.7) 1.9 G93A i 22.0 ± ± ± ± nd I113T (30.2 ± 2.5) (7.1 ± 0.2) 46.7 ± ± (1.5, 1.7) -0.7 (-0.6, -0.7) 1.9 I113T i 27.2 ± ± ± ± A4T (39.2 ± 3.8) (7.1 ± 0.2) 43.6 ± ± (0.9, 1.3) -1.1 (-1.0, -1.1) 2.3 A4T i 13.7 ± ± ± ± nd A4S (9.0 ± 2.6) (7.0 ± 0.0) 46.3 ± ± (1.1, 1.0) -0.9 (-1.2, -1.3) 2.1 A4S i 46.5 ± ± ± ± nd 16

17 G93R (45.6 ± 1.8) (6.7 ± 0.1) 49.1 ± ± (3.1, 2.9) -0.6 (-0.5, -0.5) 1.7 A4V (37.2 ± 3.8) (6.4 ± 0.3) 50.9 ± ± (2.2, 2.4) -0.1 (-0.1, -0.1) 1.2 A4V i 35.9 ± ± ± ± nd V148G (50.6 ± 1.4) (5.9 ± 0.3) 48.6 ± ± (2.3, 2.1) -0.5 (-0.5, -0.5) 1.7 V148G i 54.8 ± ± ± ± nd na, not applicable; nd, not determined. a For each mutant, the scans at different protein concentrations used in the global fitting are those listed in Table 1, with the exception of pwt, where concentrations 0.20, 0.21, 0.40, 0.44, 0.85, 1.50, and 3.0 were fit. b Numbers in the brackets were determined by ITC and fixed in the DSC three-state fits. c Errors are the uncertainty in fitted values. d t avg is 51.2 C, the average of all t 0.5 values obtained from the two-state fits (Table 1). e ΔG M U values calculated at physiological temperature. f Values are determined from fits allowing ΔH vh /ΔH cal to vary. Monomer stability was also determined using a higher ΔC p,n2 2M (2.2 kcal (mol dimer) -1 C -1 ), and these values are the first values shown in brackets. Data were also fit with ΔH vh and ΔH cal set equal, and these are the second values shown in brackets. Uncertainties in monomer stability were approximated from the range of values obtained from these 3 different fitting procedures (Table 2). g ΔΔG = ΔG pwt - ΔG mutant, a positive value indicates lower stability of the mutant relative to pwt; values are calculated at t avg, where monomer stability is best defined. h ΔG N2 2M and ΔG M U were also determined by globally fitting urea denaturation curves at 37 C to a three-state model with monomer intermediate. i ΔG M U values obtained by fitting additional parameters ΔH N2 2M and ΔG N2 2M (ie. not fixing these parameters to the values obtained by ITC) and setting ΔH vh and ΔH cal equal, for mutants with more than 3 datasets. This fitting method returns values with high uncertainty; therefore, the values from the fixed fits give more reliable comparison of relative stabilities. 17

18 Table S3. Thermodynamic parameters for monomer two-state unfolding of apo SOD1. SOD1 variant [SOD1] (mg ml -1 ) t 0.5 ( C) a C p,m U (kcal (mol monomer) -1 ) H vh (t 0.5 ) (kcal (mol monomer) -1 ) a A4V ± ± 10.6 A4V ± ± 7.9 A4V ± ± 5.1 A4V ± ± 2.5 A4V ± ± 4.4 A4V ± ± 2.6 H46R ± ± 18.8 H46R ± ± 6.6 H46R ± ± 2.2 H46R ± ± 4.7 H46R ± ± 2.5 V148G ± ± 4.3 V148G ± ± 0.6 V148G ± ± 0.3 V148G ± ± 0.2 V148G ± ± 0.1 V148G ± ± 0.8 a Uncertainty estimates in fitted parameters are from the fitting program. 18

19 Figure S1. Representative raw ITC data obtained at 37 C for SOD1 mutants. (A) G93R, (B) H43R and (C) I113T. Each peak represents the measured heat for a small volume injection of protein solution into the ITC sample cell. The heat associated with each injection (q i ) was determined by integrating the power versus time trace. Data were fit to a dimer dissociation model 10, 19, 20 according to q i = V H d ([M i ] [M i 1 ] (1 v V ) f m [M o ] v V ) + q dil, where ΔH d is the enthalpy change of dissociation from native dimer to two monomers, calculated per mol monomer. [M] o is the total concentration of apo SOD1 (monomer units) in the syringe, [M i ] and [M i-1 ] are the concentrations of apo SOD1 monomer in the ITC cell after injection i and i-1, respectively, v is the volume of each injection, V is the ITC reaction cell volume, q dil is a correction factor for the heat associated with sample dilution unrelated to dissociation, and f m is the fraction of protein in the syringe that exists as free monomer, which can be expressed as 19

20 f m = 1 4[M 0 ] ( K d + K d 2 + 8K d [M o ]). The data were fit using Microcal Origin 7.0 (Microcal Inc) with ΔH d, K d and q dil as floating parameters. 20

21 Figure S2. Plots of lnp dimer versus 1/T 0.5 used to determine molecularity, n, for apo SOD1 variants. The lnp dimer values are plotted versus 1/T 0.5 values from the dimer two-state fits for a representative set of apo variants (Table 1), and fit to a straight line using linear regression. Note that the midpoint of the thermal unfolding transition is a relatively well defined experimental value that is affected little by fitting to different unfolding models. The values of slope from these linear fits were used to determine n (summarized in Table 1) using eq 2, as described in the Material and Methods. Values of n are related to the inverse of the slope values. In this plot, the data for H46R and A4V have the steepest slopes, and hence the lowest average n values of ~1.3 and ~1.6, respectively, consistent with these mutants having higher populations of monomer (Figure 7). The lower slopes for the other SOD1 variants correspond to higher n values approaching ~2, consistent with predominantly dimer unfolding. When molecularities were calculated using H cal similar trends were observed but there was more scatter in the data, likely relating to the typically higher experimental error in H cal. 21 Taken together, the molecularity analyses are consistent with dimer unfolding with varying levels of monomer, in agreement with trends in t 0.5 values with protein concentration (Figure 3, Table 1). 21

22 Figure S3. Three-state thermal denaturation of apo SOD1. The parameters for each transition in the total heat of unfolding (black curve) can be used to simulate endotherms for two separate protein transitions, dimer dissociation (red curve) and monomer unfolding (blue curve). In the three-state global fitting approach used here, K 1 (same as K d,n2 2M) and h cal1 (same as h caln2 2M ) which characterize dimer dissociation, were set to the values determined by ITC at 37 C. The slopes of the monomer intermediate and unfolded monomer baselines were set equal to that of the native baseline, making the common assumption that ΔC p of unfolding is 4, 22 temperature independent. The intercepts of the intermediate and unfolded baselines were defined relative to the intercept of the native baseline (solid grey line) according to temperatureindependent values for ΔC p,n2 2M and ΔC p,m U (see Materials and Methods). Thus, the unfolded monomer and dimer baselines, grey dashed and dotted lines respectively, were defined based on C p,n2 2M 1.7 kcal (mol dimer) -1 C -1 and C p,m U 1.6 kcal (mol dimer) -1 C -1 ; The only floating parameters were t ref-2 and h cal2 (t ref 2 ) (same as h calm U (t ref 2 )), β1 = β2, and parameters defining the intercept (A) and slope (B) of the native baselines (solid grey line). Note, because of the way the baselines are defined, the blue and red traces do not add to make black as they do in Figure 7 with baselines subtracted. 22

23 SUPPORTING INFORMATION REFERENCES (1) Sturtevant, J. M. (1987) Biochemical Applications of Differential Scanning Calorimetry, Annu. Rev. Phys. Chem, (2) Shriver, J. W., and Edmondson, S. P. (2009) Defining the stability of multimeric proteins, Methods Mol Biol 490, (3) Becktel, W. J., and Schellman, J. A. (1987) Protein stability curves, Biopolymers 26, (4) Stathopulos, P. B., Rumfeldt, J. A., Karbassi, F., Siddall, C. A., Lepock, J. R., and Meiering, E. M. (2006) Calorimetric analysis of thermodynamic stability and aggregation for apo and holo amyotrophic lateral sclerosis-associated Gly-93 mutants of superoxide dismutase, J Biol Chem 281, (5) Makhatadze, G. I., and Privalov, P. L. (1995) Energetics of protein structure, Adv Protein Chem 47, (6) Tamura, A., Kojima, S., Miura, K., and Sturtevant, J. M. (1995) A thermodynamic study of mutant forms of Streptomyces subtilisin inhibitor. II. Replacements at the interface of dimer formation, Val13, J Mol Biol 249, (7) Prabhu, N. V., and Sharp, K. A. (2005) Heat capacity in proteins, Annu Rev Phys Chem 56, (8) Gomez, J., Hilser, V. J., Xie, D., and Freire, E. (1995) The heat capacity of proteins, Proteins 22, (9) Privalov, P. L., and Makhatadze, G. I. (1990) Heat capacity of proteins. II. Partial molar heat capacity of the unfolded polypeptide chain of proteins: protein unfolding effects, J Mol Biol 213,

24 (10) Broom, H. R., Rumfeldt, J. A., Vassall, K. A., and Meiering, E. M. (2015) Destabilization of the dimer interface is a common consequence of diverse ALS-associated mutations in metal free SOD1, Protein Sci. (11) Robic, S., Guzman-Casado, M., Sanchez-Ruiz, J. M., and Marqusee, S. (2003) Role of residual structure in the unfolded state of a thermophilic protein, Proc Natl Acad Sci U S A 100, (12) Gribenko, A. V., Keiffer, T. R., and Makhatadze, G. I. (2006) Amino acid substitutions affecting protein dynamics in eglin C do not affect heat capacity change upon unfolding, Proteins 64, (13) Spolar, R. S., Livingstone, J. R., and Record, M. T., Jr. (1992) Use of liquid hydrocarbon and amide transfer data to estimate contributions to thermodynamic functions of protein folding from the removal of nonpolar and polar surface from water, Biochemistry 31, (14) Murphy, K. P., and Freire, E. (1992) Thermodynamics of structural stability and cooperative folding behavior in proteins, Adv Protein Chem 43, (15) Myers, J. K., Pace, C. N., and Scholtz, J. M. (1995) Denaturant m values and heat capacity changes: relation to changes in accessible surface areas of protein unfolding, Protein Sci 4, (16) Negi, S. S., Kolokoltsov, A. A., Schein, C. H., Davey, R. A., and Braun, W. (2006) Determining functionally important amino acid residues of the E1 protein of Venezuelan equine encephalitis virus, J Mol Model 12, (17) Rumfeldt, J. A., Galvagnion, C., Vassall, K. A., and Meiering, E. M. (2008) Conformational stability and folding mechanisms of dimeric proteins, Prog Biophys Mol Biol 98,

25 (18) Loladze, V. V., Ermolenko, D. N., and Makhatadze, G. I. (2001) Heat capacity changes upon burial of polar and nonpolar groups in proteins, Protein Sci 10, (19) Burrows, S. D., Doyle, M. L., Murphy, K. P., Franklin, S. G., White, J. R., Brooks, I., McNulty, D. E., Scott, M. O., Knutson, J. R., Porter, D., and et al. (1994) Determination of the monomer-dimer equilibrium of interleukin-8 reveals it is a monomer at physiological concentrations, Biochemistry 33, (20) Velazquez-Campoy, A., Leavitt, S. A., and Freire, E. (2004) Characterization of proteinprotein interactions by isothermal titration calorimetry, Methods Mol Biol 261, (21) Tamura, A., and Sturtevant, J. M. (1995) A thermodynamic study of mutant forms of Streptomyces subtilisin inhibitor. I. Hydrophobic replacements at the position of Met103, J Mol Biol 249, (22) Privalov, P. L., and Potekhin, S. A. (1986) Scanning microcalorimetry in studying temperature-induced changes in proteins, Methods Enzymol 131,

1. Use the Data for RNAse to estimate:

1. Use the Data for RNAse to estimate: Chem 78 - - Spr 1 03/14/01 Assignment 4 - Answers Thermodynamic Analysis of RNAseA Denaturation by UV- Vis Difference Absorption Spectroscopy (and Differential Scanning Calorimetry). The accompanying excel

More information

Macromolecule Stability Curves

Macromolecule Stability Curves Chem728 page 1 Spring 2012 Macromolecule Stability Curves Macromolecule Transitions - We have discussed in class the factors that determine the spontaneity of processes using conformational transitions

More information

Substrate-dependent switching of the allosteric binding mechanism of a dimeric enzyme

Substrate-dependent switching of the allosteric binding mechanism of a dimeric enzyme Supplementary Information: Substrate-dependent switching of the allosteric binding mechanism of a dimeric enzyme Lee Freiburger, 1 Teresa Miletti, 1 Siqi Zhu, 1 Oliver Baettig, Albert Berghuis, Karine

More information

A Single Outer Sphere Mutation Stabilizes apo- Mn Superoxide Dismutase by 35 C and. Disfavors Mn Binding.

A Single Outer Sphere Mutation Stabilizes apo- Mn Superoxide Dismutase by 35 C and. Disfavors Mn Binding. Supporting information for A Single Outer Sphere Mutation Stabilizes apo- Mn Superoxide Dismutase by 35 C and Disfavors Mn Binding. Anne-Frances Miller* and Ting Wang Department of Chemistry, University

More information

Biological Thermodynamics

Biological Thermodynamics Biological Thermodynamics Classical thermodynamics is the only physical theory of universal content concerning which I am convinced that, within the framework of applicability of its basic contents, will

More information

Microcalorimetric techniques

Microcalorimetric techniques Microcalorimetric techniques Isothermal titration calorimetry (ITC) Differential scanning calorimetry (DSC) Filip Šupljika Filip.Supljika@irb.hr Laboratory for the study of interactions of biomacromolecules

More information

Lecture 34 Protein Unfolding Thermodynamics

Lecture 34 Protein Unfolding Thermodynamics Physical Principles in Biology Biology 3550 Fall 2018 Lecture 34 Protein Unfolding Thermodynamics Wednesday, 21 November c David P. Goldenberg University of Utah goldenberg@biology.utah.edu Clicker Question

More information

Determination of the thermodynamics of carbonic anhydrase acid-unfolding by titration calorimetry

Determination of the thermodynamics of carbonic anhydrase acid-unfolding by titration calorimetry Available online at www.sciencedirect.com J. Biochem. Biophys. Methods 70 (2008) 1043 1047 www.elsevier.com/locate/jbbm Determination of the thermodynamics of carbonic anhydrase acid-unfolding by titration

More information

Microcalorimetry for the Life Sciences

Microcalorimetry for the Life Sciences Microcalorimetry for the Life Sciences Why Microcalorimetry? Microcalorimetry is universal detector Heat is generated or absorbed in every chemical process In-solution No molecular weight limitations Label-free

More information

Supplementary Figures

Supplementary Figures 1 Supplementary Figures Supplementary Figure 1 Type I FGFR1 inhibitors (a) Chemical structures of a pyrazolylaminopyrimidine inhibitor (henceforth referred to as PAPI; PDB-code of the FGFR1-PAPI complex:

More information

= (-22) = +2kJ /mol

= (-22) = +2kJ /mol Lecture 8: Thermodynamics & Protein Stability Assigned reading in Campbell: Chapter 4.4-4.6 Key Terms: DG = -RT lnk eq = DH - TDS Transition Curve, Melting Curve, Tm DH calculation DS calculation van der

More information

Lecture 2 and 3: Review of forces (ctd.) and elementary statistical mechanics. Contributions to protein stability

Lecture 2 and 3: Review of forces (ctd.) and elementary statistical mechanics. Contributions to protein stability Lecture 2 and 3: Review of forces (ctd.) and elementary statistical mechanics. Contributions to protein stability Part I. Review of forces Covalent bonds Non-covalent Interactions: Van der Waals Interactions

More information

Thermal protein unfolding by differential scanning calorimetry and circular dichroism spectroscopy Two-state model versus sequential unfolding

Thermal protein unfolding by differential scanning calorimetry and circular dichroism spectroscopy Two-state model versus sequential unfolding REVIEW Thermal protein unfolding by differential scanning calorimetry and circular dichroism spectroscopy Two-state model versus sequential unfolding Joachim Seelig 1 * and Hans-Joachim Schönfeld 2 1 Division

More information

Biology Chemistry & Physics of Biomolecules. Examination #1. Proteins Module. September 29, Answer Key

Biology Chemistry & Physics of Biomolecules. Examination #1. Proteins Module. September 29, Answer Key Biology 5357 Chemistry & Physics of Biomolecules Examination #1 Proteins Module September 29, 2017 Answer Key Question 1 (A) (5 points) Structure (b) is more common, as it contains the shorter connection

More information

DSC Characterization of the Structure/Function Relationship for Proteins

DSC Characterization of the Structure/Function Relationship for Proteins DSC Characterization of the Structure/Function Relationship for Proteins Differential Scanning Calorimetry (DSC) DSC is recognized as Gold Std technique for measuring molecular thermal stability and structure

More information

arxiv:cond-mat/ v1 7 Jul 2000

arxiv:cond-mat/ v1 7 Jul 2000 A protein model exhibiting three folding transitions Audun Bakk Department of Physics, Norwegian University of Science and Technology, NTNU, N-7491 Trondheim, Norway arxiv:cond-mat/0007130v1 7 Jul 2000

More information

Awanish Kumar, Anjeeta Rani and Pannuru Venkatesu* Department of Chemistry, University of Delhi, Delhi

Awanish Kumar, Anjeeta Rani and Pannuru Venkatesu* Department of Chemistry, University of Delhi, Delhi Electronic Supplementary Material (ESI) for New Journal of Chemistry. This journal is The Royal Society of Chemistry and the Centre National de la Recherche Scientifique 2014 Supplimentary Informations

More information

Supporting Information for:

Supporting Information for: Supporting Information for: A Simple Molecular Model for Thermophilic Adaptation of Functional Nucleic Acids Joshua M. Blose *, Scott K. Silverman, and Philip C. Bevilacqua * * Department of Chemistry,

More information

Interaction between water and polar groups of the helix backbone: An important determinant of helix propensities

Interaction between water and polar groups of the helix backbone: An important determinant of helix propensities Proc. Natl. Acad. Sci. USA Vol. 96, pp. 4930 4935, April 1999 Biophysics Interaction between water and polar groups of the helix backbone: An important determinant of helix propensities PEIZHI LUO* AND

More information

arxiv:cond-mat/ v1 [cond-mat.soft] 19 Mar 2001

arxiv:cond-mat/ v1 [cond-mat.soft] 19 Mar 2001 Modeling two-state cooperativity in protein folding Ke Fan, Jun Wang, and Wei Wang arxiv:cond-mat/0103385v1 [cond-mat.soft] 19 Mar 2001 National Laboratory of Solid State Microstructure and Department

More information

Characterizing Binding Interactions by ITC

Characterizing Binding Interactions by ITC Characterizing Binding Interactions by ITC Christin T. Choma TA Instruments, 19 Lukens Drive, New Castle, DE 1972, USA All biochemical reactions involve recognition, binding and the formation of noncovalent

More information

ISoTherMal TITraTIon Calorimetry

ISoTherMal TITraTIon Calorimetry ISoTherMal TITraTIon Calorimetry With the Nano ITC, heat effects as small as 1 nanojoules are detectable using one nanomole or less of biopolymer. The Nano ITC uses a solid-state thermoelectric heating

More information

Presentation Microcalorimetry for Life Science Research

Presentation Microcalorimetry for Life Science Research Presentation Microcalorimetry for Life Science Research MicroCalorimetry The Universal Detector Heat is either generated or absorbed in every chemical process Capable of thermal measurements over a wide

More information

The underlying prerequisite to the application of thermodynamic principles to natural systems is that the system under consideration should be at equilibrium. http://eps.mcgill.ca/~courses/c220/ Reversible

More information

S2004 Methods for characterization of biomolecular interactions - classical versus modern

S2004 Methods for characterization of biomolecular interactions - classical versus modern S2004 Methods for characterization of biomolecular interactions - classical versus modern Isothermal Titration Calorimetry (ITC) Eva Dubská email: eva.dubska@ceitec.cz Outline Calorimetry - history + a

More information

Guessing the upper bound free-energy difference between native-like structures. Jorge A. Vila

Guessing the upper bound free-energy difference between native-like structures. Jorge A. Vila 1 Guessing the upper bound free-energy difference between native-like structures Jorge A. Vila IMASL-CONICET, Universidad Nacional de San Luis, Ejército de Los Andes 950, 5700- San Luis, Argentina Use

More information

Heat Capacity Changes Associated with DNA Duplex Formation: Salt- and Sequence-Dependent Effects

Heat Capacity Changes Associated with DNA Duplex Formation: Salt- and Sequence-Dependent Effects 604 Biochemistry 2006, 45, 604-616 Heat Capacity Changes Associated with DNA Duplex Formation: Salt- and Sequence-Dependent Effects Peter J. Mikulecky and Andrew L. Feig* Department of Chemistry, Indiana

More information

Supplementary Information. Overlap between folding and functional energy landscapes for. adenylate kinase conformational change

Supplementary Information. Overlap between folding and functional energy landscapes for. adenylate kinase conformational change Supplementary Information Overlap between folding and functional energy landscapes for adenylate kinase conformational change by Ulrika Olsson & Magnus Wolf-Watz Contents: 1. Supplementary Note 2. Supplementary

More information

FOCUS: HYDROGEN EXCHANGE AND COVALENT MODIFICATION

FOCUS: HYDROGEN EXCHANGE AND COVALENT MODIFICATION FOCUS: HYDROGEN EXCHANGE AND COVALENT MODIFICATION Accuracy of SUPREX (Stability of Unpurified Proteins from Rates of H/D Exchange) and MALDI Mass Spectrometry-Derived Protein Unfolding Free Energies Determined

More information

Molecular Origin of Hydration Heat Capacity Changes of Hydrophobic Solutes: Perturbation of Water Structure around Alkanes

Molecular Origin of Hydration Heat Capacity Changes of Hydrophobic Solutes: Perturbation of Water Structure around Alkanes J. Phys. Chem. B 1997, 101, 11237-11242 11237 Molecular Origin of Hydration Heat Capacity Changes of Hydrophobic Solutes: Perturbation of Water Structure around Alkanes Bhupinder Madan and Kim Sharp* The

More information

THE TANGO ALGORITHM: SECONDARY STRUCTURE PROPENSITIES, STATISTICAL MECHANICS APPROXIMATION

THE TANGO ALGORITHM: SECONDARY STRUCTURE PROPENSITIES, STATISTICAL MECHANICS APPROXIMATION THE TANGO ALGORITHM: SECONDARY STRUCTURE PROPENSITIES, STATISTICAL MECHANICS APPROXIMATION AND CALIBRATION Calculation of turn and beta intrinsic propensities. A statistical analysis of a protein structure

More information

Supplementary Information

Supplementary Information Supplementary Information Adenosyltransferase Tailors and Delivers Coenzyme B 12 Dominique Padovani 1,2, Tetyana Labunska 2, Bruce A. Palfey 1, David P. Ballou 1 and Ruma Banerjee 1,2 * 1 Biological Chemistry

More information

Thermodynamics. Entropy and its Applications. Lecture 11. NC State University

Thermodynamics. Entropy and its Applications. Lecture 11. NC State University Thermodynamics Entropy and its Applications Lecture 11 NC State University System and surroundings Up to this point we have considered the system, but we have not concerned ourselves with the relationship

More information

Exploring protein-folding ensembles: A variable-barrier model for the analysis of equilibrium unfolding experiments

Exploring protein-folding ensembles: A variable-barrier model for the analysis of equilibrium unfolding experiments Exploring protein-folding ensembles: A variable-barrier model for the analysis of equilibrium unfolding experiments Victor Muñoz* and Jose M. Sanchez-Ruiz *Department of Chemistry and Biochemistry and

More information

Free energy, electrostatics, and the hydrophobic effect

Free energy, electrostatics, and the hydrophobic effect Protein Physics 2016 Lecture 3, January 26 Free energy, electrostatics, and the hydrophobic effect Magnus Andersson magnus.andersson@scilifelab.se Theoretical & Computational Biophysics Recap Protein structure

More information

Review. Introduction. Ilian Jelesarov* and Hans Rudolf Bosshard

Review. Introduction. Ilian Jelesarov* and Hans Rudolf Bosshard JOURNAL OF MOLECULAR RECOGNITION J. Mol. Recognit. 1999;12:3 18 Review Isothermal titration calorimetry and differential scanning calorimetry as complementary tools to investigate the energetics of biomolecular

More information

Supporting Text Z = 2Γ 2+ + Γ + Γ [1]

Supporting Text Z = 2Γ 2+ + Γ + Γ [1] Supporting Text RNA folding experiments are typically carried out in a solution containing a mixture of monovalent and divalent ions, usually MgCl 2 and NaCl or KCl. All three species of ions, Mg, M +

More information

Effect of the Single and Double Chain Surfactant Cobalt(III) Complexes on Their Hydrophobicity, Micelle Formation,

Effect of the Single and Double Chain Surfactant Cobalt(III) Complexes on Their Hydrophobicity, Micelle Formation, Electronic Supplementary Material (ESI) for Inorganic Chemistry Frontiers. This journal is the Partner Organisations 2014 Supplementary Information Effect of the Single and Double Chain Surfactant Cobalt(III)

More information

BAE 820 Physical Principles of Environmental Systems

BAE 820 Physical Principles of Environmental Systems BAE 820 Physical Principles of Environmental Systems Acquisition of reaction rate data Dr. Zifei Liu Uncertainties in real world reaction rate data Most interesting reaction systems involves multiple reactions,

More information

General Chemistry revisited

General Chemistry revisited General Chemistry revisited A(g) + B(g) C(g) + D(g) We said that G = H TS where, eg, H = f H(C) + f H(D) - f H(A) - f H(B) G < 0 implied spontaneous to right G > 0 implied spontaneous to left In a very

More information

Protein folding. Today s Outline

Protein folding. Today s Outline Protein folding Today s Outline Review of previous sessions Thermodynamics of folding and unfolding Determinants of folding Techniques for measuring folding The folding process The folding problem: Prediction

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION doi:10.1038/nature10458 Active Site Remodeling in the Bifunctional Fructose-1,6- bisphosphate aldolase/phosphatase Juan Du, Rafael F. Say, Wei Lü, Georg Fuchs & Oliver Einsle SUPPLEMENTARY FIGURES Figure

More information

3. Solutions W = N!/(N A!N B!) (3.1) Using Stirling s approximation ln(n!) = NlnN N: ΔS mix = k (N A lnn + N B lnn N A lnn A N B lnn B ) (3.

3. Solutions W = N!/(N A!N B!) (3.1) Using Stirling s approximation ln(n!) = NlnN N: ΔS mix = k (N A lnn + N B lnn N A lnn A N B lnn B ) (3. 3. Solutions Many biological processes occur between molecules in aqueous solution. In addition, many protein and nucleic acid molecules adopt three-dimensional structure ( fold ) in aqueous solution.

More information

LABORATORY OF ELEMENTARY BIOPHYSICS. Isothermal Titration Calorimetry as a tool for determining thermodynamic parameters of chemical reactions

LABORATORY OF ELEMENTARY BIOPHYSICS. Isothermal Titration Calorimetry as a tool for determining thermodynamic parameters of chemical reactions LABORATORY OF ELEMENTARY BIOPHYSICS Experimental exercises for III year of the First cycle studies Field: Applications of physics in biology and medicine Specialization: Molecular Biophysics Isothermal

More information

Molecular dynamics simulations of anti-aggregation effect of ibuprofen. Wenling E. Chang, Takako Takeda, E. Prabhu Raman, and Dmitri Klimov

Molecular dynamics simulations of anti-aggregation effect of ibuprofen. Wenling E. Chang, Takako Takeda, E. Prabhu Raman, and Dmitri Klimov Biophysical Journal, Volume 98 Supporting Material Molecular dynamics simulations of anti-aggregation effect of ibuprofen Wenling E. Chang, Takako Takeda, E. Prabhu Raman, and Dmitri Klimov Supplemental

More information

The structure of the -helix in polypeptides was proposed

The structure of the -helix in polypeptides was proposed Enthalpy of helix coil transition: Missing link in rationalizing the thermodynamics of helix-forming propensities of the amino acid residues John M. Richardson, Maria M. Lopez, and George I. Makhatadze*

More information

Cholera Toxin Invasion

Cholera Toxin Invasion Protein-carbohydrate interactions: Isothermal Titration Calorimetry Dr Bruce Turnbull School of Chemistry and Astbury Centre for Structural Molecular Biology University of Leeds Cholera Toxin Invasion

More information

Chemical Equilibria. Chapter Extent of Reaction

Chemical Equilibria. Chapter Extent of Reaction Chapter 6 Chemical Equilibria At this point, we have all the thermodynamics needed to study systems in ulibrium. The first type of uilibria we will examine are those involving chemical reactions. We will

More information

Nature Structural and Molecular Biology: doi: /nsmb Supplementary Figure 1. Definition and assessment of ciap1 constructs.

Nature Structural and Molecular Biology: doi: /nsmb Supplementary Figure 1. Definition and assessment of ciap1 constructs. Supplementary Figure 1 Definition and assessment of ciap1 constructs. (a) ciap1 constructs used in this study are shown as primary structure schematics with domains colored as in the main text. Mutations

More information

Biophysics Jan 2013 Calorimetric Methods and Solution size determination. 22 Jan 2014

Biophysics Jan 2013 Calorimetric Methods and Solution size determination. 22 Jan 2014 Biophysics 204 22 Jan 2014 23 Jan 2013 Calorimetric Methods and Solution size determination Part I - Calorimetry ITC Part II - How to determine macromolecular size 1 Thermodynamics Define the Gibbs free

More information

Exp.3 Determination of the Thermodynamic functions for the Borax Solution

Exp.3 Determination of the Thermodynamic functions for the Borax Solution Exp.3 Determination of the Thermodynamic functions for the Borax Solution Theory: The relationship between Gibb s energy (ΔG), Enthalpy (ΔH), Entropy (ΔS) and the equilibrium constant (K) for a chemical

More information

Chemistry 431. Lecture 27 The Ensemble Partition Function Statistical Thermodynamics. NC State University

Chemistry 431. Lecture 27 The Ensemble Partition Function Statistical Thermodynamics. NC State University Chemistry 431 Lecture 27 The Ensemble Partition Function Statistical Thermodynamics NC State University Representation of an Ensemble N,V,T N,V,T N,V,T N,V,T N,V,T N,V,T N,V,T N,V,T N,V,T N,V,T N,V,T N,V,T

More information

specified quantity of a solvent at a given temperature. To deconvolute the value from the

specified quantity of a solvent at a given temperature. To deconvolute the value from the S.1 Calculations of Dilution Enthalpy and Enthalpic Interaction Coefficients. When a solute is dissolved in a solvent a solution is formed. During dissolution of a solute in any solvent, heat is either

More information

Lecture 20. Chemical Potential

Lecture 20. Chemical Potential Lecture 20 Chemical Potential Reading: Lecture 20, today: Chapter 10, sections A and B Lecture 21, Wednesday: Chapter 10: 10 17 end 3/21/16 1 Pop Question 7 Boltzmann Distribution Two systems with lowest

More information

schematic diagram; EGF binding, dimerization, phosphorylation, Grb2 binding, etc.

schematic diagram; EGF binding, dimerization, phosphorylation, Grb2 binding, etc. Lecture 1: Noncovalent Biomolecular Interactions Bioengineering and Modeling of biological processes -e.g. tissue engineering, cancer, autoimmune disease Example: RTK signaling, e.g. EGFR Growth responses

More information

Effect of Guanidine Hydrochloride on the Thermal Stability of Hen Egg White Lysozyme

Effect of Guanidine Hydrochloride on the Thermal Stability of Hen Egg White Lysozyme Effect of Guanidine Hydrochloride on the Thermal Stability of Hen Egg White Lysozyme Thesis Submitted In partial fulfillment of the requirement for the degree of MASTER OF SCIENCE IN CHEMISTRY Submitted

More information

ANSWER KEY. Chemistry 25 (Spring term 2015) Midterm Examination

ANSWER KEY. Chemistry 25 (Spring term 2015) Midterm Examination Name ANSWER KEY Chemistry 25 (Spring term 2015) Midterm Examination 1 (15 pts) Short answers 1A (3 pts) Consider the following system at two time points A and B. The system is divided by a moveable partition.

More information

ANSWER KEY. Chemistry 25 (Spring term 2017) Midterm Examination

ANSWER KEY. Chemistry 25 (Spring term 2017) Midterm Examination Name ANSWER KEY Chemistry 25 (Spring term 2017) Midterm Examination Distributed Thursday, May 4, 2017 Due Thursday, May 11, 2017 by 1 pm in class or by 12:45 pm in 362 Broad a drop box will be left outside

More information

Isothermal titration calorimetry (ITC)

Isothermal titration calorimetry (ITC) Isothermal titration calorimetry (ITC) Peter.gimeson@malvern.com Why microcalorimetry? Label-free Broad dynamic range Information rich Ease-of-use Direct measurement of heat change (ITC) Direct measurement

More information

Supplementary information

Supplementary information Supplementary information Superoxide dismutase 1 is positively selected in great apes to minimize protein misfolding Pouria Dasmeh 1, and Kasper P. Kepp* 2 1 Harvard University, Department of Chemistry

More information

Characterizing non-covalent nucleic acid interactions with small molecules and proteins by calorimetry

Characterizing non-covalent nucleic acid interactions with small molecules and proteins by calorimetry Characterizing non-covalent nucleic acid interactions with small molecules and proteins by calorimetry Christin T. Choma TA Instruments, 109 Lukens Drive, New Castle, DE 19720, USA The expression or replication

More information

Outline. The ensemble folding kinetics of protein G from an all-atom Monte Carlo simulation. Unfolded Folded. What is protein folding?

Outline. The ensemble folding kinetics of protein G from an all-atom Monte Carlo simulation. Unfolded Folded. What is protein folding? The ensemble folding kinetics of protein G from an all-atom Monte Carlo simulation By Jun Shimada and Eugine Shaknovich Bill Hawse Dr. Bahar Elisa Sandvik and Mehrdad Safavian Outline Background on protein

More information

Heat capacity analysis of oxidized Escherichia coli thioredoxin fragments (1±73, 74±108) and their noncovalent complex

Heat capacity analysis of oxidized Escherichia coli thioredoxin fragments (1±73, 74±108) and their noncovalent complex Eur. J. Biochem. 268, 1477±1485 (2001) q FEBS 2001 Heat capacity analysis of oxidized Escherichia coli thioredoxin fragments (1±73, 74±108) and their noncovalent complex Evidence for the burial of apolar

More information

Lattice protein models

Lattice protein models Lattice protein models Marc R. Roussel epartment of Chemistry and Biochemistry University of Lethbridge March 5, 2009 1 Model and assumptions The ideas developed in the last few lectures can be applied

More information

Cold denaturation of staphylococcal nuclease (protein stability/calorimetry)

Cold denaturation of staphylococcal nuclease (protein stability/calorimetry) Proc. Nati. Acad. Sci. USA Vol. 85, pp. 3343-3347, May 1988 Biochemistry Cold denaturation of staphylococcal nuclease (protein stability/calorimetry) YURI V. GRIKO*, PTR L. PRIVALOV*, JULIAN M. STURTVANTt,

More information

Full file at https://fratstock.eu

Full file at https://fratstock.eu Chapter 03 1. a. DG=DH-TDS Δ G = 80 kj ( 98 K) 0.790 kj = 44.6 kj K b. ΔG = 0 @ T m. Unfolding will be favorable at temperatures above the T m. Δ G =Δ H TΔ S 0 kj kj 80 ( xk) 0.790 K 0 Δ G = = 354.4 K

More information

Solutions to Problem Set 9

Solutions to Problem Set 9 Solutions to Problem Set 9 1. When possible, we want to write an equation with the quantity on the ordinate in terms of the quantity on the abscissa for each pf the labeled curves. A B C p CHCl3 = K H

More information

BCHS 6229 Protein Structure and Function. Lecture 3 (October 18, 2011) Protein Folding: Forces, Mechanisms & Characterization

BCHS 6229 Protein Structure and Function. Lecture 3 (October 18, 2011) Protein Folding: Forces, Mechanisms & Characterization BCHS 6229 Protein Structure and Function Lecture 3 (October 18, 2011) Protein Folding: Forces, Mechanisms & Characterization 1 The folding problem One of the greatest unsolved problems of Science The folding

More information

Keywords: dimer dissociation, Streptomyces subtilisin inhibitor, rate constant

Keywords: dimer dissociation, Streptomyces subtilisin inhibitor, rate constant J. Biol. Macromol. 8(2), 38-47 (2008) Article Kinetic study on the dissociation of a dimeric protein, Streptomyces Subtilisin Inhibitor Keiko Momma 1,2, Ben ichiro Tonomura, and Keitaro Hiromi Department

More information

Short Announcements. 1 st Quiz today: 15 minutes. Homework 3: Due next Wednesday.

Short Announcements. 1 st Quiz today: 15 minutes. Homework 3: Due next Wednesday. Short Announcements 1 st Quiz today: 15 minutes Homework 3: Due next Wednesday. Next Lecture, on Visualizing Molecular Dynamics (VMD) by Klaus Schulten Today s Lecture: Protein Folding, Misfolding, Aggregation

More information

Statistical Thermodynamics. Lecture 8: Theory of Chemical Equilibria(I)

Statistical Thermodynamics. Lecture 8: Theory of Chemical Equilibria(I) Statistical Thermodynamics Lecture 8: Theory of Chemical Equilibria(I) Chemical Equilibria A major goal in chemistry is to predict the equilibria of chemical reactions, including the relative amounts of

More information

Second Law Applications. NC State University

Second Law Applications. NC State University Chemistry 433 Lecture 11 Second Law Applications NC State University Summary of entropy calculations In the last lecture we derived formula for the calculation of the entropy change as a function of temperature

More information

A rule of seven in Watson-Crick base-pairing of mismatched sequences

A rule of seven in Watson-Crick base-pairing of mismatched sequences A rule of seven in Watson-Crick base-pairing of mismatched sequences Ibrahim I. Cisse 1,3, Hajin Kim 1,2, Taekjip Ha 1,2 1 Department of Physics and Center for the Physics of Living Cells, University of

More information

Calorimetry: differential scanning calorimetry (DSC), isothermal titration calorimetry (ITC)

Calorimetry: differential scanning calorimetry (DSC), isothermal titration calorimetry (ITC) Calorimetry: differential scanning calorimetry (DSC), isothermal titration calorimetry (ITC) Dr. Yin Li Department of Biophysics, Medical School University of Pecs Thermal Analysis IUPAC definition - a

More information

Structural energetics of serine protease inhibition*

Structural energetics of serine protease inhibition* Pure Appl. Chem., Vol. 71, No. 7, pp. 1207 1213, 1999. Printed in Great Britain. 1999 IUPAC Structural energetics of serine protease inhibition* Kenneth P. Murphy, Brian M. Baker, Stephen P. Edgcomb and

More information

Problem solving steps

Problem solving steps Problem solving steps Determine the reaction Write the (balanced) equation ΔG K v Write the equilibrium constant v Find the equilibrium constant using v If necessary, solve for components K K = [ p ] ν

More information

MCB100A/Chem130 MidTerm Exam 2 April 4, 2013

MCB100A/Chem130 MidTerm Exam 2 April 4, 2013 MCB1A/Chem13 MidTerm Exam 2 April 4, 213 Name Student ID True/False (2 points each). 1. The Boltzmann constant, k b T sets the energy scale for observing energy microstates 2. Atoms with favorable electronic

More information

Structural basis for catalytically restrictive dynamics of a high-energy enzyme state

Structural basis for catalytically restrictive dynamics of a high-energy enzyme state Supplementary Material Structural basis for catalytically restrictive dynamics of a high-energy enzyme state Michael Kovermann, Jörgen Ådén, Christin Grundström, A. Elisabeth Sauer-Eriksson, Uwe H. Sauer

More information

Thermodynamic Stability of Carbonic Anhydrase: Measurements of Binding Affinity and Stoichiometry Using ThermoFluor

Thermodynamic Stability of Carbonic Anhydrase: Measurements of Binding Affinity and Stoichiometry Using ThermoFluor 5258 Biochemistry 2005, 44, 5258-5266 Thermodynamic Stability of Carbonic Anhydrase: Measurements of Binding Affinity and Stoichiometry Using ThermoFluor Daumantas Matulis, James K. Kranz, F. Raymond Salemme,

More information

Chapter 19 Chemical Thermodynamics

Chapter 19 Chemical Thermodynamics Chapter 19 Chemical Thermodynamics Spontaneous Processes Entropy and the Second Law of Thermodynamics The Molecular Interpretation of Entropy Entropy Changes in Chemical Reactions Gibbs Free Energy Free

More information

protein complexes. Early studies by Kauzmann (8) and

protein complexes. Early studies by Kauzmann (8) and Proc. Natl. Acad. Sci. USA Vol. 89, pp. 4781-4785, June 1992 Biophysics Heat capacity changes and hydrophobic interactions in the binding of FK506 and rapamycin to the FK506 binding protein (ilmmunosuppression/calorimetry/accessible

More information

Many proteins spontaneously refold into native form in vitro with high fidelity and high speed.

Many proteins spontaneously refold into native form in vitro with high fidelity and high speed. Macromolecular Processes 20. Protein Folding Composed of 50 500 amino acids linked in 1D sequence by the polypeptide backbone The amino acid physical and chemical properties of the 20 amino acids dictate

More information

Chapter 19 Chemical Thermodynamics Entropy and free energy

Chapter 19 Chemical Thermodynamics Entropy and free energy Chapter 19 Chemical Thermodynamics Entropy and free energy Learning goals and key skills: Explain and apply the terms spontaneous process, reversible process, irreversible process, and isothermal process.

More information

Systematic errors in isothermal titration calorimetry: Concentrations and baselines

Systematic errors in isothermal titration calorimetry: Concentrations and baselines See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/50890941 Systematic errors in isothermal titration calorimetry: Concentrations and baselines

More information

MCB100A/Chem130 MidTerm Exam 2 April 4, 2013

MCB100A/Chem130 MidTerm Exam 2 April 4, 2013 MCBA/Chem Miderm Exam 2 April 4, 2 Name Student ID rue/false (2 points each).. he Boltzmann constant, k b sets the energy scale for observing energy microstates 2. Atoms with favorable electronic configurations

More information

Thermochemistry Lecture

Thermochemistry Lecture Thermochemistry Lecture Jennifer Fang 1. Enthalpy 2. Entropy 3. Gibbs Free Energy 4. q 5. Hess Law 6. Laws of Thermodynamics ENTHALPY total energy in all its forms; made up of the kinetic energy of the

More information

Lecture 6 Free energy and its uses

Lecture 6 Free energy and its uses Lecture 6 Free energy and its uses dg = VdP G - G o = PoP VdP G = G o (T) + RT ln P/P o for gases and G = G o (T) + V (P-P o ) for solids and liquids µ = µ o + RT ln P (for one mole) G = G o + RT ln Q

More information

Phase Diagrams: Conditions for Equilibrium (CfE)

Phase Diagrams: Conditions for Equilibrium (CfE) Phase Equilibrium: Conditions for Equilibrium (CfE) Phase Diagrams: Conditions for Equilibrium (CfE) Write down the conditions for equilibrium for: a pure single phase system, a pure multi-phase system,

More information

Characterizing Protein-Protein Interactions by ITC

Characterizing Protein-Protein Interactions by ITC Characterizing Protein-Protein Interactions by ITC Keywords: ITC, binding, proteins MCAPN-0132 0 interactions also occur intramolecularly at interfaces between domains and between subunits within a protein.

More information

Protein Folding & Stability. Lecture 11: Margaret A. Daugherty. Fall How do we go from an unfolded polypeptide chain to a

Protein Folding & Stability. Lecture 11: Margaret A. Daugherty. Fall How do we go from an unfolded polypeptide chain to a Lecture 11: Protein Folding & Stability Margaret A. Daugherty Fall 2004 How do we go from an unfolded polypeptide chain to a compact folded protein? (Folding of thioredoxin, F. Richards) Structure - Function

More information

OCN 623: Thermodynamic Laws & Gibbs Free Energy. or how to predict chemical reactions without doing experiments

OCN 623: Thermodynamic Laws & Gibbs Free Energy. or how to predict chemical reactions without doing experiments OCN 623: Thermodynamic Laws & Gibbs Free Energy or how to predict chemical reactions without doing experiments Definitions Extensive properties Depend on the amount of material e.g. # of moles, mass or

More information

Protein Folding Prof. Eugene Shakhnovich

Protein Folding Prof. Eugene Shakhnovich Protein Folding Eugene Shakhnovich Department of Chemistry and Chemical Biology Harvard University 1 Proteins are folded on various scales As of now we know hundreds of thousands of sequences (Swissprot)

More information

Protein Folding In Vitro*

Protein Folding In Vitro* Protein Folding In Vitro* Biochemistry 412 February 29, 2008 [*Note: includes computational (in silico) studies] Fersht & Daggett (2002) Cell 108, 573. Some folding-related facts about proteins: Many small,

More information

Temperature dependence of reactions with multiple pathways

Temperature dependence of reactions with multiple pathways PCCP Temperature dependence of reactions with multiple pathways Muhammad H. Zaman, ac Tobin R. Sosnick bc and R. Stephen Berry* ad a Department of Chemistry, The University of Chicago, Chicago, IL 60637,

More information

Section Week 3. Junaid Malek, M.D.

Section Week 3. Junaid Malek, M.D. Section Week 3 Junaid Malek, M.D. Biological Polymers DA 4 monomers (building blocks), limited structure (double-helix) RA 4 monomers, greater flexibility, multiple structures Proteins 20 Amino Acids,

More information

Relationship between the Native-State Hydrogen Exchange and Folding Pathways of a Four-Helix Bundle Protein

Relationship between the Native-State Hydrogen Exchange and Folding Pathways of a Four-Helix Bundle Protein 7998 Biochemistry 2002, 41, 7998-8003 Relationship between the Native-State Hydrogen Exchange and Folding Pathways of a Four-Helix Bundle Protein Ruiai Chu, Wuhong Pei, Jiro Takei, and Yawen Bai* Laboratory

More information

Thermodynamics & kinetics

Thermodynamics & kinetics Zepelin Hindenburg 1937 Thermodynamics & kinetics H 2 + ½ O 2 H 2 O H = - 241 KJ/mol both spontaneous! R P but rates? R P 2Fe + O 2 + 2H 2 O 2 Fe (OH) 2 H = - 272 KJ/mol Reaction coordinate Thermodynamics

More information

Protein structure forces, and folding

Protein structure forces, and folding Harvard-MIT Division of Health Sciences and Technology HST.508: Quantitative Genomics, Fall 2005 Instructors: Leonid Mirny, Robert Berwick, Alvin Kho, Isaac Kohane Protein structure forces, and folding

More information

BIOPHYSICAL CHARACTERIZATION OF PROTEIN FOLDING AND MISFOLDING

BIOPHYSICAL CHARACTERIZATION OF PROTEIN FOLDING AND MISFOLDING BIOPHYSICAL CHARACTERIZATION OF PROTEIN FOLDING AND MISFOLDING A Dissertation by JASON PETER SCHMITTSCHMITT Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of

More information

The Thermal Dependence and Urea Concentration Dependence of Rnase A Denaturant Transition

The Thermal Dependence and Urea Concentration Dependence of Rnase A Denaturant Transition The Theral Dependence and Urea Concentration Dependence of Rnase A Denaturant Transition Bin LI Departent of Physics & Astronoy, University of Pittsburgh, Pittsburgh, PA 15260, U.S.A Feb.20 th, 2001 Abstract:

More information