Size-dependent macromolecular crowding effect on the thermodynamics of protein unfolding revealed at the single molecular level

International Journal of Biological Macromolecules 141 (2019) 843–854

Contents lists available at ScienceDirect

International Journal of Biological Macromolecules journal homepage: http://www.elsevier.com/locate/ijbiomac

Size-dependent macromolecular crowding effect on the thermodynamics of protein unfolding revealed at the single molecular level Nilimesh Das, Pratik Sen ⁎ Department of Chemistry, Indian Institute of Technology Kanpur, Kanpur 208 016, UP, India

a r t i c l e

i n f o

Article history: Received 9 July 2019 Received in revised form 30 August 2019 Accepted 4 September 2019 Available online 06 September 2019 Keywords: Macromolecular crowding Size effect Protein unfolding Conformational fluctuation dynamics Thermal stability

a b s t r a c t The real biological environment involves a high degree of complexity and the macromolecular crowder is the best candidate to somewhat mimic this. In this contribution, we have used two different sized dextrans as model crowders and human serum albumin (HSA) as a model protein to decipher how the thermal stability of protein is modulated inside the crowded milieu and also to understand the effect of the size of the crowders. In our previous report (Biochemistry 2018, 57, 6078–6089) we have proposed the presence of some interaction between dextran-6 and HSA, which are probably not present between the larger dextrans and HSA. Complete thermodynamic analysis of thermal denaturation profile of HSA suggests that small crowders increase protein stability mainly via the enthalpy of denaturation while larger crowders increase stability primarily through entropy. Further, the active site dynamics is altered significantly in the presence of larger dextran-40, but not by smaller dextran-6. Surprisingly, the dynamics of the more compact intermediate state does not get modified by the crowders. Overall, our result indicates that biomacromolecules of similar chemical composition and shape may exert their effect not only by different extent but also by a different mechanism, owing to their different sizes. © 2019 Elsevier B.V. All rights reserved.

1. Introduction Cell environment is exceptionally complex with the presence of proteins, sugars, osmolytes, nucleic acids, amino acids, molecular chaperons, inorganic salts, which are commonly known as crowders [1,2]. Depending on the size of the crowders, they are sub-classified as molecular or macromolecular crowders. It has been realized that these crowders could have a profound effect on the intracellular reactions through specific and non-specific interactions [3,4]. For example, the enzymatic activity or the structure of the active form of a protein in the actual cellular environment may be very different in comparison to the bulk buffer, where these crowders are absent [5–7]. These crowder molecules occupy a large cellular volume (almost 30–40% w/ v) and exclude some volume within the cell to be accessed by others [8,9]. Moreover because of the presence of the macromolecules in such high concentration, the solution inside the cell is 3–4 times more viscous than the buffer solution, usually used in in vitro studies [10]. All these will have a profound effect on the structure, dynamics, activity, stability, aggregation behavior and folding-unfolding kinetics of a protein [11–19]. The polymer looping is also found to be controlled by ⁎ Corresponding author at: Department of Chemistry, IIT Kanpur, India. E-mail address: [email protected] (P. Sen).

https://doi.org/10.1016/j.ijbiomac.2019.09.029 0141-8130/© 2019 Elsevier B.V. All rights reserved.

macromolecular crowding [20–22]. However, the in-cell crowding investigation or even the in-vitro cell mimicking using cell extracts are very difficult because of extremely complex and heterogeneous nature of the cellular interior. In such environment, the modulation of the protein signal might originate not only due to the bulk-crowding, but also from micro-environmental difference, confinement, adsorption, phase separation, etc. [23–26]. Instead, a varieties of synthetic substances, ca. polyethylene glycols (PEG), dextrans, ficolls, are usually used as the molecular crowders. In this investigation, we have focused on the stability of a protein inside the crowded milieu using artificial macromolecules (dextrans). Protein stability is generally characterized as the thermodynamic stability of the protein. This is to note that proteins are the most fundamental biomolecule inside a living body, and perform the essential molecular reactions in an extremely complicated fashion [27,28]. In such circumstances, different types of forces on the protein decides in which form it will stay within the cell [29]. Various factors can be responsible for altering this particular form of the protein and the ability of the protein to retain its original structural parameters against this disruption is called its stability [30]. The more a protein can maintain its specific structural motif against the disrupting forces, the more is its stability. Protein functions depend strongly on its structural parameters and hence on its stability. Therefore, the study of protein stability remains an exciting field

844

N. Das, P. Sen / International Journal of Biological Macromolecules 141 (2019) 843–854

among researchers from early times. The excluded volume effect often explains the effect of crowder on the protein stability. It originates from the fact that two solute molecules cannot access the same place at a given time making some space unavailable to the other solutes [31–35]. Therefore, a protein can access only a limited space in a crowded milieu as compared to the ideal solution [33,35]. Thus, crowder is expected to shift the folding-unfolding equilibrium of a protein in a direction in which the protein occupies less space. Generally, the native state of a protein is more compact than the denatured state and thus in the presence of crowder, the native state will be more favored. It is from the basic La Chatelier principle. The impact is entropic because it solely involves the arrangement of solutes and not their interactions [3,35]. The theory of this stability is sometimes called Hard-core repulsion theory as it arises due to the impenetrability of two solute molecules generating steric repulsion. Lately, there are several reports contrary to this general expectation, i.e., the unfolding process is more favorable in the crowded environment [36–42]. For example, Schlesinger et al. reported that immunoglobulin G binding domain of protein L becomes less stable in the crowded environment of cytoplasm [36]. Another report from the same group taking chymotrypsin inhibitor 2 (CI2) as the model system also suggests such type of destabilization inside the crowded mileu [37]. This observation has also been supported by the molecular dynamics simulation [39]. Parray et al. recently reported destabilization of myoglobin in the crowded environment imposed by an artificial crowder, polyethylene glycol (PEG) [38]. This suggests that some other forces may also be present in the crowded environment in addition to the excluded volume effect. Such forces has been identified as the soft chemical interaction between the crowder molecule and the protein [43]. This interaction may be attractive or repulsive [44,45]. Repulsive chemical interactions are stabilizing, as in a way they reinforce the effect of hardcore repulsion. Attractive chemical interactions, on the other hand, are destabilizing [44]. These type of interactions are generally nonspecific and increases the surface area of the

protein leading to unfolding [45]. These interactions are known to have an enthalpic component notwithstanding the entropic one [45]. Recognition of the individual terms leading to this overall stability of a protein holds high importance in understanding the mechanism of crowder induced changes in protein and ultimately in elucidating biological functions in a cellular environment [46]. In an in-vitro study, Ebbinghaus and co-workers reported that while dextran stabilizes ubiquitin, PEG destabilizes it through chemical interactions [47]. Taking the same ubiquitin as the model system, Pielak and coworkers suggest that both chemical interactions (enthalpic component) and hard-core repulsion (entropic part) must be taken into account when assessing the overall stability of the protein [48]. They have done thermal denaturation study in the presence of various crowders to determine the relative importance of the two factors that govern the overall stability of the protein inside the crowded milieu. Similar thermal denaturation study has been done to recognize the entropic and enthalpic term for other biosystems. Nesbit and co-workers found that enthalpy has a minimal role to play in deciding the overall stability of RNA in a crowded environment by synthetic PEG [49]. Therefore the stability of a protein has two components: enthalpic and entropic. The overall stability of a protein inside the crowded milieu depends on the fine balance between these two components [50–52]. Such interactions are very much protein and crowder specific and require a case to case study in recognition of individual stability component to understand the complexity. In a report by Singh et al. this protein specificity is well revealed by taking human serum albumin (HSA), and bovine serum albumin (BSA) as the test proteins, which shares 76% sequence homology yet shows very much different response to various artificial crowders like dextran, ficoll and PEG [53]. In this context, we want to mention that biological macromolecules are of various sizes and size-dependent systematic study of crowding is very important. In some previous publications; this sizedependency has been established both theoretically and experimentally [54–58]. In a report, the size distributions of macromolecules are proved

Fig. 1. (a) CD spectra of HSA with increasing temperature in the absence of crowder, (b) CD spectra of HSA with increasing temperature in the presence of 100 gL−1dextran-6 (c) CD spectra of HSA with increasing temperature in the presence of dextran-40. (d) Variation of α-helicity of HSA with increasing temperature in the absence of crowder and in the presence of 100 gL−1 dextran-6 and dextran-40. (e) % relative change of hydrodynamic radius of HSA with increasing temperature is shown. The concentration of HSA is maintained at 4 μM and the path length is 2 mm. Every experimental point is the average value of three independent measurements and the error bar indicates the standard deviation.

N. Das, P. Sen / International Journal of Biological Macromolecules 141 (2019) 843–854

to be crucial factors in determining the hydration structure and dynamics of proteins [55]. In a report by Zhou and co-workers, the FK-506 binding protein is found to be most stabilized by dextran-40 (among dextran-6, 10, 20, 40, 70, 100 and 150) against urea denaturation [56]. In another report from Chowdhury and co-workers, one can see that dextran-6 has the highest stabilization effect on HSA followed by dextran-70 and dextran-40 [57]. However, there is also report that stability of apoazurin does not change significantly with the variation of crowder size from dextran-20 to dextran-40 and dextran-70 [58]. In our previous publication, we have studied the size effect of macromolecular crowding on the structural, functional and dynamical response of human serum albumin (HSA) taking different sized dextrans as crowder [59]. Whereas, for dextran-40 and dextran-70, the effect can be satisfactorily explained by the pressure exerted by the crowder molecules on the protein surface; dextran-6 induced changes cannot be adequately explained by the pressure effect only. We have hypothesized the presence of some destabilizing, soft chemical interaction between HSA and dextran-6. To verify our hypothesis, in the present study we have studied the thermal denaturation in the presence of two different sized crowders to recognize the individual entropic and enthalpic term. By complete thermodynamic analysis, we want to investigate the difference in the origin of interaction between different sized crowders and protein. The recognition of the entropic and enthalpic contribution towards the overall stability has not been studied extensively probably because at high-temperature many proteins tend to aggregate [60]. So, a simple thermodynamic equilibrium model cannot be applied in such cases. However, in the present study, we have done the experiments at the single molecular level using fluorescence correlation spectroscopy (FCS), where sample concentration is maintained at around 50 nM. At this concentration range, the probability of aggregate formation is almost zero. Another advantage of FCS measurement is that it simultaneously furnishes information about the overall size change and also the very local conformational dynamics arising through a persistent interconversion between several closely related structures or confirmations of a protein [61]. This fluctuation is believed to influence the nearby environment and initiate different bio-molecular processes [62]. In this work, we have tagged the Tyr-411 residue of HSA, which is present in the domain-III of HSA. In fact, domain-III of HSA is the most important domain of the protein as it involves in binding and transporting various drugs like Warfarin, myristic acid, diazepam, and so forth and is also crucial for the esterase activity of HSA [63–65]. In one of our previous publication, we have reported the local dynamics around Tyr-411 of HSA along the thermal denaturation profile [65]. As discussed, this dynamical timescale is very important, and in this report, we have investigated how this thermal denaturation profile of the local structural dynamics changes in the presence of crowder. Thus, the main aim of this paper is two-fold. Firstly, to observe size dependent macromolecular crowding effect on the thermodynamics of protein unfolding at the single molecular level and by recognizing the entropic and enthalpic contribution we intend to understand how crowders of different sizes (with similar shape and chemical composition) affect a protein. Secondly, we intend to contemplate the macromolecular crowding effect on the active-site dynamics of the protein against thermal denaturation. 2. Materials and methods 2.1. Materials We have purchased human serum albumin (HSA, fatty acid-free), coumarin-343, 4-dimethylamino pyridine (DMAP), N, Ndicyclohexylcarbodiimide (DCC), 4-nitrophenol, dextran-6, dextran-40 and dialysis membrane (14 kDa cut-off) from Sigma-Aldrich. Dialysis membranes were washed according to the procedure given by SigmaAldrich. We have purchased analytical grade di sodium hydrogen

845

phosphate and sodium dihydrogen phosphate from Merck, India and used to prepare 50 mM buffer (pH 7.4). Centrifugal filtration units (Amicon Ultra, 10 kDa cutoff) have been purchased from Merck Millipore, Germany. HPLC grade dimethyl sulfoxide (DMSO), dichloromethane (DCM) were obtained from S. D. Fine Chemicals Ltd., India and used after distillation. 2.2. Synthesis of p-nitrophenyl coumarin ester (NPCE) We have synthesized NPCE following the procedure reported in our previous publications [59,65,66]. The details can also be found in the Supplementary data. 2.3. Protein labeling and sample preparation The Tyr-411 of HSA was tagged by NPCE following the procedure of Wang et al. [67]. The detailed methods can be found in our previous publications and also we have given the details in the Supplementary Data [56,62]. The labeled protein was concentrated by centrifuging the sample using 10 kDa cutoff filtration unit (5000 rpm, Eppendorf 5810R). For steady state and CD measurement, the protein concentration was maintained at around 4 μM. For single molecular level measurement, the protein concentration was maintained at 50 nM. Temperature-dependent experiments are performed after incubating the samples at the concerned temperature for 30 min. The reversibility of the processes in each step has also been checked. The crowder containing samples are equilibrited for 12 h at 4 °C before measuring the data. For emission and FCS measurements NPCE tagged HSA is used, whereas for the CD experiments, untagged HSA is used. 2.4. Instrumentation The absorption and emission spectra are recorded on a commercial UV–visible spectrophotometer (UV-2450, Shimadzu, Japan) and spectrofluorimeter (FluoroMax4, Jobin-Yvon, USA), respectively. Circular dichroism spectra are recorded in a commercial CD spectrometer (J-815, Jasco, Japan). We have performed the fluorescence correlation spectroscopic (FCS) measurements on an instrument built in our laboratory. The details of the setup and data fitting can be found in our previous publications as well as in the Supplementary Data [59,65]. We have prepared a very simple glass-cell for temperature dependent FCS study. The bottom of the cell has been closed by a cover-slip on which sample solution is taken. The temperature of the cell has been controlled using Labocon LLCB-202 temperature controller unit. For a single component system, assuming Gaussian detection volume, autocorrelation function can be written as [68] GðτÞ ¼

   −1=2    1 τ −1 τ τ 1þ 1þ 2 1 þ A∙ exp − N τD τR ω τD

ð1Þ

In the above equation, τD is the time constant for the diffusion, N is the number of particles in the observation volume and ω = l/r is the ratio of the longitudinal to transverse radius of the 3D Gaussian volume. Here, A is the amplitude of the other process than diffusion that may give rise to fluorescence fluctuation and τR is the timescale of such processes. By fitting the FCS autocorrelation curve we get two parameters, τD and τR. From the diffusion time (τD) and transverse radius of the observation volume (r), the diffusion coefficient and hydrodynamic radius (rH) of the molecule can be calculated using the following equations Dt ¼

r2 4τ D

ð2Þ

rH ¼

kB T 6πηDt

ð3Þ

846

N. Das, P. Sen / International Journal of Biological Macromolecules 141 (2019) 843–854

where, kB is the Boltzmann constant, T is the temperature in Kelvin and η is the viscosity of the solution. We took several FCS data (of varying concentration) of rhodamine 6G (R6G) in water and globally fitted them to determine the value of ω. While calibrating the value of ω, the diffusion coefficient of R6G in water is taken to be Dt = 4.14 × 10−6 cm2 s−1 [69]. For a particular set of experiment, while fitting the data with Eq. (1), ‘ω’ is kept fixed. With the addition of crowders or application of temperature, refractive index and viscosity of the solution may change significantly in addition to the diffusion properties of the protein therein. We have nullified the effect of the viscosity change by doing a control experiment at every experimental point taking R6G as the probe. R6G is a rigid molecule and will not go through any structural change when exposed to the crowder or heat. In this way, any change in its diffussion time through the detection volume with the addition of crowder or with the change in temperature will be exclusively because of the change in the medium viscosity. Using this information and the reported value of the hydrodynamic radius of R6G 7.7 Å in pH 7.4 buffer, we can calculate the hydrodynamic radius of HSA at every experimental point according to the following equation.

the wavelengths lower than 210 nm is also vital for secondary structural details, the CD data cannot be recorded beyond 210 nm as in that range the output voltage exceeds the instrument threshold. The raw data is plotted in the Fig. 1. We also have plotted the %-α-helicity and relative change of %- α-helicity as a function of temperature in the Fig. 1 for all the three cases, and the full set of the structural parameters are tabulated in the Table S2 of the Supplementary Data. The secondary structural contents do not change appreciably in the temperature range 15 °C to 50 °C. However, beyond that α-helicity gradually decreases to ~40% at 70 °C mainly on the expense of random coil. In the presence of 100 g L−1 dextran-6, the α-helicity of HSA is found to be 38% (at 15 °C), and on the application of heat, it goes to 21% at 70 °C. In the presence of 100 gL−1 dextran-40, the denaturation profile starts at 70% αhelicity at 15 °C and ends at 42% at 70 °C. 3.2. Steady-state absorption and fluorescence spectroscopic study

The change in refractive index is dealt by changing the objective collar position and setting it to have the minimum diffusion time for each sample. In this way, we maintain the lowest detection volume attainable for each sample.

Free NPCE shows absorption and emission maxima at 447.0 nm and 489.0 nm, respectively. Upon tagging to HSA, the absorption and emission maxima blue shifted to 439.0 nm and at 478.5 nm respectively at 25 °C (see Fig. S2 of the Supplementary Data). These values are in agreement with our previous reports [59,65,66]. In the absence of crowder, the emission maximum remain constant at 478.5 nm in the temperature range of 15 °C to 40 °C. Beyond 40 °C, the emission maximum gradually red-shifted with increasing temperature and reaches to 484.0 nm at 70 °C. In the presence of 100 g L−1 dextran-6 or dextran-40, the profile does not alter significantly (see Fig. 2). The raw data is given in the Fig. S3 of the Supplementary data.

3. Results

3.3. FCS measurement

3.1. Circular dichroism spectroscopy

In buffer, the autocorrelation curve for free NPCE gives a diffusion time of 24 ± 2 μs, whereas, the autocorrelation curve of NPCE tagged HSA gives a diffusion time of 132 ± 7 μs (see Fig. S4 of Supplementary data). From the diffusion time of NPCE labeled to HSA (132 μs), the hydrodynamic radius of native HSA is calculated to be 37.8 Å, which matches well with previous reports [59,65,66]. Here, we want to mention that the auto-correlation curve for free NPCE is satisfactorily fitted with pure diffusion equation but the autocorrelation curve of NPCE tagged to HSA cannot be fitted with the same equation. In this case, we have used Eq. (1), where we have incorporated some relaxation time constant. In our previous publications, we have proved that this timescale comes due to the conformational fluctuation of the protein [59,65,66]. Further, the autocorrelation curves for NPCE tagged HSA was recorded in a temperature range between 15 °C to 70 °C without and with 100 gL−1 dextran-6 and dextran-40 to measure the diffusion time and conformational fluctuation time. Some of the measured autocorrelation curves and the comparison of fitting by two different models are shown in Fig. 3. Earlier we had reported the thermal denaturation profile of HSA in another publication [65]. Here, for the sake of comparison, we are reproducing the result. The hydrodynamic radius of HSA at 15 °C without crowder is found to be 37.5 Å which remains almost unaltered up to 40 °C. With further increase in the temperature, the value of the hydrodynamic radius of HSA gradually increases and reaches to 56 Å at 70 °C. However, in the presence of crowders, the thermal denaturation profile of HSA gets modified significantly. In the presence of 100 g L−1 dextran-6, the hydrodynamic radius of HSA at 15 °C is found to be 37.9 Å, which is similar to the case when no crowder is present. In this case also, up to 40 °C, the hydrodynamic radius does not change significantly and after that increases up to 48.7 Å at 70 °C. In the presence of 100 g L−1 dextran-40, the denaturation profile starts from a relatively lower value of the hydrodynamic radius (34.9 Å) and attains the highest value of 43.7 Å at 70 °C. The change of hydrodynamic radius and %-relative change of hydrodynamic radius with increasing temperature without and with various crowders are plotted in Fig. 3d and e, respectively. As noted earlier, the additional exponential time

r HSA ¼ r R6G  H H

τ HSA D τ R6G D

ð4Þ

CD spectra of tagged and untagged HSA in 50 mM phosphate buffer (pH = 7.4) are recorded (see Fig. S1 of Supplementary data) to confirm that tagging has not perturbed the secondary structure of the protein greatly. The secondary structure of a protein is a combination of αhelices, β-sheets, β-turns, and random coil. The %-contribution of these secondary structural parameters are calculated using CDNN software (http://gerald-boehm.de) and shown in the Table S1 of the Supplementary Data for the tagged and untagged HSA [70]. Now, we proceed further to record the CD spectra of HSA at different temperatures (15 °C to 70 °C with a temperature gradient of 5 °C) in the absence of crowder and in the presence of 100 gL−1 dextran-6 and dextran-40. The CD signal is recorded from 210 nm to 260 nm. Though

Fig. 2. Variation of wavelength maxima of NPCE tagged HSA with increasing temperature in the absence of crowder and in the presence of dextran-6 and dextran-40. Excitation wavelength is 445 nm for all the cases. Every experimental point is the average of three independent measurements and the error bar indicates the standard deviation.

N. Das, P. Sen / International Journal of Biological Macromolecules 141 (2019) 843–854

847

Fig. 3. (a) A schematic representation to monitor translational and conformational dynamics of NPCE tagged HSA at the single molecular level with fluorescence correlation spectroscopy technique. The initial time component of ~8–15 μS (τR) gives information about the conformational fluctuation dynamics (local phenomenon within domain-III of HSA) whereas, the longtime component in the range of 100 s of μs (τD) gives information about the diffussion timescale (global phenomenon). From τD, hydrodynamic radis (rH) is calculated. Observation volume is maintained at ~0.7 fL in the present experiment. (b) Normalized autocorrelation curve for NPCE tagged HSA (i) in the absence of crowder, (ii) in the presence of 100 gL−1dextran-6 and (iii) in the presence of 100 gL−1dextran-40 at some representative temperatures. Comparison of fitting and the corresponding residuals are shown by solid cyan line (single diffusion equation) and solid black line (after incorporation of a relaxation time component). (c) Variation of conformational fluctuation time of NPCE tagged HSA with increasing temperature in the absence of crowder and in the presence of dextran-6 and dextran-40. (d) Variation of Hydrodynamic radius of NPCE tagged HSA with increasing temperature in the absence of crowder and in the presence of dextran-6 and dextran-40. (e) %-relative change of hydrodynamic radius of NPCE tagged HSA with increasing temperature in the absence of crowder and in the presence of dextran-6 and dextran-40. Every experimental point is the average of three independent measurements and the error bar indicates the standard deviation. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

component arises for such cases is due to the conformational fluctuation motion of domain-III of HAS [59,65,66]. Native HSA shows a conformational fluctuation time of 7.8 μs and its variation with increasing temperature is shown in the Fig. 3c, which matches well with our previous report [65]. The considerable difference in the diffussion dynamics and conformational fluctuation dynamics make it possible to assign them differently. As reported earlier a local minimum is observed around 40 °C [65]. At 15 °C, this timescale in the presence of 100 g L−1 dextran-6 is almost similar to the value when no crowder is present. In this case also, the denaturation profile goes through a minima, but around 50 °C. In the presence of 100 g L−1 dextran-40, the conformational fluctuation time is found to be ~13 μs at 15 °C and ~15 μs at 70 °C. In this case, the minima is achieved at around 40 °C, where the value of this time constant is ~7 μs.

4. Discussion First, by absorption, emission, and FCS measurement we have ascertained the covalent tagging of NPCE to the Tyr-411 residue of HSA as was done previously [59,65,66]. A brief discussion on this can be found in the Supplementary Data. Circular dichroism measurement indicates that the secondary structural contents of HSA do not alter appreciably upon tagging. The α-helicity of native HSA (at 25 °C) is calculated to be 66%, which is very much in line with previous results [59,65,66]. The secondary structural contents of HSA do not change much in the temperature range 15 °C to 50 °C, beyond which αhelicity gradually decreases for all the three cases. This suggests that only beyond 50 °C the thermal denaturation of HSA is operational. Our results indicate that the presence of crowders do not have any

848

N. Das, P. Sen / International Journal of Biological Macromolecules 141 (2019) 843–854

Fig. 4. Percent relative change of structural and dynamical parameters from various spectroscopic study in the course of thermal denaturation of HSA in the absence and presence of dextran-6 and dextran-40. The initial and final temperature are taken as 15 °C and 70 °C for the present analysis. The change of a spectroscopic parameter in the course of thermal denaturation in the absence of any crowder is normalized to 100%.

prominent role in modulating the thermal denaturation profile of HSA, at least qualitatively. To have a clearer idea about this fact we have plotted % decrease of α-helicity against temperature in Fig. 1b. This plot was necessary mainly because the thermal denaturation profile involving 100 g L−1 dextran-6 starts from a relatively lower value, and therefore difficult to compare. While the addition of 100 g L−1 dextran-40 does not significantly alter the native protein structure, the addition of 100 g L−1 dextran-6 greatly perturbs the protein structure even at ambient temperature. This structural perturbation is documented and explained on the basis of a destabilizing interaction between dextran-6 and HSA arises because of the penetration of smaller sized dextran-6 molecule into HSA matrix in our previous report [59]. This structural perturbation is likely to alter the thermodynamics of thermal denaturation. However, from the Fig. 1b it is clear that none of the two crowders used in this study have any effect on the thermal denaturation profile of HSA quantitatively or qualitatively. We have also monitored the thermal denaturation profile of HSA in the absence and in the presence of various crowders by monitoring NPCE-fluorescence. NPCE is covalently attached to the Tyr-411 residue in domain-III of HSA. Thus, by monitoring NPCE-fluorescence, we can have an idea about the local environment change involving domain-III of HSA during its thermal denaturation and how different crowders affect this pathway. From Fig. 2 it is clear that beyond 40 °C NPCE fluorescence is getting gradually red-shifted, probably because of the gradual opening of domain-III. However, we found that the profile remains the same in the presence of dextran-6 or dextran-40. Taken together, these two ensemble averaged spectroscopic study does not hint towards any significant crowder induced change of the global and local thermal denaturation profile of HSA. FCS measurements also reveal that thermal denaturation of HSA starts only after 40 °C. As discussed earlier, from FCS study, we get two parameters, namely hydrodynamic radius and conformational fluctuation time. Hydrodynamic radius furnishes information about the overall structure and conformational fluctuation time provides

information about the local dynamics. In both cases, we have observed a significant effect of crowders (see Fig. 3c and e). In Fig. 4, we have plotted % relative change of structural parameters from various spectroscopic survey in the course of thermal denaturation in the absence and presence of 100 gL−1 dextran-6 and 100 g L−1 dextran-40. While the bulk analysis is unable to differentiate between the three denaturation profiles, single molecular level measurement can clearly distinguish between these three. The FCS result indicates that both the crowders used in the study counteract the action of thermal denaturation and the stabilizing power of dextran-40 is higher as compared to that of dextran-6. To better quantify the extent of stabilization by the crowders we have defined the differential free energy change as ΔΔG ¼ ΔGcrowder −ΔGwithout crowder

ð5Þ

The structural transition (hydrodynamic radius in this case) during the course of thermal denaturation in the absence and presence of crowders is used to extract the free energy data of the transitions. To do so, we have assumed each denaturation profile as a two-state model [71]: F⇌U

ð6Þ

where, F stands for the folded state of the protein (in this case the protein conformation with lowest hydrodynamic radius), and U stands for the unfolded state of protein (in this case the protein conformation with highest hydrodynamic radius). The assumption of a reversible two state is based on the nature of the curves in Fig. 3d and also from the temperature reversal study (see Fig. S5 of the Supplementary data). We found that the hydrodynamic radius along the unfolding (with rise in the temperature) and folding (with decrease in the temperature) pathway of HSA matches well in 15 °C–70 °C temperature range. Although it can be a concern here that the hydrodynamic radius value does not saturate

N. Das, P. Sen / International Journal of Biological Macromolecules 141 (2019) 843–854

at 70 °C (see Fig. 3d), we chose this as the unfolded state in the reversible limit as beyond this temperature such reversibility is lost as shown in Fig. S6 of the Supplementary Data. Pico has also observed such reversible thermal denaturation of HSA up to 74 °C [72]. In this case, the equilibrium constant is defined as K¼

fU fF

ð7Þ

where, fU and fF are the fractions of unfolded and folded state, respectively. If the measured quantity associated with these two states are yU and yF, then considering a linear combination of contribution from each species the measured signal can be written as [73]: y ¼ y F f F þ yU f U ¼ y F

1 K þ yU 1þK 1þK

ð8Þ

Rearranging Eq. (8) we get K¼

y F −y y−yU

ð9Þ

The change of free energy is given by ΔG ¼ −RTlnK

ð10Þ

Combining Eqs. (9) and (10), we can determine the value of ΔG at each experimental point. Here, yF is taken as 33.9 Å and yU is taken as 56 Å. By applying Eq. (5), we have calculated ΔΔGDextran−6 and ΔΔGDextran−40 and listed them in Table 1. From Table 1, two conclusions can be drawn. Firstly, the positive values of ΔΔG demonstrate the stabilization of HSA by the crowders against thermal denaturation. Secondly, the stabilizing power of dextran-40 is higher as compared to that of dextran-6. Now, let move on and have a closer look at the values. At 25 °C, ΔΔGDextran−6 and ΔΔGDextran−40 are 10 cal K−1 mol−1 and 1225 cal K−1 mol−1, respectively, suggesting that at 25 °C, dextran-40 stabilizes HSA way more than dextran-6. However, at 70 °C, the values of ΔΔGDextran−6 and ΔΔGDextran−40 are 3305 cal K−1 mol−1 and 3925 cal K−1 mol−1, respectively. Here, two points to be noted. Firstly, with increasing temperature, the extent of stabilization by crowders

Table 1 Differential free energy change of thermal denaturation of HSA at various temperatures in the presence of 100 gL−1 dextran-6 and 100 gL−1 dextran-40. Temperature (°C)

ΔΔGDextran−6 (cal mol−1)

ΔΔGDextran−40 (cal mol−1)

−17

844

82

796

10

1225

63

1737

0

1255

31

1111

81

1098

167

1118

384

1165

676

1582

1138

1852

3305

3925

15 20 25 30 35 40 45 50 55 60 65 70

849

increases. We know that, ΔG = ΔH − TΔS. Therefore, with the change in temperature, only the entropic part changes, whereas, enthalpic contribution remains more or less unaltered (Though for many cases ΔH is a function of temperature, but obviously, that intrinsic dependence would be too small as compared to the dependence of entropic contribution). So, the effect of entropy is to stabilize the protein. Secondly, at higher temperature also dextran-40 stabilizes HSA more than that by dextran-6, but the effect of stabilization with temperature change is more pronounced for dextran-6 induced crowding than that by dextran-40. This suggests that entropic contribution is higher for dextran-6 than that for dextran-40. When crowder is introduced to the solution, a protein molecule is restricted in a smaller volume effectively reducing its randomness and limits the possible number of microstates. Dextran-6 excludes less volume as compared to that of dextran40 owing to its smaller size. Thus the change in the entropic term is expected to be higher for dextran-40. Hydrodynamic radius of dextran-6 is 18.6 Å and that of dextran-40 is 47.8 Å [74]. If we calculate the relative volume that the protein molecule cannot access in the presence of crowders, it will give us an idea about the relative effect due to the excluded volume (Vex). Considering hard-sphere model of crowder of radius rcr, the excluded volume for a particular crowder can be expressed as [75]: V ex ¼ 4  Ncr  V cr ¼ 4 

100 4π   r3cr M:W: 3

ð11Þ

where, Ncr represents the number of crowder molecules at 100 gL−1 crowder concentration, and Vcr represents the volume of one crowder molecule and M.W. is the molecular weight of the crowder. At a crowder concentration of 100 g L−1 the ratio of the volume excluded by dextran6 and dextran-40 turns out to be r3 V ex M:W dex−40 dex−6 ¼ 3dex−6  ¼ 1 : 2:54 ex V dex−40 r dex−40 M:W:dex−6

ð12Þ

This indicates that entropic contribution for dextran-40 should be much higher as compared to dextran-6. However, the experimental observation is just the opposite. It is to note that the crowding effect of macromolecules is anticipated by the assumption that molecules must avoid energetically unfavorable steric overlaps. So the presence of macromolecules in the solution imposes a constrain to the available volume by the protein. It seems very much perfect and easy to comprehend. But in this theory, we have neglected the solvent, principally water and to some extent small ions. Water strongly interacts with the protein molecule and the predominant part of the entropic gain mainly originated from the released water molecules around the hydrophobic residues [76]. However, the positional restriction of water might also play a crucial role. Recently, Sharp considered such small molecules to assess the effect of crowding and concluded that smaller is better as far as crowding is concerned [77]. They argued that the solvent molecules also could not overlap each other. Therefore, if the protein is constrained to a smaller volume between crowdres, then it will also be restricted to the smaller volume between water molecules. Also, the space between large crowders is additionally loaded up with small crowding agents. In Scheme 1 such situations are compared. The upper panel is the traditional description of the excluded volume effect. Obviously, here the protein's possible position is restrained with the introduction of the crowder. In the lower panel, we have considered the effect of water molecules as well. Now the question is, does the possible position of the protein look like more constrained with the introduction of the crowder? At least, now this does not seem to be so obvious, and we suggest that the entropic effect is a balance between the contribution from both crowder and water molecules. Many results are showing that smaller is better as far as crowder is concerned and we believe that this type of results are underreported as happens for most of the negative results. Our point is that the effect of the excluded volume is as

850

N. Das, P. Sen / International Journal of Biological Macromolecules 141 (2019) 843–854

Scheme 1. A schematic representation of the excluded volume effect. (a) Dashed circles indicate the excluded volume by a crowder molecule that will be unavailable to the protein. If a protein molecule is inserted to a solution of macromolecular crowder, it can access less volume as compared to the solution having no crowder molecule as indicated by a shorter dashed arrow. (b) Transfer of protein molecule from a solution of water to a solution of crowder. Water is also considered to be excluding. The net accessible space of the protein is not that much altered as indicated by almost equal length arrows.

apparent as gravity; as every molecule, be it micro or macro, will exclude, but its effect is not so straightforward to comprehend and is generally overestimated. For the present case, if we consider water also, then,

V ex dex−6 ¼ V ex dex−40

100  r 3dex−6 Mdex−6 ¼ 1 : 1:64 100 þ  r 3dex−40 M dex−40

55:55  r 3water þ 55:55  r 3water

ð13Þ

Here we want to mention that, though the effect of crowding is explained in terms of hard-sphere repulsion theory in the present calculation (as is the case for most of the previous reports), the absolute value of excluded volume does not give a reasonable number. As for example, with this assumption, the specific volume of dextran-40 would be 6.9 cm3 g −1. But in fact, the partial specific volume of dextran-40 is only about a tenth of that [58,78]. This suggests that dextran-40 is a random-coil polymer and hard-sphere theory fails miserably to estimate the excluded volume by such model crowder. However, in this report, we do not intend to calculate the perfect value. We are just estimating a relative number to compare two situations discussed in the study. Earlier, we have studied the

macromolecular crowding by various sized dextran molecules around HSA and have roughly estimated that the relative pressure exerted by dextran-6 is much higher compared to that by dextran40 on the protein surface [59]. This pressure effect also is nothing but the manifestation of entropic contribution as it does not consider any interaction, but only arrangement. So, the entropic contribution should be higher for dextran-6 induced crowding if we consider only the pressure. The take-home message is that, the traditional concept of excluded volume is not enough to account for the stability of a protein. Primarily the deviation of the expected stabilization originates from the contribution due to enthalpic term as we have seen in several previous reports [33–39]. Here, we are saying that even entropic part of the stabilization cannot be fully comprehended from the traditional picture of excluded volume. In the present contribution, we have quantified the relative contributions of the entropic and enthalpic part by considering the van't Hoff equation. Fig. 5 displays the ΔG0deconstruction curve in the form of lnK vs 1/T according to the van't-Hoff equation

ΔH0 ΔS0 þ lnK ¼ − RT R

ð14Þ

N. Das, P. Sen / International Journal of Biological Macromolecules 141 (2019) 843–854

Fig. 5. van't Hoff plot for the thermal denaturation equilibrium of NPCE tagged HSA in the absence of crowder and in the presence of dextran-6 and dextran-40.

The analysis yield a straight line (for a two-state transition model) ΔS0 ΔH0 and slope of− . We have defined differential R R 0 enthalpy change (ΔΔH ) and differential entropy change (ΔΔS0) according to the following two equations and listed them in Table 2. with an intercept of

ΔΔH⁰ ¼ ΔH⁰crowder −ΔH⁰without crowder

ð15Þ

ΔΔS⁰ ¼ ΔS⁰crowder −ΔS⁰without crowder

ð16Þ

The negative value of ΔΔH⁰ suggests that enthalpic contribution towards crowder induced overall change is destabilizing; whereas the negative sign of ΔΔS⁰ (entropic contribution, (−TΔΔS⁰) is positive for negative ΔΔS⁰) means that entropic contribution is stabilizing. A closer inspection of Fig. 5 and Table 2 depicts a fascinating result. The slopes of fitting ccorresponds to that without crowder and with 100 g L−1 dextran-40 are almost the same, suggesting that there is very small effect of enthalpic component in the dextran-40 induced stabilization process in the thermal denaturation of HSA. Whereas, the fitting curve of lnK vs 1000/T in the presence of 100 g L−1 dextran-6 shows a change in both its intercept and slope, suggesting that the effect of dextran-6 on the thermal denaturation profile of HSA is manifested both by entropic and enthalpic contribution. The origin of stabilizing entropic contribution comes from excluded volume effect and pressure effect, whereas the origin of destabilizing enthapic contribution is the soft chemical interaction. In case of dextran-6, such type of interaction is facilitated possibly because of the penetration of smaller sized dextran-6 into HSA matrix [59]. This result is extremely interesting where the two crowders of similar type and shape exerts its effect not only to a different extent but probably through different mechanism. Our result redefined the importance of the investigation of macromolecular crowding in a more extensive and case to case manner. Another interesting point is that, the larger change in entropy in the case of thermal denaturation in the presence of dextran-6 is almost compensated by a corresponding higher change in enthalpy, whereas, in the presence of dextran-40 the entropic Table 2 The entropic and enthalpic change of crowder induced stabilization of thermal denaturation profile for HSA.

ΔΔH⁰ (kcal mol−1) ΔΔS⁰(cal mol−1 K−1)

Dextran-6

Dextran-40

−8.1 −25.7

−1.8 −9.6

851

change is smaller and enthalpic part is negligible. This indicates towards a remarkable enthalpy-entropy compensation in the present study. Single molecular level measurement by FCS furnishes an additional timescale other than the diffusion. In our previous report, we have proved the origin of this extra-time component of 7.8 μs in domain-III of HSA as the conformational fluctuation time [63]. This dynamics is a very local phenomenon and furnishes information about the motion of domain-III of HSA. Because of this dynamics, the electron-rich amino acid residues around the NPCE molecule moves close and away from the probe, thus modulating its fluorescence behavior, and can be observed in FCS experiment [65,66]. In our previous report, we suggested the presence of an intermediate state in the thermal denaturation of HSA around 40 °C, where the deep in the denaturation profile was explained by the lower τr [65]. It is to note that the state around 40 °C cannot be represented as a linear combination of the states at 15 °C and 70 °C with a non-negative coefficient. The presence of such intermediate state in the thermal denaturation of domain-III and the absence of any intermediate state in the overall thermal denaturation path of HSA reinstate the fact that the domain specific behavior and overall behavior of a multi-domain protein might not be the same. The signature of this intermediate state is also observed in the presence of crowder. Because of the close proximity, quenching and the subsequent turn-on of the NPCE molecule become faster. The compactness and opening of the domain-III will be reflected upon the decrease and increase of this timescale. However, in the presence of crowder, the situation is more complicated. Here we need to consider another factor. A layer of crowder molecules may be formed around the HSA molecule, which in a way, imposes confinement to the system. Any confinement leads to the decrease of degrees of freedom and is expected to restrict the chain dynamics of domain-III of HSA; and consequently, the fluorescent quenching and subsequent turn-on of NPCE fluorescence get slower. Probably, this is the reason that the conformational fluctuation time of domain-III of HSA in the presence of 100 g L−1 dextran-40 starts from a very high value of ~13 μs at 15 °C (see Fig. 3c) as compared to when no crowder is present. The presence of smaller sized crowder, dextran-6, is probably not efficient in restricting the side chain dynamics as we have already indicated in our previous report [59].The more interesting point is that around 40 °C, the τr in the presence of both the crowders is almost similar to the value when no crowder is present. It suggests that the presence of crowders alter the conformational dynamics of the protein in every state except the most stable intermediate one. The result bears high significance because these intermediate states are crucial to carry out important biological processes inside the cell and are also responsible for protein misfolding [79]. Dextran-6 induced crowding shifts the local minima to 50 °C, probably because of its way of interaction with HSA. At higher temperature, the value of τr in the presence of 100 g L−1 dextran-40 is much higher as compared to the case where no crowder is present. The result reveals that both the native and thermally unfolded state shows a slower side chain dynamics likely because of the confinement imposes by dextran-40. However, it cannot alter the side chain dynamics of the more compact intermediate state. 5. Summary and conclusion In this report, we have scrutinized the effect of macromolecular crowding on the thermodynamics of protein unfolding through bulk and single molecular level spectroscopic measurement. While the bulk analysis is unable to differentiate between the denaturation profiles (absence and presence of crowders), single molecular level measurement can clearly distinguish between these. In our previous study we have hypothesized the presence of some destabilizing, soft chemical interaction between HSA and dextran-6, which is probably absent in the case of HSA and larger dextrans [59]. Complete thermodynamic analysis proves that there is a very small effect of the enthalpic component in the dextran-40 induced stabilization process of thermal denaturation of HSA. But the effect of dextran-6 is manifested both through entropic

852

N. Das, P. Sen / International Journal of Biological Macromolecules 141 (2019) 843–854

Scheme 2. Profile for the Hydrodynamic Radius and Conformational Fluctuation Time of HSA in the course of thermal denaturation in the absence and presence of various crowders. The role of solvent molecules in assessing the “excluded volume effect” and also the asymmetry in the spatial distribution of dextran-6 has been emphasized. The relative contributions of stability arising from the individual entropic and enthalpic component are also mentioned.

and enthalpic contribution. This not only supports the hypothesis of our previous conclusion but also quantifies the extent of stabilizing and destabilizing forces, which is very important to unravel the mechanism of crowder induced change. Apart from that, the followings are the main outcome of this report: (i) The two different sized crowders used in the survey counteract the action of thermal denaturation and the stabilizing power of dextran-40 is higher as compared to that of dextran-6. (ii) Overall stability is a combination of two factors, ca. entropy and enthalpy. Thermodynamic analysis proves that the entropic part is stabilizing, whereas enthalpic part is destabilizing in nature. The entropic contribution is higher for dextran-6 than that of dextran-40. Simple hard-core repulsion theory would have predicted a higher degree of entropic stabilization by dextran-40 than that by dextran-6. This discrepancy has been explained in terms of pressure effect, the overestimation of excluded volume because of not considering water molecules and the polymeric nature of dextran molecule for which hard sphere calculation fails miserably. (iii) The result reveals that both the native state and thermally unfolded state shows a slower side chain dynamics likely because of the confinement imposes by dextran-40. However, it cannot alter the side chain dynamics of the more compact intermediate state. Dextran-6, on the other hand, modifies the denaturation path to a smaller extent and shifts the intermediate state towards higher temperature. In the following scheme (Scheme.2) we have summarized our result. As a whole, the report demonstrates that crowders of different sizes, having similar shape and same chemical composition, may modulate a protein's behavior not only to different extent but through different mechanism. This reminds us of the substantial complexity of biological systems and probably there is no other way but a case to case study to decipher the crowder-induced changes of a protein. Fundamentally

speaking, this report gives a hint that the hard-sphere repulsion theory cannot even predict the entropic part of the overall stability. Obviously, more experiments, efficient calculations and better models are necessary to rationalize the behavior. In our next contribution, we will come up with a systematic study involving various crowders to point out various factors that may contribute to this entropy term. Declaration of competing interest The authors declare no competing financial interest. Acknowledgment ND acknowledges Council of Scientific and Industrial Research (CSIR, Government of India) for providing fellowship. PS thanks Visvesvaraya PhD Programme of Ministry of Electronics & Information Technology (MeitY), Government of India for providing young faculty research fellowship. This work is financially supported by Science and Engineering Research Board, Government of India (Grant No. EMR/2016/006555) and Indian Institute of Technology Kanpur. Appendix A. Supplementary data Synthesis of p-nitrophenyl coumarin ester (NPCE), Protein labeling and sample preparation, Fluorescence corelation spectroscopic set-up and data-processing method, Discussion on the covalent tagging of NPCE to Tyr-411 residue, Secondary structural parameters of untagged and NPCE tagged HSA, Secondary structural parameters of HSA with increasing temperature (a) Without crowder, (b) With 100 gL−1dextran6 (c) With 100 gL−1dextran-40; Circular dichroism spectra of untagged

N. Das, P. Sen / International Journal of Biological Macromolecules 141 (2019) 843–854

(blue) and NPCE tagged (cyan) HSA. Normalized absorption (dotted line) and emission spectra (solid line) of free NPCE (black line) and NPCE tagged to HSA (blue line); Normalized emission spectra of NPCE tagged HSA with increasing temperature (a) in the absence of crowder, (b) in the presence of 100 gL-1dextran-6 (c) in the presence of dextran40, Autocorrelation curve of free NPCE (black) and NPCE tagged to HSA (blue) in buffer; Variation of Hydrodynamic radius of NPCE tagged HSA with increasing the temperature from 15 °C to 70 °C (unfolding) and variation of Hydrodynamic radius of NPCE tagged HSA with decreasing temperature from 70 °C to 15 °C (Folding), Variation of Hydrodynamic radius of NPCE tagged HSA with increasing the temperature from 15 °C to 85 °C (unfolding) and variation of Hydrodynamic radius of NPCE tagged HSA with decreasing temperature from 85 °C to 15 °C (Folding).Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ijbiomac.2019.09.029. References [1] O. Medalia, I. Weber, A.S. Frangakis, D. Nicastro, W. Baumeister, Macromolecular architecture in eukaryotic cells visualized by cryoelectron tomography, Science 298 (2002) 1209–1214. [2] N.F. Dupuis, E.D. Holmstorm, D.J. Nesbitt, Tests of Kramers' theory at the singlemolecule level: evidence for folding of an isolated RNA tertiary interaction at the viscous speed limit, J. Phys. Chem. B 122 (2018) 8796–8804. [3] A.P. Minton, Excluded volume as a determinant of protein structure and stability, Biopolymers 20 (1981) 2093–2120. [4] M. Sarkar, C. Li, G.J. Pielak, Soft interactions and crowding, Biophys. Rev. 5 (2013) 187–194. [5] B.K. Derham, J.J. Harding, The effect of the presence of globular proteins and elongated polymers on enzyme activity, Biochim. Biophys. Acta 1764 (2006) 1000–1006. [6] B.P. Paudel, E. Fiorini, R. Börner, R.K.O. Sigel, D.S. Rueda, Optimal molecular crowding accelerates group II intron folding and maximizes catalysis, Proc. Natl. Acad. Sci. 115 (2018) 11917–11922. [7] N. Samanta, D. Das Mahanta, D. Patra, R.K. Mitra, Soft interaction and excluded volume effect compete as polyethylene glycols modulate enzyme activity, Int. J. Biol. Macromol. 118 ( (2018) 209–215. [8] S.B. Zimmerman, S. Trach, Estimation of macromolecule concentrations and excluded volume effects for the cytoplasm of Escherichia coli, J. Mol. Biol. 222 (1991) 599–620. [9] R.J. Ellis, Macromolecular crowding: obvious but underappreciated, Trends Biochem. Sci. 26 (2001) 597–604. [10] E.O. Puchkov, Intracellular viscosity: methods of measurement and role in metabolism, Biochem. (Moscow) Supp. Series A: Membrane and Cell Biol 7 (2013) 270–279. [11] A. Dhar, K. Girdhar, D. Singh, H. Gelman, S. Ebbinghaus, M. Gruebele, Protein stability and folding kinetics in the nucleus and endoplasmic reticulum of eucaryotic cells, Biophys. J. 101 (2011) 421–430. [12] H.X. Zhou, Protein folding and binding in confined spaces and in crowded solutions, J. Mol. Recognit. 17 (2004) 368–375. [13] D. Gnutt, J. Ahlers, B. König, M. Heyden, S. Ebbinghaus, SOD1 folding modulation in the crowded cell, Biophys. J. 114 (2018) 52–53. [14] H.X. Zhou, Influence of crowded cellular environments on protein folding, binding, and oligomerization: biological consequences and potentials of atomistic modeling, FEBS Lett. 587 (2013) 1053–1061. [15] N. Samanta, T.Q. Luong, D. Das Mahanta, R.K. Mitra, M. Havenith, Effect of short chain poly(ethylene glycol)s on the hydration structure and dynamics around human serum albumin, Langmuir 32 (2016) 831–837. [16] S. Mittal, L.R. Singh, Macromolecular crowding decelerates aggregation of a β-rich protein, bovine carbonic anhydrase: a case study, J. Biochem. 156 (2014) 273–282. [17] M. Erlkamp, S. Grobelny, R. Winter, Crowding effects on the temperature and pressure dependent structure, stability and folding kinetics of Staphylococcal nuclease, Phys. Chem. Chem. Phys. 16 (2014) 5965–5976. [18] J. Kundu, U. Kar, S. Gautam, S. Karmakar, P.K. Chowdhury, Unusual effects of crowders on heme retention in myoglobin, FEBS Lett. 589 (2015) 3807–3815. [19] Z.A. Parray, S. Ahamad, F. Ahmad, M.I. Hassan, A. Islam, First evidence of formation of pre-molten globule state in myoglobin: a macromolecular crowding approach towards protein folding in vivo, Int. J. Biol. Macromol. 126 (2019) 1288–1294. [20] J. Shin, A.G. Cherstvy, R. Metzler, Polymer looping is controlled by macromolecular crowding, spatial confinement, and chain stiffness, ACS Macro Lett. 4 (2015) 202–206. [21] J. Shin, A.G. Cherstvy, R. Metzler, Self-subdiffusion in solutions of star-shaped crowders: non-monotonic effects of inter-particle interactions self-subdiffusion in solutions of star-shaped crowders: non- monotonic effects of inter-particle interactions, New J. Phys. 17 (2015), 113028. [22] J. Shin, A.G. Cherstvy, R. Metzler, Soft matter kinetics of polymer looping with macromolecular crowding: effects of volume fraction and crowder size, Soft Matter 11 (2015) 472–488. [23] G. Rivas, A.P. Minton, Macromolecular crowding in vitro, in vivo, and in between, Trends Biochem. Sci. 41 (2016) 970–981.

853

[24] A.P. Minton, Confinement as a determinant of macromolecular structure and reactivity, Biophys. J. 63 (1992) 1090–1100. [25] C.D. Keating, Aqueous phase separation as a possible route to compartmentalization of biological molecules, Acc. Chem. Res. 18 (2012) 2114–2124. [26] H. Walter, D.E. Brooks, Phase separation in cytoplasm, due to macromolecular crowding, is the basis for micro compartmentation, FEBS Lett. 361 (1995) 135–139. [27] D. Nelson, M. Cox, Lehninger Principles of Biochemistry, 4th ed. W.H. Freeman and Company, New York, 2005. [28] C.N. Pace, S. Trevino, E. Prabhakaran, J.M. Scholtz, Protein structure, stability and solubility in water and other solvents, Philos. Trans. R. Soc. B 359 (2004) 1225–1235. [29] M. Michael Gromiha, Protein Bioinformatics, Elsevier, 2010 209–245. [30] M.C. Deller, B. Rupp, Protein stability: a crystallographer's perspective, Acta Cryst.F. 72 (2016) 72–95. [31] H.X. Zhou, Loops, linkages, rings, catenanes, cages, and crowders: entropy-based strategies for stabilizing proteins, Acc. Chem. Res. 37 (2004) 123–130. [32] A. Dhar, A. Samiotakis, S. Ebbinghaus, L. Nienhaus, D. Homouz, M. Gruebele, M.S. Cheung, Structure, function, and folding of phosphoglycerate kinase are strongly perturbed by macromolecular crowding, Proc. Natl. Acad. Sci. 107 (2010) 17586–17591. [33] J.B.C. Papers, A.P. Minton, The influence of macromolecular crowding and macromolecular confinement on biochemical reactions in physiological media, J. Biol. Chem. 276 (2001) 10577–10581. [34] I.M. Kuznetsova, B.Y. Zaslavsky, L. Breydo, K.K. Turoverov, V.N. Uversky, Beyond the excluded volume effects: mechanistic complexity of the crowded milieu, Molecules 20 (2015) 1377–1409. [35] A.P. Minton, Biochemical consequences, Mol. Cell. Biochem. 140 (1983) 119–140. [36] A.P. Schlesinger, Y. Wang, X. Tadeo, O. Millet, G.J. Pielak, Macromolecular crowding fails to fold a globular protein in cells, J. Am. Chem. Soc. 133 (2011) 8082–8085. [37] M. Sarkar, A. Smith, G.J. Pielak, Impact of reconstituted cytosol on protein stability, Proc. Natl. Acad. Sci. 110 (2013) 19342–19347. [38] Z.A. Parray, S. Shahid, F. Ahmad, M.I. Hassan, A. Islam, Characterization of intermediate state of myoglobin in the presence of PEG 10 under physiological conditions, Int. J. Biol. Macromol. 99 (2017) 241–248. [39] M. Feig, Y. Sugita, Variable interactions between protein crowders and biomolecular solutes are important in understanding cellular crowding, J. Phys. Chem. B 116 (2011) 599–605. [40] N. Samanta, D. Das Mahanta, S. Hazra, G.S. Kumar, R.K. Mitra, Short chain polyethylene glycols unusually assist thermal unfolding of human serum albumin, Biochimie 104 (2014) 81–89. [41] I. Yu, T. Mori, T. Ando, R. Harada, J. Jung, Y. Sugita, M. Feig, Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm, eLife. 5 (2016) 1–22. [42] L.A. Benton, A.E. Smith, G.B. Young, G.J. Pielak, Unexpected effects of macromolecular crowding on protein stability, Biochemistry 51 (2012) 9773–9775. [43] M. Sarkar, C. Li, G.J. Pielak, Soft interactions and crowding, Biophys. Rev. 5 (2013) 187–194. [44] M. Rubenstein, R.H. Colby, Polymer Physics, Oxford University Press, New York, 2003. [45] G.I. Makhatadze, P.L. Privalovab, Protein interactions with urea and guanidinium chloride. A calorimetric study, J. Mol. Biol. 226 (1992) 491–505. [46] A.P. Minton, Quantitative assessment of the relative contributions of steric repulsion and chemical interactions to macromolecular crowding, Biopolymers 99 (2013) 239–244. [47] M. Senske, L. Törk, B. Born, M. Havenith, C. Herrmann, S. Ebbinghaus, Protein stabilization by macromolecular crowding through enthalpy rather than entropy, J. Am. Chem. Soc. 136 (2014) 9036–9041. [48] Y. Wang, M. Sarkar, A.E. Smith, A.S. Krois, G.J. Pielak, Macromolecular crowding and protein stability, J. Am. Chem. Soc. 134 (2012) 16614–16618. [49] N.F. Dupuis, E.D. Holmstrom, D.J. Nesbitt, Molecular-crowding effects on singlemolecule RNA folding/unfolding thermodynamics and kinetics, Proc. Natl. Acad. Sci. 111 (2014) 8464–8469. [50] R. Politi, D. Harries, Enthalpically driven peptide stabilization by protective osmolytes, Chem. Commun. 46 (2010) 6449–6451. [51] S. Sukenik, L. Sapir, R. Gilman-Politi, D. Harries, Diversity in the mechanisms of cosolute action on biomolecular processes, Faraday Discuss. 160 (2013) 225–237. [52] L. Sapir, D. Harries, Origin of enthalpic depletion forces, J. Phys. Chem. Lett. 5 (2014) 1061–1065. [53] P. Singh, P.K. Chowdhury, Crowding-induced quenching of intrinsic tryptophans of serum albumins: a residue-level investigation of different conformations, J. Phys. Chem. Lett. 4 (2013) 2610–2617. [54] T. Ando, I. Yu, M. Feig, Y. Sugita, Thermodynamics of macromolecular association in heterogeneous crowding environments: theoretical and simulation studies with a simplified model, J. Phys. Chem. B 120 (2016) 11856–11865. [55] P. Wang, I. Yu, M. Feig, Y. Sugita, Influence of protein crowder size on hydration structure and dynamics in macromolecular crowding, Chem. Phys. Lett. 671 (2017) 63–70. [56] J. Batra, K. Xu, H.X. Zhou, Nonadditive effects of mixed crowding on protein stability, Proteins 77 (2009) 133–138. [57] S. Biswas, P.K. Chowdhury, Unusual domain movement in a multidomain protein in the presence of macromolecular crowders, Phys. Chem. Chem. Phys. 17 (2015) 19820–19833. [58] A. Christiansen, P. Wittung-Stafshede, Quantification of excluded volume effects on the folding landscape of Pseudomonas aeruginosa apoazurin in vitro, Biophys. J. 105 (2013) 1689–1699.

854

N. Das, P. Sen / International Journal of Biological Macromolecules 141 (2019) 843–854

[59] N. Das, P. Sen, Structural, functional, and dynamical responses of a protein in a restricted environment imposed by macromolecular crowding, Biochemistry 57 (2018) 6078–6089. [60] M. Rosa, C.J. Roberts, M.A. Rodriguez, Connecting high-temperature and lowtemperature protein stability and aggregation, PLoS One 12 (2017), e0176748. [61] A.W. Kahsai, S. Rajagopal, J. Sun, K. Xiao, Monitoring protein conformational changes and dynamics using stable-isotope labeling and mass spectrometry, Nat. Protoc. 9 (2014) 1301–1319. [62] J. Guo, H.X. Zhou, Protein allostery and conformational dynamics, Chem. Rev. 116 (2016) 6503–6515. [63] H. Watanabe, S. Tanase, K. Nakajou, T. Maruyama, U. Kragh- Hansen, M. Otagiri, Role of arg-410 and tyr-411 in human serum albumin for ligand binding and esteraselike activity, Biochem. J. 349 (2000) 813–819. [64] J. Ghuman, P. Zunszain, I. Petitpas, A. Bhattacharya, M. Otagiri, S. Curry, Structural basis of the drug-binding specificity of human serum albumin, J. Mol. Biol. 353 (2005) 38–52. [65] B. Sengupta, N. Das, P. Sen, Elucidation of μs dynamics of domain-III of human serum albumin during the chemical and thermal unfolding: a fluorescence correlation spectroscopic investigation, Biophys. Chem. 221 (2017) 17–25. [66] B. Sengupta, A. Acharya, P. Sen, Elucidation of the local dynamics of domain-III of human serum albumin over the ps–μs time regime using a new fluorescent label, Phys. Chem. Chem. Phys. 18 (2016) 14350–14358. [67] R. Wang, S. Sun, E. Bekos, F.V. Bright, Dynamics surrounding Cys-34 in native, chemically denatured, and silica-adsorbed bovine serum albumin, Anal. Chem. 67 (1995) 149–159. [68] J.R. Lakowicz, Principles of Fluorescence Spectroscopy, 3rd ed Springer, New York, 2006.

[69] C.B. Müller, A. Loman, V. Pacheco, F. Koberling, D. Willbold, W.J. Richtering, Precise measurement of diffusion by multi-color dual-focus fluorescence correlation spectroscopy, Europhys. Lett. 83 (2008) 46001(1)–46001(5). [70] G. Böhm, R. Muhr, R. Jaenicke, Quantitative analysis of protein far UV circular dichroism spectra by neural networks, Protein Eng. 5 (1992) 191–195. [71] W.J. Becktel, J. Schellman, Protein stability curves, Biopolymers (11) (1987) 1859–1877. [72] G. Pico, Thermodynamic features of the thermal unfolding of human serum albumin, Int. J. Biol. Macromol. 20 (1997) 63–73. [73] A. Rani, P. Venkatesu, Insights into the interactions between enzyme and cosolvents: stability and activity of stem bromelain, Int. J. Biol. Macromol. 73 (2015) 189–201. [74] M.A. Masuelli, Dextrans in aqueous solution. Experimental review on intrinsic viscosity measurements and temperature effect, J. Polymer Biopolymer Phys. Chem. 1 (2013) 13–21. [75] J. Shin, A.G. Cherstvy, R. Metzler, Kinetics of polymer looping with macromolecular crowding: effects of volume fraction and crowder size, Soft Matter 11 (2015) 472–488. [76] D. Chandler, Interfaces and the driving force of hydrophobic assembly, Nature 437 (2005) 640–647. [77] K.A. Sharp, Analysis of the size dependence of macromolecular crowding shows that smaller is better, Proc. Natl. Acad. Sci. 112 (2016) 7990–7995. [78] A. Christiansen, Q. Wang, A. Samiotakis, M.S. Cheung, P. Wittung-Stafshede, Factors defining effects of macromolecular crowding on protein stability: an in vitro/in silico case study using cytochrome c, Biochemistry 49 (2010) 6519–6530. [79] R. Santucci, F. Polticelli, L.F. Sinibaldi, Recent advances in medicinal chemistry: role of intermediate states in protein folding and misfolding, recent advances in medicinal chemistry, Bentham Science Publishers 1 (2014) 433–455.