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IV. Protein Sorption and Denaturation

IV. Protein Sorption and Denaturation

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Figure 4 Schematic view of protein interaction with a solid surface. Adapted with permission

from Andrade, J. D. and Hlady, V. (1986). Protein adsorption and material biocompatibility: A tutorial

review and suggested hypothesis. Adv. Polym. Sci. 79, 1–63. Copyright Springer-Verlag GmbH &

Co. KG.

more sorption sites become active during unfolding of the protein, and the desorption becomes less likely (Fig. 5).

During adsorption, various parts of the protein molecule attach to the solid

surface. To desorb the molecule from the surface, all of these attachment sites

have to be released simultaneously, which requires a considerable amount of energy

(Norde, 1995). Diluting the aqueous phase as in the standard desorption procedure

usually does not desorb proteins from a surface very well. Desorption may be

increased by changing pH, ionic strength of the solution, or by adding compounds,

such as other proteins, that compete for sorption sites. It is also likely that in some

cases the desorbed molecules differ from their original structure, and it has been

found that in many cases the adsorption is not completely reversible (Norde, 1995).

It is also known that in the case of irreversible adsorption, the amount of proteins

adsorbed increases with increasing bulk concentration (Ramsden, 1995b). There

is a controversy in the literature about the explanation for this finding. Hypotheses

are that (i) proteins adsorb in two or more distinct orientations at the surface,



Figure 5 Schematic view of sorption of a soft protein. (1) Adsorption/desorption of native protein.

(2) Structural rearrangement at the surface interface. (3) Adsorption/desorption of conformationally

changed molecule. (4) Transformation to native state. Adapted from Kleijn and Norde (1995). The

adsorption of proteins from aqueous solution on solid surfaces. Heterog. Chem. Rev. 2, 157–172.

Copyright C John Wiley & Sons Limited. Reproduced with permission.

(ii) proteins form an ordered two-dimensional crystal on the surface, and (iii)

proteins denature at the surface (Ramsden, 1995b).

As discussed earlier, several types of interactions (e.g., electrostatic, hydrophobic, and hydrogen-bonding) are involved in the sorption of protein and other

colloidal particles. The magnitudes of the various interactions determine the thermodynamic aspects of the sorption behavior in colloid and protein systems. Strong

interactions between particles and the surface, often leading to irreversible sorption, have been observed with polymer microspheres (Johnson and Elimelech,

1995; Johnson and Lenhoff, 1996; Semmler et al., 1998) and proteins (Andrade

and Hlady, 1986; Kondo and Mihara, 1996; Norde and Lyklema, 1978; Soderquist

and Walton, 1980). In many protein systems, however, protein–surface interactions

are relatively weak and are affected by changing solution conditions (Yuan et al.,

2000). In general, the extent and mechanisms of protein sorption depend upon

the balance between particle–surface attraction and particle–particle repulsion. In

their review, Yuan et al. (2000) outlined the following possible types of protein

sorption reactions.

1. Irreversible sorption. When the attraction between a charged particle and an

oppositely charged surface is very strong, the particle is likely to maintain a

stable position at the surface. Such an irreversible sorption behavior cannot

be captured accurately with equilibrium models. Rather, random sequential

adsorption (RSA)-type models have been found to be more appropriate.

2. Reversible sorption at low surface coverage. The particles may not bind permanently to any specific segment of the solid surface when particle–surface



interaction is relatively weak. Instead, they may attach to various parts of the

surface or undergo desorption, in which case equilibrium sorption models can

be used to describe such behavior.

Whether an irreversible or a reversible sorption reaction occurs is determined

by the balance between particle–surface and particle–particle interactions, both

of which are influenced by solution pH and ionic strength as well as particle size

(Oberholzer and Lenhoff, 1999; Yuan et al., 2000). Based on energetic considerations, irreversible sorption is more frequent for large particles, whereas reversible

sorption is more frequent for smaller particles (Yuan et al., 2000).


1. Equilibrium

Protein sorption has usually been described with the Langmuir isotherm. The

assumptions made for the Langmuir isotherm to be applicable are that (i) adsorption occurs in a monolayer, (ii) the surface is homogeneous, (iii) adsorption does

not affect the energy status of other molecules, (iv) only one adsorbing species

is present, and (v) sorption is reversible. Recent evidence, however, has shown

mechanisms different from those of Langmuir-type behavior for protein sorption.

Alternative approaches to describe protein sorption kinetics are discussed in the

following sections.

2. Kinetics

Many different approaches have been proposed to describe kinetics of protein

sorption. The basic model is the kinetic Langmuir model,


= κ1 φC − κ2 S,



φ = Smax − S.



In this model, the sorption process is completely reversible. The parameter φ represents the number of available sorption sites. For equilibrium conditions, Eqs. (26)

and (27) reduce to the Langmuir isotherm (Eq. 1).

To account for the specific characteristics of protein sorption, such as the timedependent conformational changes, the basic Langmuir model has been extended

by adding additional compartments. The reactions between the compartments are

assumed to be reversible, irreversible, or time-dependent. Andrade and Hlady

(1986) give an overview over these types of models and propose a general model

as shown in Fig. 6. This model assumes that the desorption is time dependent and



Figure 6 A general kinetic model for protein sorption in case of reversible denaturation. Adapted

with permission from Andrade and Hlady (1986). Protein adsorption and material biocompatibility: A

tutorial review and suggested hypothesis. Adv. Polym. Sci. 79, 1–63. Copyright Springer-Verlag GmbH

& Co. KG.

that denaturated proteins quickly regain their native state. The return to the native

state is justified when no covalent bonds have been formed during the denaturation

process (Andrade and Hlady, 1986). This general model differs slightly from the

concept shown in Fig. 5, where denaturated proteins may sorb reversibly and

denaturation is considered to be more likely irreversible. Specifics on how to

model time-dependent reactions are given in Soderquist and Walton (1980). These

authors proposed that adsorption and desorption rates can be written as




κ1,i C(ti ) −

κ2,i S(ti ),


where the rate constants κ 1,i and κ 2,i change with time.

The kinetic Langmuir model implies that sorption is reversible and takes place

at definite sites, and the sorbed molecules do not interfere with each other. However, at most surfaces sorption takes place at randomly selected positions. For

large molecules, this random sorption on the surface may lead to gaps between

sorbed molecules that cannot be filled anymore. It has also been observed that the

adsorption is in many cases irreversible.

The random adsorption leads to inaccessible sorption sites, and the available fraction of sites φ is actually smaller than Smax − S (Widom, 1966). This

surface-exclusion effect has been formulated mathematically by sequentially placing particles of given size randomly on a line or plane and is often referred to as

the “parking problem”(Feder and Giaever, 1980; Feder, 1980). Figure 7 shows a

one-dimensional schematic of a Langmuir and parking problem process. Schaaf

and Talbot (1989a, 1989b) presented the first kinetic analysis of the surfaceexclusion process, and they write the kinetic expression in a generalized Langmuir



= κ1 φ( )C − κ2 ,




Figure 7


Schematic of a one-dimensional Langmuir sorption process and “parking problem.”

where is the surface coverage given by = S/Smax, and the surface exclusion

effect is represented by the function φ( ). This surface exclusion can be formulated

in different ways, depending on the processes occurring during sorption.

Random sequential adsorption theory (RSA) was developed to model the irreversible deposition of colloidal particles. In the RSA process it is assumed that

(i) the particles cannot overlap on the surface, (ii) adsorption is irreversible (κ 2 = 0

in Eq. 29), and (iii) sorbed particles do not diffuse on the surface. In this case, and

assuming spherical particles, the function φ( ) is given by (Schaaf and Talbot,




6 3 2


+ √

+ O( 4 ).


φ =1−4 +



The RSA model is a two-dimensional simulation of the adsorption process in which

a disk is placed at a random location on a planar surface. The placement continues

until no more disks can fit on the surface without overlap with others previously

placed on the surface. The jamming limit, given as the fraction of the total surface

area covered by disks, is found empirically to be max = 0.547. Equation (30) is

valid for < 0.3. At higher surface coverage, the kinetics can be approximated

with (Schaaf and Talbot, 1989b)

φ = 8.98(


− )3 .


Only steric interactions between adsorbed particles are accounted for in the basic

RSA model (Yuan et al., 2000). Deviations from RSA deposition have been found

in several experimental studies of charged particle adsorption where the maximum

surface coverage was dependent upon ionic strength (Johnson and Elimelech, 1995;

Johnson and Lenhoff, 1996; Semmler et al., 1998). The results of these studies

indicate that the effective jamming limit was significantly lower than the 54.7%

predicted by the basic RSA model at low ionic strength and increased to approach

the 54.7% maximum coverage with increasing ionic strength. Therefore, a modified version of the RSA model has been developed to include particle–particle

electrostatic repulsion. Such modification requires the adsorbing particle to avoid

overlap with particles already adsorbed as well as to avoid adsorbing in close



proximity to each other when electrostatic repulsion is large. Taking into account

the effect of the electrostatic particle–particle repulsion, the maximum coverage

can be expressed as (Semmler et al., 1998)


= 0.547(a/aeff )2 ,


where a is the actual radius of a charged particle and aeff is the radius of the effective

area excluded by the charged particle.

A variety of other extensions and generalizations of the basic RSA model have

been developed in recent years. Among these are the consideration of the relative

importance of diffusion and sedimentation prior to particle deposition (Lavalle

et al., 1999) and the application of RSA to particle deposition during flow

in porous media (Ko and Elimelech, 2000; Ko et al., 2000). During transport

of charged particles in porous media, hydrodynamic as well as electrostatic

interactions cause deviations from standard RSA behavior, and a modified

blocking function taking into account particle size, flow velocity, and electrolyte

concentrations has been developed (Ko et al., 2000).

Figure 8 shows the effect of the dynamic blocking function on the rate of adsorption in a flowthrough reactor. We consider a flowthrough reactor where the

concentration in the aqueous phase is constant, and plot the rate of adsorption versus

the amount sorbed on the sorbent. The solid line denotes an irreversible Langmuir

kinetics (Eqs. 26, 27 with κ 2 = 0), the dashed line represents RSA (Eqs. 29–31).

The parameter κ 1 has been chosen as 1. Langmuir kinetics shows a linear dependence, whereas in RSA the rate of adsorption is initially faster and decreases with

increasing surface coverage.

Figure 8 Rate of surface coverage as a function of surface coverage for inrreversible Langmuir

and RSA type of kinetics in a flowthrough reactor.



The RSA kinetics has been experimentally verified in some cases and was found

to be superior to the Langmuir kinetics (Adamczyk et al., 1992; Kurrat et al.,

1994; Ramsden, 1995a). Many other theoretical approaches of the RSA type have

been developed (Adamczyk et al., 1992, 1999; Adamczyk, 2000; Evans, 1993;

Kurrat et al., 1994; Oberholzer et al., 1997), but most of them have not yet been

experimentally tested.



Many factors may influence virus survival in the subsurface environment

(Table I). Virus inactivation is defined as a loss of viral titer with time due to

disruption of coat proteins and degradation of nucleic acid (Gerba, 1984). A large

body of evidence indicates that temperature is the primary influential factor in the

survival of viruses in soil and groundwater (Straub et al., 1992; Yahya et al., 1992;

Yates et al., 1985). Lefler and Kott (1974) found that it took 42 days for 99% inactivation of poliovirus in sand at 25◦ C, whereas for the same degree of inactivation

more than 175 days were required at 18◦ C. Poliovirus was found to persist for

more than 180 days in saturated sand and sandy loam soils at 4◦ C, whereas no

viruses could be recovered from the soils incubated at 37◦ C after 12 days (Yeager

and O’Brien, 1979). Hurst et al. (1980) studied the survival of poliovirus at three

temperatures: 1, 23, and 37◦ C in a loamy sand. They found that the inactivation rate

was significantly correlated with incubation temperature, noting faster inactivation

rates at the highest temperatures.

Generally, viruses seem to survive longer under moist as compared to dry conditions. Bagdasaryan (1964) observed that several enteroviruses, including poliovirus 1, coxsackievirus B3, and echoviruses 7 and 9, could survive for 60 to

90 days in soil with 10% moisture as compared with only 15 to 25 days in airdried soils. Ninety-nine percent inactivation of poliovirus occurred in 1 week as

the soil moisture content was reduced from 13 to 0.6%; however, 7 to 8 and 10

to 11 weeks were required for the same amount of inactivation in soils with 25

and 15% moisture content, respectively (Sagik et al., 1978). Hurst et al. (1980)

found that the poliovirus inactivation rate increased as the moisture content was

increased from 5 to 15%, then decreased as more liquid was added.

When viruses are sorbed to a solid surface, such as a clay particle, they are

generally protected from inactivation. Sobsey et al. (1986) compared the rate of

inactivation of hepatitis A virus in five different soil types including a clay soil, a

clay loam, a loamy sand, a sand, and an organic muck. Survival was the greatest in

the clay soils, in which at least 8 weeks were required to inactivate 99% of the

infectious viruses. This may be due to virus sorption to the soils. Reductions in virus



inactivation rates have been reported for virus adsorbed to soil (Hurst et al., 1980),

to clay minerals (Babich and Stotzky, 1980; Lipson and Stotzky, 1984a; Taylor

et al., 1980), to estuarine sediments (Bitton, 1974; Gerba and Schaiberger, 1975;

Liew and Gerba, 1980; Smith et al., 1978), and to sewage solids (Gerba et al., 1978).

The protective effect of virus association with particulate matter or other surfaces

includes protection from proteolytic enzymes or other substances which inactivate

viruses, increased stability of the viral capsid, prevention of virus aggregation

formation, and blocking of ultraviolet radiation (Gerba, 1984). Protection of viruses

against thermoinactivation has been suggested from the results of Bitton et al.

(1976), Liew and Gerba (1980), and Stotzky et al. (1981).

Although virus association with solids in natural environments has generally

been observed to be protective, the association with metal and metal oxide surfaces has been found to enhance virus inactivation. Bacteriophages MS-2 and f2

were inactivated in fluids that had been in contact with Al3+, Zn2+, and Mg2+

(Yamamoto et al., 1964). Atherton and Bell (1983) observed degradation of MS-2

into small fragments after trichloroethylene elution from magnetite at pH 10. Poliovirus readily adsorbed to several metal oxide surfaces and was inactivated at the

surface of MnO2 and CuO (Murray and Laband, 1979). Studies also have shown

that Cu2+ and Fe3+ can cause virus inactivation, and viruses that are enveloped or

contain RNA are more sensitive to inactivation to Cu2+ than those that are nonenveloped or contain DNA (Sagripanti 1992; Sagripanti et al., 1993). The presence

of iron oxides (mainly goethite) was found to be responsible for the sorption and

inactivation of MS-2; however, φX174 was not affected by the metal oxides (Chu

et al., 2000). These results indicate that the degree of inactivation due to metals

and metal oxides is virus specific.

Other factors such as UV radiation (Battigelli et al., 1993), dissolved oxygen

level (Scheuerman et al., 1991), organic matter concentration and pH (Campos

et al., 2000), certain cations (Quignon et al., 1998; Sagripanti et al., 1993; Siegl

et al., 1984; Wallis et al., 1962), and the presence of other microorganisms (Hurst,

1988; Yates et al., 1990) have also been found to influence virus survival in the

subsurface environment. Because viruses can be quite persistent and mobile in

soil and groundwater, there is a need to better understand and quantify the factors

that influence virus survival behavior. A more detailed discussion on the factors

affecting virus inactivation can be found in Schijven and Hassanizadeh (2000).


Virus inactivation is often assumed to follow first-order kinetics (Sim and

Chrysikopoulos, 1996; Yates and Yates, 1988), although deviations from this rate

law have been noted for many years (Chang, 1966). In particular, the interplay of

different factors affecting virus survival will likely cause deviations from simple

first-order kinetics.



Several types of regression equations have been used by Hurst et al. (1992)

to relate virus inactivation to environmental parameters. Among eight equations




= log10 β0 + β1 log10 X 1 + · · · + βn log10 X n + βt log10 t



was found to be most suitable (Hurst et al., 1992), where N0 is the titer at time zero,

Nt is the titer at some subsequent observation time t, and X1 through Xn represent

independent variables, i.e., water conductivity, water turbidity, incubation time,

incubation temperature, and ability to support bacterial growth. The values β 0

through β t represent the respective coefficients assigned to the independent variables X1 through Xn.

Other possible causes of non-first-order inactivation include natural variations

in the lability of individual virus particles (virions) in a viral population (Pollard

and Solosko, 1971; Yamagishi and Ozeki, 1972), the association of viruses with

nonviral colloidal material (Babich and Stotzky, 1980; Bitton, 1974; Gerba and

Schaiberger, 1975), or the presence of viral aggregates in the inactivating suspension (Sobsey, 1966). Grant (1995) developed a kinetic model for the inactivation

of viruses that exhibit a range of initial aggregate sizes. Virus aggregation is a

concern mainly because it affects the biological activity of viruses in the following

ways: (i) if viral aggregates consist of many virions that are individually infective,

the overall level of infectivity of an aggregated suspension is reduced relative to

the dispersed state; and (ii) aggregates may be more resistant to inactivation than

single virions (Floyd and Sharp, 1978). In his model, Grant (1995) assumed that

viral aggregates are more resistant to inactivation than a single virion because all

virions within an aggregate must be inactivated before the aggregate as a whole

is considered inactive, and undamaged components of inactive virions within an

aggregate may recombine to cause host–cell infection (multiplicity reactivation

(MR)). Grant proposed three different inactivation laws for three different systems: (i) monodispersed and completely homogeneous, (ii) aggregated viruses

without, and (iii) aggregated viruses with MR. Survival curves calculated from the

model compared well with experimental inactivation data.

There is evidence that virus inactivation rate coefficients may change over time

(Grant et al., 1993; Hurst et al., 1980; Parkinson and Huskey, 1971; Shah and

McCamish, 1972). When a virus population consists of different subpopulations

with different resistances against inactivation, the overall inactivation rate coefficients will decrease with time (Grant et al., 1993; Parkinson and Huskey, 1971).

The time dependence of the inactivation rate coefficient can be modeled either

explicitly as a function of time (Sim and Chrysikopoulos, 1996) or as a function

of residence time (Flury and Jury, 1999). In batch systems, the two approaches are

identical; however, in a flow system, time and residence-time-dependent processes

are different depending on the boundary conditions (Flury and Jury, 1999).





The effects of the air–water interface (AWI) on virus survival were first encountered by investigators studying the fate of airborne viruses in aerosols. It was

suggested that virus adsorption and inactivation at the AWI may be very similar

to those for individual proteins (Adams, 1948; Trouwborst et al., 1974). Shaklee

and Meltzer (1909) observed that shaking a pepsin solution in the presence of an

AWI resulted in degradation (i.e., loss of biological activity) of pepsin, whereas in

the absence of the AWI, i.e., when the bottles were completely filled with liquid,

no degradation of pepsin occurred. They also observed that bubbling air or CO2

through the solution results in denaturation of pepsin and that the denaturation rate

increased with decreasing pH of the solution. These early observations have been

confirmed and extended in many other studies (Table V).

The mechanisms of denaturation or inactivation is closely related to sorption

of viruses and proteins at the AWI. Studies have shown that proteins in solution

diffuse to the AWI and adsorb, and subsequently may undergo conformational

changes from their native state to a state of minimal interfacial tension (van del

Vegt et al., 1996). Such a conformational change causes unfolding of a protein’s

three-dimensional configuration and results in its denaturation (Adams, 1948;

Augenstine and Ray, 1957; Donaldson et al., 1980; Tronin et al., 1996). The unfolding of the protein molecular structure is an endothermic process (Zittle, 1953).

Whether or not denaturation of a protein occurs at an AWI is partially determined

by its structural characteristics, which are the cases for the distinction between

“hard” and “soft” proteins. Hard proteins are structurally stable, possibly due to

the presence of greater numbers of intrachain disulfide bonds, and generally resist

denaturation upon adsorption (Arai and Norde, 1990; Norde and Favier, 1992;

Tripp et al., 1995). Soft proteins are much less structurally stable and are more

likely to undergo conformational change and lose their biological activities (Tripp

et al., 1995). When proteins desorb from the interface, their native state generally

cannot be regained. Due to the significant change in physicochemical properties of

the molecule, protein sorption at the AWI has been considered to be an irreversible

process (MacRitchie, 1987; Neurath and Bull, 1938; Quinn and Dawson, 1970).

Although a single protein is much less complex, it is reasonable to consider a

virus as a large conglomerate of distinct proteins. The hydrophobic regions of a

virus protein partition to the gas phase at an AWI via conformational change

and may render the virus inactive (Trouwborst et al., 1974). However, studies

have shown that the extent of inactivation by the air–water interfacial forces is a

virus-dependent phenomenon. Trouwborst et al. (1974) demonstrated that during

shaking, the EMC virus was not inactivated at the AWI, while phages T3 and T5

were partially inactivated, and T1, MS-2, and Semliki Forest viruses were rapidly


Virus Inactivation and Protein Denaturation at the Gas–Liquid Interface


Pepsin, renin,


Egg albumin




Influenza A






T1, . . .,T7









P22H5 and



MS-2, φX174


Shaking results in first-order denaturation; no denaturation

in absence of interface; denaturation increases with

increasing acidity of solution; no denaturation in full

bottles; in absence of air–water interface; denaturation

not caused by oxidation; different degree of denaturation

for different proteins.

Vigorous shaking results in zero-order denaturation.

Protein unfold at interface and form monomolecular film;

stirring creates new interface area.

Spreading of protein at gas–liquid interface results in

denaturation of protein; proteins become insoluble.

Proteins form surface film; coagulum formed when

solution is shaken; rate of denaturation dependent on

size of bottle, shaking intensity but not concentration.

Inactivation by bubbling air laden with certain vapors

through virus solution.

Inactivation by shaking in buffered saline solution and by

bubbling gas through solution; inactivation increased as

pH reduced from 7 to 5.

Inactivation by shaking and bubbling air through solution;

inactivation dependent on pH; presence of gelatin

prevents inactivation.

Unfolding of macromolecules largely determined by

interfacial energy; sorption follows Langmuir isotherm.

Irreversible binding of proteins to interface.

EMC virus not affected, bacteriophages T3,T5 only little

affected, T1, MS-2, and Semliki Forest virus inactivated

by bubbling air or nitrogen gas through solution;

inactivation prevented by adding peptone and apolar

carboxylic acids; rate of inactivation dependent on salt

concentration, more sorption at higher salt concentration.

Inactivation of MS-2 at air–water interface.

Denaturation at interface depends on gas–liquid contact

time and surface regeneration rate; denaturation reduced

in presence of surfactants.

Denaturation at interface due to unfolding; insoluble

coagulum formed when solution is shaken.

Denaturation of T7 at the interface due to partial unfolding

of protein structure in aeration and shaking experiments;

P22H5 much more stable than T7.

Denaturation at the interface due to partial unfolding of

protein structure.

Inactivation in polypropylene bottles, but not in glass

bottles; inactivation occurs at the triple-phase interface

boundary air–water–solid.


Shaklee and Meltzer (1909)

Bull (1938)

Gorter (1938)

Langmuir and Waugh (1938)

Neurath and Bull (1938)

Grubb et al. (1947)

McLimas (1947)

Adams (1948)

James and Augenstein (1966)

Quinn and Dawson (1970)

Trouwborst et al. (1974)

Trouwborst and de Jong (1973)

Donaldson et al. (1980)

MacRitchie (1987)

ˇ sko (1992)

Bricelj and Siˇ

Tronin et al. (1996)

Thompson et al. (1998)

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IV. Protein Sorption and Denaturation

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