International
Tables for Crystallography Volume B Reciprocal space Edited by U. Shmueli © International Union of Crystallography 2010 
International Tables for Crystallography (2010). Vol. B, ch. 2.4, pp. 287293
Section 2.4.4. Isomorphous replacement and anomalous scattering in protein crystallography^{a}Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560 012, India, and ^{b}Raman Research Institute, Bangalore 560 080, India 
Perhaps the most spectacular applications of isomorphous replacement and anomalousscattering methods have been in the structure solution of large biological macromolecules, primarily proteins. Since its first successful application on myoglobin and haemoglobin, the isomorphous replacement method, which is often used in conjunction with the anomalousscattering method, has been employed in the solution of scores of proteins. The application of this method involves the preparation of protein heavyatom derivatives, i.e. the attachment of heavy atoms like mercury, uranium and lead, or chemical groups containing them, to protein crystals in a coherent manner without changing the conformation of the molecules and their crystal packing. This is only rarely possible in ordinary crystals as the molecules in them are closely packed. Protein crystals, however, contain large solvent regions and isomorphous derivatives can be prepared by replacing the disordered solvent molecules by heavyatomcontaining groups without disturbing the original arrangement of protein molecules.
For any given reflection, the structure factor of the native protein crystal , that of a heavyatom derivative , and the contribution of the heavy atoms in that derivative are related by the equationThe value of depends not only on the positional and thermal parameters of the heavy atoms, but also on their occupancy factors, because, at a given position, the heavy atom may not often be present in all the unit cells. For example, if the heavy atom is present at a given position in only half the unit cells in the crystal, then the occupancy factor of the site is said to be 0.5.
For the successful determination of the heavyatom parameters, as also for the subsequent phase determination, the data sets from the native and the derivative crystals should have the same relative scale. The different data sets should also have the same overall temperature factor. Different scaling procedures have been suggested (Blundell & Johnson, 1976) and, among them, the following procedure, based on Wilson's (1942) statistics, appears to be the most feasible in the early stages of structure analysis.
Assuming that the data from the native and the derivative crystals obey Wilson's statistics, we have, for any range of ,andwhere and refer to the atomic scattering factors of protein atoms and heavy atoms, respectively. and are the scale factors to be applied to the intensities from the native and the derivative crystals, respectively, and and the temperature factors of the respective structure factors. Normally one would be able to derive the absolute scale factor and the temperature factor for both the data sets from (2.4.4.2) and (2.4.4.3) using the well known Wilson plot. The data from protein crystals, however, do not follow Wilson's statistics as protein molecules contain highly nonrandom features. Therefore, in practice, it is difficult to fit a straight line through the points in a Wilson plot, thus rendering the parameters derived from it unreliable. (2.4.4.2) and (2.4.4.3) can, however, be used in a different way. From the two equations we obtainThe effects of structural nonrandomness in the crystals obviously cancel out in (2.4.4.4). When the lefthand side of (2.4.4.4) is plotted against , it is called a comparison or difference Wilson plot. Such plots yield the ratio between the scales of the derivative and the native data, and the additional temperature factor of the derivative data. Initially, the number and the occupancy factors of heavyatom sites are unknown, and are roughly estimated from intensity differences to evaluate . These estimates usually undergo considerable revision in the course of the determination and the refinement of heavyatom parameters.
At first, heavyatom positions are most often determined by Patterson syntheses of one type or another. Such syntheses are discussed in some detail elsewhere in Chapter 2.3 . They are therefore discussed here only briefly.
Equation (2.4.2.6) holds when the data are centric. is usually small compared to and , and the minus sign is then relevant on the lefthand side of (2.4.2.6). Thus the difference between the magnitudes of and , which can be obtained experimentally, normally gives a correct estimate of the magnitude of for most reflections. Then a Patterson synthesis with as coefficients corresponds to the distribution of vectors between heavy atoms, when the data are centric. But proteins are made up of Lamino acids and hence cannot crystallize in centrosymmetric space groups. However, many proteins crystallize in space groups with centrosymmetric projections. The centric data corresponding to these projections can then be used for determining heavyatom positions through a Patterson synthesis of the type outlined above.
The situation is more complex for threedimensional acentric data. It has been shown (Rossmann, 1961) thatwhen is small compared to and . Patterson synthesis with as coefficients would, therefore, give an approximation to the heavyatom vector distribution. An isomorphous difference Patterson synthesis of this type has been used extensively in protein crystallography to determine heavyatom positions. The properties of this synthesis have been extensively studied (Ramachandran & Srinivasan, 1970; Rossmann, 1960; Phillips, 1966; Dodson & Vijayan, 1971) and it has been shown that this Patterson synthesis would provide a good approximation to the heavyatom vector distribution even when is large compared to (Dodson & Vijayan, 1971).
As indicated earlier (see Section 2.4.3.1), heavy atoms are always anomalous scatterers, and the structure factors of any given reflection and its Friedel equivalent from a heavyatom derivative have unequal magnitudes. If these structure factors are denoted by and and the real component of the heavyatom contributions (including the real component of the dispersion correction) by , then it can be shown (Kartha & Parthasarathy, 1965) thatwhere . Here it has been assumed that all the anomalous scatterers are of the same type with atomic scattering factor and dispersioncorrection terms and . A Patterson synthesis with the lefthand side of (2.4.4.6) as coefficients would also yield the vector distribution corresponding to the heavyatom positions (Rossmann, 1961; Kartha & Parthasarathy, 1965). However, is a small difference between two large quantities and is liable to be in considerable error. Patterson syntheses of this type are therefore rarely used to determine heavyatom positions.
It is interesting to note (Kartha & Parthasarathy, 1965) that addition of (2.4.4.5) and (2.4.4.6) readily leads toThus, the magnitude of the heavyatom contribution can be estimated if intensities of Friedel equivalents have been measured from the derivative crystal. is then not readily available, but to a good approximationA different and more accurate expression for estimating from isomorphous and anomalous differences was derived by Matthews (1966). According to a still more accurate expression derived by Singh & Ramaseshan (1966),The lower estimate in (2.4.4.9) is relevant when and the upper estimate is relevant when . The lower and the upper estimates may be referred to as and , respectively. It can be readily shown (Dodson & Vijayan, 1971) that the lower estimate would represent the correct value of for a vast majority of reflections. Thus, a Patterson synthesis with as coefficients would yield the vector distribution of heavy atoms in the derivative. Such a synthesis would normally be superior to those with the lefthand sides of (2.4.4.5) and (2.4.4.6) as coefficients. However, when the level of heavyatom substitution is low, the anomalous differences are also low and susceptible to large percentage errors. In such a situation, a synthesis with as coefficients is likely to yield better results than that with as coefficients (Vijayan, 1981).
Direct methods employing different methodologies have also been used successfully for the determination of heavyatom positions (Navia & Sigler, 1974). These methods, developed primarily for the analysis of smaller structures, have not yet been successful in a priori analysis of protein structures. The very size of protein structures makes the probability relations used in these methods weak. In addition, data from protein crystals do not normally extend to high enough angles to permit resolution of individual atoms in the structure and the feasibility of using many of the currently popular directmethod procedures in such a situation has been a topic of much discussion. The heavy atoms in protein derivative crystals, however, are small in number and are normally situated far apart from one another. They are thus expected to be resolved even when lowresolution Xray data are used. In most applications, the magnitudes of the differences between and are formally considered as the `observed structure factors' of the heavyatom distribution and conventional directmethod procedures are then applied to them.
Once the heavyatom parameters in one or more derivatives have been determined, approximate protein phase angles, 's, can be derived using methods described later. These phase angles can then be readily used to determine the heavyatom parameters in a new derivative employing a difference Fourier synthesis with coefficientsSuch syntheses are also used to confirm and to improve upon the information on heavyatom parameters obtained through Patterson or direct methods. They are obviously very powerful when centric data corresponding to centrosymmetric projections are used. The synthesis yields satisfactory results even when the data are acentric although the difference Fourier technique becomes progressively less powerful as the level of heavyatom substitution increases (Dodson & Vijayan, 1971).
While the positional parameters of heavy atoms can be determined with a reasonable degree of confidence using the abovementioned methods, the corresponding temperature and occupancy factors cannot. Rough estimates of the latter are usually made from the strength and the size of appropriate peaks in difference syntheses. The estimated values are then refined, along with the positional parameters, using the techniques outlined below.
The leastsquares method with different types of minimization functions is used for refining the heavyatom parameters, including the occupancy factors. The most widely used method (Dickerson et al., 1961; Muirhead et al., 1967; Dickerson et al., 1968) involves the minimization of the functionwhere the summation is over all the reflections and w is the weight factor associated with each reflection. Here is the observed magnitude of the structure factor for the particular derivative and is the calculated structure factor. The latter obviously depends upon the protein phase angle , and the magnitude and the phase angle of which are in turn dependent on the heavyatom parameters. Let us assume that we have three derivatives A, B and C, and that we have already determined the heavyatom parameters , and . Then,A set of approximate protein phase angles is first calculated, employing methods described later, making use of the unrefined heavyatom parameters. These phase angles are used to construct for each derivative. (2.4.4.11) is then minimized, separately for each derivative, by varying for derivative A, for derivative B, and for derivative C. The refined values of , and are subsequently used to calculate a new set of protein phase angles. Alternate cycles of parameter refinement and phaseangle calculation are carried out until convergence is reached. The progress of refinement may be monitored by computing an R factor defined as (Kraut et al., 1962)
The above method has been successfully used for the refinement of heavyatom parameters in the Xray analysis of many proteins. However, it has one major drawback in that the refined parameters in one derivative are dependent on those in other derivatives through the calculation of protein phase angles. Therefore, it is important to ensure that the derivative, the heavyatom parameters of which are being refined, is omitted from the phaseangle calculation (Blow & Matthews, 1973). Even when this is done, serious problems might arise when different derivatives are related by common sites. In practice, the occupancy factors of the common sites tend to be overestimated compared to those of the others (Vijayan, 1981; Dodson & Vijayan, 1971). Yet another factor which affects the occupancy factors is the accuracy of the phase angles. The inclusion of poorly phased reflections tends to result in the underestimation of occupancy factors. It is therefore advisable to omit from refinement cycles reflections with figures of merit less than a minimum threshold value or to assign a weight proportional to the figure of merit (as defined later) to each term in the minimization function (Dodson & Vijayan, 1971; Blow & Matthews, 1973).
If anomalousscattering data from derivative crystals are available, the values of can be estimated using (2.4.4.7) or (2.4.4.9) and these can be used as the `observed' magnitudes of the heavyatom contributions for the refinement of heavyatom parameters, as has been done by many workers (Watenpaugh et al., 1975; Vijayan, 1981; Kartha, 1965). If (2.4.4.9) is used for estimating , the minimization function has the formThe progress of refinement may be monitored using a reliability index defined as
The major advantage of using 's in refinement is that the heavyatom parameters in each derivative can now be refined independently of all other derivatives. Care should, however, be taken to omit from calculations all reflections for which is likely to be the correct estimate of . This can be achieved in practice by excluding from leastsquares calculations all reflections for which has a value less than the maximum expected value of for the given derivative (Vijayan, 1981; Dodson & Vijayan, 1971).
A major problem associated with this refinement method is concerned with the effect of experimental errors on refined parameters. The values of are often comparable to the experimental errors associated with and . In such a situation, even random errors in and tend to increase systematically the observed difference between them (Dodson & Vijayan, 1971). In (2.4.4.7) and (2.4.4.9), this difference is multiplied by k or , a quantity much greater than unity, and then squared. This could lead to the systematic overestimation of 's and the consequent overestimation of occupancy factors. The situation can be improved by employing empirical values of k, evaluated using the relation (Kartha & Parthasarathy, 1965; Matthews, 1966)for estimating or by judiciously choosing the weighting factors in (2.4.4.14) (Dodson & Vijayan, 1971). The use of a modified form of , arrived at through statistical considerations, along with appropriate weighting factors, has also been advocated (Dodson et al., 1975).
When the data are centric, (2.4.4.9) reduces toHere, again, the lower estimate most often corresponds to the correct value of . (2.4.4.17) does not involve which, as indicated earlier, is prone to substantial error. Therefore, 's estimated using centric data are more reliable than those estimated using acentric data. Consequently, centric reflections, when available, are extensively used for the refinement of heavyatom parameters. It may also be noted that in conditions under which corresponds to the correct estimate of , minimization functions (2.4.4.11) and (2.4.4.14) are identical for centric data.
A Patterson function correlation method with a minimization function of the typewas among the earliest procedures suggested for heavyatomparameter refinement (Rossmann, 1960). This procedure would obviously work well when centric reflections are used. A modified version of this procedure, in which the origins of the Patterson functions are removed from the correlation, and centric and acentric data are treated separately, has been proposed (Terwilliger & Eisenberg, 1983).
As shown in Section 2.4.2.3, ideally, protein phase angles can be evaluated if two isomorphous heavyatom derivatives are available. However, in practice, conditions are far from ideal on account of several factors such as imperfect isomorphism, errors in the estimation of heavyatom parameters, and the experimental errors in the measurement of intensity from the native and the derivative crystals. It is therefore desirable to use as many derivatives as are available for phase determination. When isomorphism is imperfect and errors exist in data and heavyatom parameters, all the circles in a Harker diagram would not intersect at a single point; instead, there would be a distribution of intersections, such as that illustrated in Fig. 2.4.4.1. Consequently, a unique solution for the phase angle cannot be deduced.
The statistical procedure for computing protein phase angles using multiple isomorphous replacement (MIR) was derived by Blow & Crick (1959). In their treatment, Blow and Crick assume, for mathematical convenience, that all errors, including those arising from imperfect isomorphism, could be considered as residing in the magnitudes of the derivative structure factors only. They further assume that these errors could be described by a Gaussian distribution. With these simplifying assumptions, the statistical procedure for phase determination could be derived in the following manner.
Consider the vector diagram, shown in Fig. 2.4.4.2, for a reflection from the ith derivative for an arbitrary value for the protein phase angle. Then,If corresponds to the true protein phase angle , then coincides with . The amount by which differs from , namely,is a measure of the departure of from . is called the lack of closure. The probability for being the correct protein phase angle could now be defined aswhere is the normalization constant and is the estimated r.m.s. error. The methods for estimating will be outlined later. When several derivatives are used for phase determination, the total probability of the phase angle being the protein phase angle would bewhere the summation is over all the derivatives. A typical distribution of plotted around a circle of unit radius is shown in Fig. 2.4.4.3. The phase angle corresponding to the highest value of would obviously be the most probable protein phase, , of the given reflection. The most probable electrondensity distribution is obtained if each is associated with the corresponding in a Fourier synthesis.

Vector diagram indicating the calculated structure factor, , of the ith heavyatom derivative for an arbitrary value for the phase angle of the structure factor of the native protein. 

The probability distribution of the protein phase angle. The point P is the centroid of the distribution. 
Blow and Crick suggested a different way of using the probability distribution. In Fig. 2.4.4.3, the centroid of the probability distribution is denoted by P. The polar coordinates of P are m and , where m, a fractional positive number with a maximum value of unity, and are referred to as the `figure of merit' and the `best phase', respectively. One can then compute a `best Fourier' with coefficientsThe best Fourier is expected to provide an electrondensity distribution with the lowest r.m.s. error. The figure of merit and the best phase are usually calculated using the equationswhere are calculated, say, at intervals (Dickerson et al., 1961). The figure of merit is statistically interpreted as the cosine of the expected error in the calculated phase angle and it is obviously a measure of the precision of phase determination. In general, m is high when and are close to each other and low when they are far apart.
When anomalousscattering data have been collected from derivative crystals, and can be formally treated as arising from two independent derivatives. The corresponding Harker diagram is shown in Fig. 2.4.4.4. Thus, in principle, protein phase angles can be determined using a single derivative when anomalousscattering effects are also made use of. It is interesting to note that the information obtained from isomorphous differences, , and that obtained from anomalous differences, , are complementary. The isomorphous difference for any given reflection is a maximum when and are parallel or antiparallel. The anomalous difference is then zero, if all the anomalous scatterers are of the same type, and is determined uniquely on the basis of the isomorphous difference. The isomorphous difference decreases and the anomalous difference increases as the inclination between and increases. The isomorphous difference tends to be small and the anomalous difference tends to have the maximum possible value when and are perpendicular to each other. The anomalous difference then has the predominant influence in determining the phase angle.
Although isomorphous and anomalous differences have a complementary role in phase determination, their magnitudes are obviously unequal. Therefore, when and are treated as arising from two derivatives, the effect of anomalous differences on phase determination would be only marginal as, for any given reflection, is usually much smaller than . However, the magnitude of the error in the anomalous difference would normally be much smaller than that in the corresponding isomorphous difference. Firstly, the former is obviously free from the effects of imperfect isomorphism. Secondly, and are expected to have the same systematic errors as they are measured from the same crystal. These errors are eliminated in the difference between the two quantities. Therefore, as pointed out by North (1965), the r.m.s. error used for anomalous differences should be much smaller than that used for isomorphous differences. Denoting the r.m.s. error in anomalous differences by E′, the new expression for the probability distribution of protein phase angle may be written aswhereandHere is the phase angle of [see (2.4.4.19) and Fig. 2.4.4.2]. is the anomalous difference calculated for the assumed protein phase angle . may be taken as the average of and for calculating using (2.4.4.20).
Perhaps the most important parameters that control the reliability of phase evaluation using the Blow and Crick formulation are the isomorphous r.m.s. error and the anomalous r.m.s. error . For a given derivative, the sharpness of the peak in the phase probability distribution obviously depends upon the value of E and that of E′ when anomalousscattering data have also been used. When several derivatives are used, an overall underestimation of r.m.s. errors leads to artifically sharper peaks, the movement of towards , and deceptively high figures of merit. Opposite effects result when E's are overestimated. Underestimation or overestimation of the r.m.s. error in the data from a particular derivative leads to distortions in the relative contribution of that derivative to the overall phase probability distributions. It is therefore important that the r.m.s. error in each derivative is correctly estimated.
Centric reflections, when present, obviously provide the best means for evaluating E using the expressionAs suggested by Blow & Crick (1959), values of E thus estimated can be used for acentric reflections as well. Once a set of approximate protein phase angles is available, can be calculated as the r.m.s. lack of closure corresponding to [i.e. in (2.4.4.20)] (Kartha, 1976). can be similarly evaluated as the r.m.s. difference between the observed anomalous difference and the anomalous difference calculated for [see (2.4.4.24)]. Normally, the value of is about a third of that of (North, 1965).
A different method, outlined below, can also be used to evaluate E and E′ when anomalous scattering is present (Vijayan, 1981; Adams, 1968). From Fig. 2.4.2.2, we haveandwhere . Using arguments similar to those used in deriving (2.4.3.5), we obtainIf is considered to be equal to , we obtain from (2.4.4.28)We obtain what may be called if the magnitude of is determined from (2.4.4.26) and the quadrant from (2.4.4.28). Similarly, we obtain if the magnitude of is determined from (2.4.4.28) and the quadrant from (2.4.4.26). Ideally, and should have the same value and the difference between them is a measure of the errors in the data. obtained from (2.4.4.27) using may be considered as its calculated value . Then, assuming all errors to lie in , we may writeSimilarly, the calculated anomalous difference may be evaluated from (2.4.4.29) using . ThenIf all errors are assumed to reside in , E can be evaluated in yet another way using the expression
2.4.4.7. Suggested modifications to Blow and Crick formulation and the inclusion of phase information from other sources
Modifications to the Blow and Crick procedure of phase evaluation have been suggested by several workers, although none represent a fundamental departure from the essential features of their formulation. In one of the modifications (Cullis et al., 1961a; Ashida, 1976), all 's are assumed to be the same, but the lackofclosure error for the ith derivative is measured as the distance from the mean of all intersections between phase circles to the point of intersection of the phase circle of that derivative with the phase circle of the native protein. Alternatively, individual values of are retained, but the lack of closure is measured from the weighted mean of all intersections (Ashida, 1976). This is obviously designed to undo the effects of the unduly high weight given to in the Blow and Crick formulation. In another modification (Raiz & Andreeva, 1970; Einstein, 1977), suggested for the same purpose, the and circles are treated as circular bands, the width of each band being related to the error in the appropriate structure factor. A comprehensive set of modifications suggested by Green (1979) treats different types of errors separately. In particular, errors arising from imperfect isomorphism are treated in a comprehensive manner.
Although the isomorphous replacement method still remains the method of choice for the ab initio determination of protein structures, additional items of phase information from other sources are increasingly being used to replace, supplement, or extend the information obtained through the application of the isomorphous replacement. Methods have been developed for the routine refinement of protein structures (Watenpaugh et al., 1973; Huber et al., 1974; Sussman et al., 1977; Jack & Levitt, 1978; Isaacs & Agarwal, 1978; Hendrickson & Konnert, 1980) and they provide a rich source of phase information. However, the nature of the problem and the inherent limitations of the Fourier technique are such that the possibility of refinement yielding misleading results exists (Vijayan, 1980a,b). It is therefore sometimes desirable to combine the phases obtained during refinement with the original isomorphous replacement phases. The other sources of phase information include molecular replacement (see Chapter 2.3 ), direct methods (Hendrickson & Karle, 1973; Sayre, 1974; de Rango et al., 1975; see also Chapter 2.2 ) and different types of electrondensity modifications (Hoppe & Gassmann, 1968; Collins, 1975; Schevitz et al., 1981; Bhat & Blow, 1982; Agard & Stroud, 1982; Cannillo et al., 1983; Raghavan & Tulinsky, 1979; Wang, 1985).
The problem of combining isomorphous replacement phases with those obtained by other methods was first addressed by Rossmann & Blow (1961). The problem was subsequently examined by Hendrickson & Lattman (1970) and their method, which involves a modification of the Blow and Crick formulation, is perhaps the most widely used for combining phase information from different sources.
The Blow and Crick procedure is based on an assumed Gaussian `lumped' error in which leads to a lack of closure, , in defined by (2.4.4.20). Hendrickson and Lattman make an equally legitimate assumption that the lumped error, again assumed to be Gaussian, is associated with . Then, as in (2.4.4.20), we havewhere is the lack of closure associated with for an assumed protein phase angle α. Then the probability for α being the correct phase angle can be expressed aswhere is the r.m.s. error in , which can be evaluated using methods similar to those employed for evaluating . Hendrickson and Lattman have shown that the exponent in the probability expression (2.4.4.34) can be readily expressed as a linear combination of five terms in the following manner.where , , , and are constants dependent on and . Thus, five constants are enough to store the complete probability distribution of any reflection. Expressions for the five constants have been derived for phase information from anomalous scattering, tangent formula, partial structure and molecular replacement. The combination of the phase information from all sources can then be achieved by simply taking the total value of each constant. Thus, the total probability of the protein phase angle being α is given bywhere etc. are the constants appropriate for the sth source and N is the normalization constant.
It is often useful to have a Fourier representation of only the anomalous scatterers in a protein. The imaginary component of the electrondensity distribution obviously provides such a representation. When the structure is known and and have been experimentally determined, Chacko & Srinivasan (1970) have shown that this representation is obtained in a Fourier synthesis with as coefficients, where , whose magnitude is , is the complex conjugate of . They also indicated a method for calculating the phase angles of and . It has been shown (Hendrickson & Sheriff, 1987) that the Bijvoetdifference Fourier synthesis proposed earlier by Kraut (1968) is an approximation of the true imaginary component of the electron density. The imaginary synthesis can be useful in identifying minor anomalousscattering centres when the major centres are known and also in providing an independent check on the locations of anomalous scatterers and in distinguishing between anomalous scatterers with nearly equal atomic numbers (Sheriff & Hendrickson, 1987; Kitagawa et al., 1987).
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