Automated NOESY Interpretation with Ambiguous Distance ......Automated NOESY Interpretation with Ambiguous Distance Restraints: The Refined NMR Solution Structure of the Pleckstrin

J. Mol. Biol. (1997) 269, 408±422

Automated NOESY Interpretation with AmbiguousDistance Restraints: The Refined NMR SolutionStructure of the Pleckstrin Homology Domainfrom bbb-Spectrin

Michael Nilges*, Maria J. Macias, SeÂan I O'Donoghueand Hartmut Oschkinat

European Molecular BiologyLaboratory, Meyerhofstr. 1D-69117, Heidelberg, FRG

Abbreviations used: ADR, ambrestraint; ISPA, isolated spin pairnuclear magnetic resonance; NOEeffect; rms, root-mean-square; SAvdW, van der Waals; PH, pleckst

0022±2836/97/230408±15 $25.00/0/m

We have used a novel, largely automated, calculation method to re®nethe NMR solution structure of the pleckstrin homology domain of b-spec-trin. The method is called ARIA for Ambiguous Restraints for IterativeAssignment. The starting point for ARIA is an almost complete assign-ment of the proton chemical shifts, and a list of partially assigned NOEs,mostly sequential and secondary structure NOEs. The restraint list isthen augmented by automatically interpreting peak lists generated byautomated peak-picking. The central task of ARIA is the assignment ofambiguous NOEs during the structure calculation using a combination ofambiguous distance restraints and an iterative assignment strategy. Inaddition, ARIA calibrates ambiguous NOEs to derive distance restraints,merges overlapping data sets to remove duplicate information, and usesempirical rules to identify erroneous peaks. While the distance restraintsfor the structure calculations were exclusively extracted from homonuc-lear 2D experiments, ARIA is especially suited for the analysis of multidi-mensional spectra. Applied to the pleckstrin homology domain, ARIAgenerated structures of good quality, and of suf®ciently high accuracy tosolve the X-ray crystal structure of the same domain by molecular repla-cement. The comparison of the free NMR solution structure to the X-raystructure, which is complexed to D-myo-inositol-1,4,5-triphosphate, showsthat the ligand primarily induces a disorder-order transition in the bind-ing loops, which are disordered in the NMR ensemble but well orderedin the crystal. The structural core of the protein is unaffected, as evi-denced by a backbone root-mean-square difference between the averageNMR coordinates and the X-ray crystal structure for the secondary struc-ture elements of less than 0.6 AÊ .

# 1997 Academic Press Limited

Keywords: nuclear magnetic resonance; nuclear Overhauser effect;simulated annealing; three-dimensional solution structure; automatedassignment
*Corresponding author
Introduction

The pleckstrin homology (PH) domain hasemerged as a ubiquitous protein domain with aroÃ le in intra-cellular signalling (Musacchio et al.,1993). The three-dimensional structures of several

iguous distanceapproximation; NMR,, nuclear Overhauser, simulated annealing;rin homology.

b971044

PH domains have been reported (Downing et al.,1994; Ferguson et al., 1994, 1995; Fushman et al.,1995; Macias et al., 1994; Timm et al., 1994;Yoon et al., 1994; Zhang et al., 1995). The structureof the conserved domain consists of a seven-stranded antiparallel b-sheet forming an orthog-onal sandwich, with a C-terminal a-helix thatblocks one end of the sandwich. While it is still notclear if there is a general function for the PHdomain, binding to phosphatidylinositol-4,5-bipho-sphate (Ptd-Ins(4,5)P2) or D-myo-inositol-1,4,5-tri-phosphate (Ins(1,4,5)P3) molecules (Garcia et al.,

# 1997 Academic Press Limited

Figure 1. Overview over the operations performed byARIA.

Re®nement of PH Domain NMR Solution Structure 409

1995; Harlan et al., 1994; HyvoÈnen et al., 1995;Ferguson et al., 1995) has been reported for severalPH domains. Only the mouse b-spectrin PHdomain has been studied in detail both in thebound and free forms. A high-resolution structureat near-physiological conditions seemed necessaryto study the effects of ligand binding in more de-tail. Here, we present the re®ned NMR structure ofmouse b-spectrin, and describe in detail a newiterative spectra assignment and calculation strat-egy.

The two-dimensional homonuclear NOE spectraused for the determination of the three-dimen-sional structure of the mouse b-spectrin PHdomain contained a large number of ambiguouscrosspeaks, which made their assignment a chal-lenging task. Central to the re®nement strategypresented here is therefore the use of ambiguousdistance restraints (ADRs) to incorporate the infor-mation from ambiguous crosspeaks. ADRs havebeen used in deriving the fold of the domain (Ma-cias et al., 1994). Here, we show that a combinationof ADRs and an iterative interpretation strategycan be used to interpret NOE spectra in a largelyautomated fashion, starting from automaticallygenerated peak lists. The resulting structures are ofgood quality and accuracy. We document the re-®nement progress with a number of quality par-ameters; namely, the quality indices reported bythe programs PROSA (Sippl, 1993), WhatIf (Vriend& Sander, 1993) and PROCHECK (Morris et al.,1992).

Calculation Strategy

Overview of the assignment method

Many NOE contacts can be unambiguouslyassigned manually in the course of resonance as-signment, such as intra-residue and sequentialNOEs, those characteristic for secondary structure,and some easily identi®able long-range contacts.These NOEs are often suf®cient to de®ne at leastsome aspects of the overall fold of the molecule.The main aim of our new calculation strategy is toextract fully automatically the information fromthe available NOE spectra necessary to de®ne a re-®ned structure. Two main tasks have to be per-formed: ®rst, artefacts have to be recognized andremoved from the data lists; second, the usefulNOE contacts that are ambiguous have to be as-signed. A further task is the merging of data fromdifferent sources (i.e. the manually assigned list,and several spectra taken under different con-ditions).

Here, we present a fully automated, iterativemethod that performs these tasks (ARIA, Ambigu-ous Restraints for Iterative Assignment). It consistsof a series of routines that perform partial assign-ment, calibration, violation analysis and merging,together with scripts for the organization of theiterative procedure. The routines are interfaced to

X-PLOR 3.1 (BruÈ nger, 1992). The calculations per-formed by ARIA are outlined in Figure 1.

To start the calculation, we divide the data intotwo parts. (1) The ®rst part comprises the list ofNOEs that are the result of manual assignment.This list can contain ambiguous NOEs to beassigned by ARIA (i.e. a peak can be clearly ident-i®ed but not unambiguously assigned), but it mustnot contain any errors. (2) The second part containspeak lists automatically generated from the rawNOE spectra using a standard peak-picking algor-ithm. ARIA assigns peaks on this list, calibratesthem to obtain distance restraints, and tries toidentify errors.

In the ®rst round of calculations (iteration zero),an initial ensemble of structures is calculated basedon the manually prepared list. Any ambiguitiesin this list are treated with ambiguous distancerestraints (ADRs; Nilges, 1995). A subset of thisensemble is selected for use in the iterative assign-ment.

Each following iteration begins with orderingthe ensemble from the previous iteration withrespect to total energy, and selecting the structureswith lowest total energy as the basis for interpret-ing the spectra. The spectra are ®rst calibrated,using average distances calculated from the chosenstructures as reference. For every NOE whosechemical shift coordinates correspond to protonresonances, an ADR is added to the list. All the

410 Re®nement of PH Domain NMR Solution Structure

restraints extracted from the spectra in this wayare analysed for restraint violations in the chosenstructures. Any restraint that is systematically vio-lated is removed from the list. The restraints arethen partially assigned, that is to say, assignmentpossibilities that correspond to large distances inthe chosen structures are removed. This procedureis applied to each spectrum separately (e.g. takenat different mixing times, temperatures, etc.), andthe restraint lists derived from the different spectraare merged with the initial restraint list to avoidduplication of information. A new set of structuresis calculated. The whole procedure is iterated untilstructures and data sets do not change signi®-cantly. The ®nal result of the procedure consists ofcalculated structures, assigned distance restraints,distance restraints that have been assigned butrejected because they are considered as artefacts bythe method, and peaks that are rejected because nocorresponding chemical shifts exist. Manualinspection of the lists of rejected restraints andpeaks is especially useful in the location of errors.The ®nal list of restraints is also inspected andmodi®ed by hand if necessary, and a set of ®nalstructures is calculated.

Automated partial NOE assignment

In the isolated spin pair approximation (ISPA),an ambiguous NOE corresponds to a summed dis-tance D (Nilges, 1995):

DF1;F2 �� XN�F1;F2�

i�1

Dÿ6i

�ÿ1=6

�1�

where k runs through all N(F1,F2) contributions toa crosspeak at frequencies F1 and F2, and Dk is thedistance between two protons corresponding to thecontribution k. This distance can be calculated fromthe coordinates of a model structure. The structurecalculation or re®nement can proceed in a waydirectly analogous to re®nement with standarddistance restraints, by restraining D by means ofan appropriate target function to lower and upperbounds L and U derived from the size of the NOEcrosspeak:

L � D � U �2�Equation (1) runs over all contributions, even thosecorresponding to large distances, which are there-fore vanishingly small. Once an approximate struc-ture of the molecule is known, the restraints can bepartially assigned by discarding the contributionsto the crosspeak that correspond to large distancesin the structures. This increases the ef®ciency ofthe protocols in two ways: ®rstly, the calculation ofthe restraint energy is considerably faster, sincefewer contributions to the summed distance haveto be evaluated; secondly, the convergence rate ofthe protocols increases with the number of unam-biguously assigned restraints. Fewer structures

have to be calculated to obtain an ensemble of ®nalstructures that satisfy the data. We will show else-where that the iterative assignment scheme usingADRs has a signi®cantly larger radius of conver-gence than the use of ADRs in a non-iterative pro-cedure (Nilges, 1995).

We could have based the partial assignment ofa peak on a distance cutoff criterion: contri-butions are discarded if the corresponding dis-tances are larger than the chosen cutoff in allconverged structures. Instead, we preferred touse a criterion that takes the relative size of thecontributions of different assignment possibilitiesto the crosspeak into account. This is estimatedas follows. For each contribution k to the ambigu-ous NOE we determine the minimum distanceDk

min in the ensemble of converged structures.The contribution Ck of assignment k to the cross-peak is then estimated as:

Ck � Dkmin

ÿ6PN�F1;F2�i Di

min

ÿ6�3�

The Ck are then sorted according to size, and theNp largest contributions are chosen such that:

XNp

i

Ci > p �4�

where p is a parameter set by the user. In thepresent structure determination we have variedp from 0.999 for the ®rst iteration to 0.80 in thelast. If the shorter of two distances is 2.5 AÊ , avalue for p of 0.999 would exclude a seconddistance of 7.9 AÊ , a value of 0.95, a distance of4.1 AÊ , and a value of 0.8, a distance of 3.3 AÊ ; ifthe shorter distance is 4.0 AÊ , possibilities withminimum distances of 12.6, 6.6 and 5.2 AÊ , re-spectively, would be excluded. If all but onecontribution can be excluded in this way, theNOE is assigned in the usual meaning of theword.

For simplicity, we do not distinguish betweenambiguities that arise from several contributions toan NOE present already in one structure of the en-semble, and several different possibilities presentin different members of the ensemble.

Calibration and error bounds

Distances were derived from the NOE volumesusing the isolated spin pair approximation (ISPA),Dÿ6

ij � A NOEij, with a calibration factor A. Differ-ent factors were used depending on the type ofprotons involved. Protons were classed into ®vegroups: (1) exchangeable protons, (2) aromatic pro-tons, (3) aliphatic protons, (4) a-protons and (5)methyl protons. In order to calibrate all NOEs be-tween these ®ve groups of protons, 5(5 � 1)/2 � 15calibration factors would be necessary. We have re-duced the number of independent calibration fac-


tors by requiring the following relation betweencalibration factors for different proton classes Iand J:

AIJ ��AIIAJJ

p �5�This relation can be seen to be correct if, forexample, the calibration factor depends only onthe population of the hydrogen atoms (e.g. 90%for amide protons in 90% H2O).

Since spin diffusion and internal dynamics affectNOEs with ®xed reference distances differentlyfrom other NOEs, we have used averages over alldistances < 3.5 AÊ from calculated structures as re-ference. Distances to methyl and equivalent aro-matic protons were calculated with the rÿ6 sum.This is equivalent to dividing the intensity invol-ving one of the groups by the number of atomsand using the rÿ6 average. For a detailed discus-sion of different averaging methods for equivalentprotons, see Fletcher et al. (1996).

In order to apply the calibration factors to anambiguous NOE, we have used a weighted aver-age:

Dÿ6 �

XN

i

CiAiNOE �6�

with relative peak contributions Ci estimated as inequation (3), and Ai set to the calibration factor AIJ

appropriate for the contribution i.Lower and upper bounds were than set to

L � D ÿ 0.125D2, U � D � 0.125D2 for a distanceestimate D derived from the NOE, resulting in an0.5 AÊ error estimate from a distance of 2 AÊ and 2 AÊ

for a distance of 4 AÊ . These fairly generous errorestimates seemed necessary for the 80 ms data set,where we expected signi®cant spin diffusioneffects. For the 30 ms data set we have used atighter error estimate; L � D ÿ 0.2D,U � D � 0.2D.

Restraint selection

The major obstacle for ARIA is the presence ofnoise peaks in the peak lists. There are true arte-facts, resulting from spectral processing, incom-plete water suppression, or impurities in thesample. There may be peaks due to strong coup-ling with a resulting splitting of the peaks, andpeaks from unassigned proton resonances. Further-more, there are errors in peak position, due to theimprecision of automated peak-picking algorithms,especially in crowded regions of the spectrum. Theerrors often exceed the frequency window set forthe automated NOE assignment.

Many of these artefacts will appear at positionsin the spectrum where they do not correspond to apossible chemical shift pair. These peaks are listedby the program for manual inspection, but other-wise ignored in the calculation. The list is es-pecially valuable in the beginning of a structuredetermination project for checking the chemicalshift assignments. However, many artefacts or

incorrectly positioned peaks will have possibleassignments, and will result in an incorrect (ambig-uous) distance restraint on the list.

A last category of errors leads to incorrect dis-tance estimates. Severe overlap leads to an incor-rect estimation of the peak volume, and spindiffusion and dynamic effects lead to a signi®cantdeviation from the Dÿ6 dependence of the peakvolume. In distance geometry calculations, theseerrors are taken into account by appropriate errorbounds and a ``¯at-bottom-harmonic-wall'' poten-tial.

Our automated method searches iteratively thespectra for crosspeaks that are consistent with thestructures from a previous iteration. A noise peakwill, in general, not be consistent with a three-dimensional structure. This reasoning is implicitlypart of any iterative scheme, be it manual or auto-matic (GuÈ ntert et al., 1993; Meadows et al., 1994;Mumenthaler & Braun, 1995), unless a clean peaklist can be assumed. The difference between ourapproach and that of others (GuÈ ntert et al., 1993;Meadows et al., 1994; Mumenthaler & Braun, 1995)is that the selection of a restraint and its assign-ment are separated, through the use of ADRs.

In each re®nement iteration, a list of ADRs isgenerated from the peak list by the distance cali-bration described above. Restraints that are sys-tematically violated in the converged structures ofthe previous ensemble are removed from the list.In the same spirit as Mumenthaler & Braun (1995)we call a violation systematic if it exceeds a certainthreshold TV in NV converged structures. TV is var-ied from iteration to iteration (see Table 1), withlarger values in the ®rst iteration to very smallvalues in the ®nal iteration. NV is generally set to50% of the converged structures. As convergedstructures we use simply the third with the lowesttotal energy.

The error bounds play an important roÃ le in dis-tinguishing noise from real data. They should beset large enough to account for most of the effectsdescribed above. If they are set too large, however,information content is lost, which has several con-sequences: ®rst, the precision of the structure willdecrease; second, the NOE assignment through theADR will contain more errors (Nilges, 1995), andthird, the distinction between noise and data is lesswell de®ned.

We have tested several different error estimateschemes (data not shown). In general, tighter errorestimates lead to fewer NOE peaks being inter-preted, and consequently to less well determinedstructures. Looser error estimates seemed to reducethe information content of the NOE-derived re-straint more than necessary, resulting again in lesswell determined structures, and the interpretationof noise peaks as real data.

Peaks on the manually selected list are not partof this selection scheme. Systematic violations onthis list are manually inspected and often indicateerrors associated with the ``hard'' restraints or thechemical shift assignments of protons.


We emphasize that the criterion we use does notallow a distinction between artefacts and restraintsfor which the error in the distance estimate exceedsthe set error bounds. Inspection of the list of re-jected restraints is therefore necessary to decide ifcalibration and error bounds are appropriate.

Merging of data sets

The experimental data derived from the NOEspectra are usually present in several partiallyoverlapping lists. For the mouse b-spectrin PHdomain, we used peak lists derived from two NOEspectra at different mixing times, and one partiallyassigned list of distance restraints (see Results).Additionally, peaks were picked on both sides ofthe diagonal in some regions of the spectra, lead-ing to further duplication. All lists were read intoX-PLOR, calibrated and partially assigned separ-ately. If the partial assignment (see equation (4))for several peaks was identical, only the restraintwith the narrowest error bounds was kept. Inthis way, a qualitative restraint on the initialpeak list was usually replaced by a calibratedpeak from the 30 ms or 80 ms NOE spectra, anddistance restraints derived from the 30 ms spec-trum with tighter error bounds are used in placeof those from the 80 ms spectrum if both can besatis®ed.

Results

The data

The sample, a construct of 106 amino acid resi-dues comprising the mouse b-spectrin PH domain,was stable in a range of pH values between 4 and7, and temperatures between 290 and 315 K. The

Table 1. Assignment statistics

MAN 80 msItnb pc Namb

d Nunambe Namb Nunamb

1 0.999 196 372 1534 2202 0.999 180 388 1475 2283 0.99 109 459 1160 5354 0.98 91 477 1010 6775 0.96 73 495 882 8156 0.93 60 508 725 9607 0.90 50 518 610 10638 0.80 35 533 404 1246w 0.80 35 533 404 1246w2 0.80 36 532 417 1235f 0.80 33 535 415 1228wf 0.80 33 535 415 1228

a Dataset merged from MAN, 80 ms and 30 ms.b Iteration number. Iteration w is a re®nement of structures from

water, f is the ®nal calculation, and wf is the re®nement of the ®nalc Assignment parameter; see the text.d Number of ambiguous crosspeaks.e Number of unambiguously assigned crosspeaks.f Violation threshold. Restraints were removed from the data if th

proton NMR signals were very well dispersed andresolved, mainly due to the large number of aro-matic residues in the sequence. Therefore, most ofthe assignment of the spin system resonances, thesequential connectivities, and the identi®cation ofthe secondary structure elements was possibleusing 2D experiments. The ambiguities observed insome of the sequential crosspeaks or involvingsome of the assignments of secondary structure el-ements were resolved by analysing the appropriateplanes in the 3D TOCSY-NOESY spectrum. Struc-tural restraints were derived from two NOE spec-tra at 30 and 80 ms.

In all, 563 crosspeaks were identi®ed, quanti-®ed and assigned manually. Of these, 295 wereinitially assigned as sequential, 268 as medium-range and long-range. For the calculations, the re-straints were assumed ambiguous if two chemicalshifts differed by less than 0.005 ppm. Of these``de-assigned'' restraints, 83 were sequential, 17medium-range, 92 long-range, and the restambiguous. This list was used throughout thecalculation, since it contained valuable distanceinformation not present on the automaticallypicked lists (e.g. peak shoulders).

Additional distance restraints were used for thehydrogen bonds. A restraint was added for eachslowly exchanging amide proton. Several possibleacceptors were used for most known hydrogenbond donors; namely, the carbonyl oxygen atom ofthe residue that would be the acceptor in regularsecondary structure, and the carbonyl oxygenatoms of one residue directly preceding and oneresidue following this residue at the C-terminaland N-terminal turn of a-helices, and of two resi-dues in b-sheet regions. In addition, we have in-cluded side-chain oxygen atoms as acceptors forthe hydrogen bonds in turns and at the beginningof the C-terminal a-helix, and at the N terminus ofthe domain.

30 ms Totala

vtolf Namb Nunamb vtol Namb Nunamb

1.00 501 70 0.25 1998 5050.25 554 84 0.25 1962 5200.25 429 199 0.25 1438 7880.25 389 262 0.25 1235 8990.25 338 328 0.25 1060 10100.25 274 407 0.25 843 11400.00 216 438 0.00 703 12040.00 142 509 0.00 462 13520.00 142 509 0.00 462 13520.00 149 514 0.00 479 13510.00 149 509 0.00 486 13280.00 149 509 0.00 486 1328

iteration 8 in explicit water, w2 is a second re®nement in explicitensemble in explicit water.

ey systematically violated the bounds by more than vtol.

Figure 2. Histograms of the number of possible assign-ments for the restraints in the merged data sets, andcontact plots of the merged data sets. The squares abovethe diagonal indicate possible but ambiguous contacts,the squares under the diagonal indicate unambiguouslyassigned NOE contacts. a, Iteration 0; b, iteration 1; c,last iteration.


Summary of performed calculations

With the manually assigned data set and the hy-drogen bonds, 50 initial structures were calculated(iteration 0). Of these, the 20 with the lowest en-ergy were selected for the re®nement/assignmentiteration. In each iteration, the seven structureswith lowest energy were chosen to select peaksand assign the spectra. After eight iterations withthe standard PARALLHDG force-®eld, two iter-ations were performed in a shell of solvent withthe PARALLHDG/OPLS hybrid force-®eld (seeMaterials and Methods). The data set after thesetwo water iterations was taken as the ®nal dataset. This data set was checked manually for errors,and then used to calculate 200 ®nal structures. The50 structures with lowest energy were re®ned in ashell of solvent and analysed.

Iterative interpretation of the NOE spectra

Three data sets were used for the calculation ofthe structures. The ®rst data set, called MAN inTable 1, was derived from a manual assignment(see above). The second and the third were derivedfrom automatically peak-picked lists from the NOEspectra with 30 and 80 ms mixing times. The mostobvious artefacts were removed from the peaklists. These data sets are called 30 ms and 80 ms,respectively. In each iteration, the peaks were con-verted into ADRs as described in Materials andMethods and calibrated. Iterative partial assign-ment was used for all three data sets, peak selec-tion only for 30 ms and 80 ms.

Table 1 shows the assignment record. Listed arethe amount of assigned and ambiguous NOEs foreach spectrum, together with the parameters usedfor selection and assignment. The ambiguity of themerged data set in the iterations 0, 1 and ®nal isshown in the histograms and contact plots(Figure 2).

The ®nal data set contained 1728 restraints, ofwhich 1328 were unambiguously assigned, 324had two, 66 had three, 22 had four, seven had ®ve,and one had six assignment possibilities. Of these605 were intra-residue, 417 sequential, 175 med-ium-range and 531 long-range, where ambiguousrestraints were added with weights from equation(3). The distribution of medium-range and long-range NOEs is shown in Figure 6a.

The structures in each iteration

Figure 3 shows the seven best structures in eachof iterations 0, 1 and ®nal. The quality of the struc-tures in each iteration was followed with respect toa number of criteria. Figure 4a shows the rmsdifference from the average structure, and the rmsdifference of the average structure from the X-raystructure.

Figure 4b and c show the rms difference fromexperimental bounds in each iteration, and theaverage rms differences from ideality. The

CHARMM PARMALLH6 Lennard-Jones energy isshown in Figure 4d as a measure of the quality ofnon-bonded interaction. This energy was not partof the total energy function. In the iterations in ex-plicit solvent, the OPLS parameters (Jorgensen &Tirado-Rives, 1988) were used, in the others the``repel'' function. The pooled w1 standard devi-ation, and the percentage of residues in the mostpreferred regions of the Ramachandran plot (Mor-ris et al., 1992) are shown in Figure 4e and f. ThePROSA energy (Sippl, 1993) is shown in Figure 4gand the quality index from WhatIf (Vriend &Sander, 1993) in Figure 4h.

The final structures

With the ®nal data set, 200 structures were re-calculated ab initio, and the 50 best of these wereselected for a ®nal re®nement cycle in explicit sol-vent, and ®nal analysis. The structure with thelowest restraint energy after re®nement in solventwas chosen as the representative NMR structure.Figure 5 shows a diagram of the structure.

The hydrogen bonds formed in the ®nal struc-tures are those expected from the secondarystructure assignment and agree, with very few ex-ceptions, with those published previously (Macias

Figure 3. Ca traces of the seven lowest energy structures: a, iteration 0; b, iteration 1; c, last iteration.


et al., 1994). Figure 6 shows sequence plots of anumber of parameters describing the structure;namely, the number of medium-range and long-range NOEs per residue (a), the average rms differ-ence from the average (b), the rms difference fromthe X-ray crystal structure (c), and the circularorder parameter (Hyberts et al., 1992; (d)), and rela-tive solvent accessibilities of side-chains (e) andbackbone (f). Figure 7 is a Ramachandran plot of

all 50 ®nal structures. Glycine residues are alwaysshown as circles, all other residues as crosses iftheir angular order parameter exceeds 0.9, other-wise as dots. Table 2 gives the structural statisticsof the ®nal ensemble, including the PROSA energy(Sippl, 1993) and the percentage of residues in themost favourable regions (Morris et al., 1992).Table 3 gives the rms differences from the averageand from the X-ray structure. Figure 8(a) shows

Figure 4. Structural parameters during re®nement. a,The rms differences from the average structure (continu-ous line) and from the X-ray crystal structure (HyvoÈnenet al., 1995; broken line); b, rms difference from distancebounds (in AÊ ). c, The rms difference from ideal anglevalues (in degrees). d, CHARMM PARMALLH6 (Brookset al., 1983) Lennard-Jones vdW energy. This vdWenergy was used as a consistent criterion of the packingquality, not in the re®nement. e, Pooled w1 standarddeviation reported by PROCHECK (Morris et al., 1992).f, Percentage of residues in the most favourable regionsof the Ramachandran plot as reported by PROCHECK(Morris et al., 1992). g, PROSA energy (Sippl, 1993).h, WhatIf quality index (Vriend & Sander, 1993). Figure 6. Sequential plots for several structural par-

ameters: a, number of long-range (open bars) and med-ium-range NOEs; b, average rms difference from theaverage structure; c, average rms difference from the X-ray crystal structure; d, circular order parameter(Hyberts et al., 1992) of f (continuous line) and c (bro-ken line); e, relative solvent-accessibility of side-chains;f, relative solvent-accessibility of the backbone.


the Ca trace of the 50 ®nal NMR structures, (b) thedistribution of side-chain positions in the hydro-phobic core, and (c) a superposition with the X-raycrystal structure (HyvoÈnen et al., 1995), indicatingthe side-chains involved in ligand binding. Figure 9shows the superposition of the conserved second-

Figure 5. Schematic representation of the solutionstructures of the b-spectrin PH domain.

Figure 7. Ramachandran plot of all 50 ®nal structures.Glycine residues are always shown as circles, all otherresidues as crosses if the angular order parameterexceeds 0.9 for both c and f, otherwise as dots.

Table 2. Structure statistics

rms differences from ideal valuesBond (AÊ ) 0.65 � 10ÿ3 (�/ÿ 0.37 � 10ÿ4)Angle (�) 0.61 (�/ÿ 0.03)Impr (�) 0.98 (�/ÿ 0.29)

Non-bonded energies (kcal molÿ1)Repela 56.6 (�/ÿ 21.7)vdWb ÿ494.5 (�/ÿ 17.6)vdWc 637.0 (�/ÿ 17.6)Elecd ÿ3204.40 (�/ÿ 87.3)

rms differences from distance restraints (AÊ )Unambig 2.42 � 10ÿ2 (�/ÿ 4.23 � 10ÿ3)Ambig 1.93 � 10ÿ2 (�/ÿ 3.20 � 10ÿ3)H bond 6.65 � 10ÿ2 (�/ÿ 2.51 � 10ÿ3)All NOEs 2.31 � 10ÿ2 (�/ÿ 3.34 � 10ÿ3)All data 2.69 � 10ÿ2 (�/ÿ 2.76 � 10ÿ3)

Violations of distance restraints > 0.2 AÊ

Unambig 4.3 (�/ÿ 1.86)Ambig 0.52 (�/ÿ 0.72)H bond 2.28 (�/ÿ 0.53)All NOEs 4.82 (�/ÿ 2.07)All data 7.1 (�/ÿ 2.04)

Quality indicesPROSA(kT)e ÿ1.18 (�/ÿ 0.08)% f ÿ cf 74.41 (�/ÿ 3.09)WhatIfg ÿ0.79 (�/ÿ 0.11)

a The repel energy Erepel � krepel (max(0, (Srmin)2 ÿ r2))2 wasevaluated with krepel � 5, S � 0.78 (see Table 4). This energyfunction was not part of the ®nal re®nement step.

b CHARMM PARMALLH6 Lennard-Jones energy. Thisenergy function was not part of the ®nal re®nement step, but isquoted for consistency.

c OPLS/AMBER Lennard-Jones energy, evaluated for proteinonly.

d OPLS/AMBER vacuum electrostatic energy.e Sippl (1993).f Percentage of residues in most favourable regions of the

Ramachandran plane (Morris et al., 1992).g Vriend & Sander (1993).


ary structure regions of PH domains from differentproteins; dynamin (Ferguson et al., 1994), pleckstrin(Yoon et al., 1994), PLCd (Ferguson et al., 1995),and the X-ray crystal and NMR structures of b-spectrin.

Table 3. The rms differences

Atomic rms differences (AÊ )Backbone atoms N,

Ca, CAll non-hydrogen

atoms

rms from average

Secondary structurea 0.39 (�/ÿ 0.091) 0.80 (�/ÿ 0.099)Buried side-chainsb 0.47 (�/ÿ 0.10) 0.59 (�/ÿ 0.083)All residues 1.00 (�/ÿ 0.19) 1.61 (�/ÿ 0.19)

rms from X-ray

Secondary structure 0.71 (�/ÿ 0.091) 1.67 (�/ÿ 0.10)Buried side-chains 0.93 (�/ÿ 0.090) 1.31 (�/ÿ 0.070)All residues 1.86 (�/ÿ 0.21) 2.98 (�/ÿ 0.21)

a Residues in regular secondary structure in both X-ray crystaland NMR structure.

b Side-chains less than 20% solvent accessible.

Discussion

The NMR solution structure of the domain

The structure consists of the characteristic seven-stranded b-sandwich, which is closed with the C-terminal a-helix at one end (Figure 5). The NMRensemble is mostly well ordered, including side-chains in the core of the protein. Disorder is foundespecially in the long loops between strands A andB, strands E and F, and the loop between helix H1and strand D. This correlates with the fact that vir-tually no long-range NOE could be detected forthese regions. No resonance could be detected forArg21 in loop AB, indicating local motion.

A comparison with the X-ray crystal structureshows a very close resemblance of the two struc-tures. Note that because of rather different sampleconditions (free protein at pH 6.5 in the NMR sol-ution, complexed protein at pH 4.8 in the crystal),perfect agreement might not be expected. The sec-ondary elements (evaluated with DSSP (Kabsch &Sander, 1983)) are virtually identical, with strand Aextending from residues 2 to 11, strand B from 23to 31, strand C from 34 to 38, helix 1 from 41 to 46,strand D from 55 to 57, strand E from 62 to 66,strand F from 75 to 79, strand G from 85 to 89, andhelix 2 from 93 to 104. Small differences are re-stricted to the ends of strands, with the NMR struc-ture showing strands B, D, F and G one residuelonger than in the X-ray crystal structure, relatedto differences in hydrogen bonding discussedbelow.

The differences are indeed mostly con®ned toregions involved in the binding of IP3. The resi-dues forming hydrogen bonds or salt-bridges toIP3 in the X-ray crystal structure are Arg21, Ser22and Trp23 at the end of the loop between strandsA and B, Lys8 in the ®rst b-strand, and Tyr69 andLys71 in the loop between strands F and G. The®rst loop, extending from residue 12 to residue 22,is longer in spectrin PH domains than in mostother PH domains (Musacchio et al., 1993). Whilethere is some local order in this loop, residueArg21 is completely disordered. Even after exten-sive search, only very few medium-range or long-range NOEs could be found to any residue in thisloop (see Figure 6), indicating motion on a mediumtime-scale. Out of the six residues involved in IP3binding, only two (Trp23 and Lys8) are in thesame position in the liganded and unligandedforms. Three residues (Arg21, Ser22 and Lys71) aredisordered, and Tyr69 is ordered but has to under-go a conformational transition (see Figure 8(c)).The conformational transitions and the entropiccosts induced by ligand binding may explain theonly moderate binding af®nity (HyvoÈnen et al.,1995).

There are few differences away from the bindingsite. One involves residue Glu53, which forms asalt-bridge to Arg7 in the X-ray crystal structure.There is no evidence for this salt-bridge in theNMR ensemble, which is quite disordered around

Figure 8. The ensemble of 50 ®nal structures. (a) Ca trace of all residues; (b) side-chains forming the hydrophobiccore around Trp99; (c) Overlay of the 50 NMR structure (in grey) and the X-ray crystal structure (HyvoÈnen et al.,1995). The residues involved in IP3 binding are shown.


residue 50. There are differences in hydrogen-bonding patterns at two positions in the structure.The ®rst is a hydrogen bond between 37 N and54 O in the NMR structure, which is absent in theX-ray structure and thus extends strand D by oneresidue in the NMR structure. The amide group ofresidue 37 is protected in the NMR sample. Thesecond is a hydrogen bond between the (pro-tected) amide group of residue 75 and 66 O,which again is absent from the X-ray structure.This conformational difference could be due toligand binding, since residue Tyr69 has to rotate,

and residue Lys71 has to move considerably inorder to come into contact with IP3 (seeFigure 8(c)). The position in the complex mightbe incompatible with an extension of the b-sheet.The conformation of the C-terminal a-helix iscompletely unaffected.

As expected, the structure is very similar to thatof the PH domain of Drosophila b-spectrin (Zhanget al., 1995). The only signi®cant difference is in theexact position of helix 1. There is evidence forincreased mobility of this helix in solution (fastamide exchange and large positional ¯uctuations

Figure 9. Overlay of conserved secondary structure elements of spectrin (HyvoÈnen et al., 1995; this work), pleckstrin(Yoon et al., 1994), dynamin (Ferguson et al., 1994) and PLCd (Ferguson et al., 1995).


in molecular dynamics calculations (R. Abseher &M. N., unpublished results).

The comparison with PH domains from otherproteins shows that the fold of the domain is verywell conserved for the common secondary struc-ture, even for proteins showing basically no se-quence similarity. The secondary structure forspectrin residues 3 to 7, 25 to 30, 34 to 37, 55-56,63-64, 75 to 79, 86 to 89 and 93 to 103 is conservedin pleckstrin (Yoon et al., 1994), dynamin (Fergusonet al., 1994) and PLCd (Ferguson et al., 1995). Theend of strand G and the beginning of the C-term-inal helix are strictly conserved between the struc-tures.

The solvent accessibility of the backbone(Figure 6e) is, as expected, small for the regions ofsecondary structure, with the exception of strandsD and E, which are accessible at every other resi-due. The same has been observed for the PTBdomain, which has the same fold as the PH do-main (Lemmon et al., 1996; Zhou et al., 1996; Ecket al., 1996).

The roÃ le of ADRs in the derivation of the PHdomain structure

The derivation of the structure of the PH domainwas made rather dif®cult by overlap in key regionsin the 2D NOE spectra. The use of ADRs was criti-cal in determining the fold of the protein (Maciaset al., 1994). Due to the unfortunate chemical shiftdispersion for residues in the C-terminal helix, nocontact could be assigned from the helix to thecore of the protein, with the exception of W at 99.Consequently, the calculated structures showedthree different positions for the helix. The additionof unassigned peaks in the form of ADRs led to acorrect placement of the helix (Macias et al., 1994).ADRs also played an important roÃ le in the detec-tion of errors in the initial chemical shift assign-ments and initially assigned NOEs. The data setused for the very ®rst structure calculations wasself-consistent, and a restraint violation analysiscould therefore not be used to identify errors. Withthe addition of information from unassigned peaks

in the form of ADRs, these violations appeared,and errors could be identi®ed.

The NMR structures used for solving the X-raycrystal structure of the domain (HyvoÈnen et al.,1995; Wilmanns & Nilges, 1996) were calculatedwith an early version of the method presentedhere. The structures had high conformational ener-gies and were generally not of the same quality asthe structures here, but were suf®ciently accuratefor molecular replacement.

Quality indices during refinement

There is a good correlation between the progressof re®nement and most of the parameters. In some,there is a clear further improvement with there®nement in explicit solvent (WhatIf, w1 standarddeviation, the quality of the f, c map). In contrast,the PROSA energy stays virtually constant afterthe structures have essentially converged to their®nal fold. Interestingly, the curves for the Rama-chandran analysis and the WhatIf quality indicesare almost perfectly parallel.

The quality of the ®nal structures is comparablewith that of other structures derived from homo-nuclear NMR experiments. This is remarkable,because most of the NOE interpretation was per-formed automatically, and no additional data (tor-sion angles from coupling constants) were used.

Possible improvements and extensions ofthe method

Automated analysis of peak shape (Antz et al.,1995) would be very useful in combination with re-straint violation analysis to help recognize noisepeaks, for example, by assigning likelihoods thatpeaks contain useful information on the basis oftheir shape. The probability that a restraint isremoved from the list could be set proportional tothis likelihood. Better distance estimates wouldhelp as well the assignment with ADRs (Nilges,1995) as the restraint violation analysis. This couldbe achieved by using complete relaxation matrixanalysis (Boelens et al., 1989) as part of the iterativescheme. Likewise, the current procedure could, inprinciple, easily be modi®ed to allow ensemble


re®nements (Bonvin & BruÈ nger, 1995). Initial trialshave shown, however, that a naive application ofthese ideas does not work.

Conclusions

Automation is a necessary element of a speedupof the determination of three-dimensional struc-tures by NMR. This speedup is needed especiallyin view of the larger and larger number ofsequences becoming available from genome se-quencing projects, and the detection of domainsfrom multiple sequence alignments (Casari et al.,1996). NMR is the method of choice for getting an,at least approximate, picture of the fold of domainsof suitable size. A bottleneck in the structure deter-mination is often the NOESY assignment.

The aim of this study was to devise a generalmethod that interprets an NOE spectrum automati-cally, once the resonances have been assigned(almost) completely, and some NOEs have beenassigned that give a very rough idea of the fold.While we have shown that structures of good qual-ity can be derived with the automated methodalone, it is clear that in general it will be necessaryto inspect the spectra and correct some interpret-ations by hand. Inspection of the list of rejectedrestraints is especially useful to adjust tolerances forchemical shifts and distance bounds, and identifyerrors in the resonance assignments. The methodprovides criteria where the assignment encounteredthe largest dif®culties. The advantage of using the

Table 4. Simulated annealing protocol

ConformationalStage searcha

Temperature (K)b 2000

Masses (a.m.u.) 100

Energy constants

Ky ÿ fc (kcal molÿ1 radÿ2) 5

Ko ÿ fc (kcal molÿ1 radÿ2) 5

Krepel (kcal molÿ1 AÊ ÿ4) 0.02! 0.1d

Srepeld 1.25e

KNOE (kcal molÿ1 AÊ ÿ2) 10.0! 50.0Kambig (kcal molÿ1 AÊ ÿ2) 1Asymptotef 2.0Rsw (AÊ )f 1.0

Simulation time (teps) 10,000

a The search phase was omitted in the re®nement cycles.b The temperature was maintained by coupling to a heat bath (Bc Only the energy constants involving diastereospeci®cally unas

assignment protocol. Ky ÿ f and Ko ÿ f are the energy constants forgroups. All other energy constants for covalent interactions1000 kcal molÿ1 AÊ ÿ2 for bonds and 500 kcal molÿ1 radÿ2 for bond a

d Scale factor for calculating the van der Waals radii from LennaGEO radii (Havel & WuÈ thrich, 1984) are reproduced exactly for S �

e In the ``search'' phase, the non-bonded interactions are comside-chain, with van der Waals radii of 2.25 AÊ .

f Asymptotic slope and in¯exion point of the ¯exible distance res

method may be comparable to an SA re®nement inX-ray crystallography (BruÈ nger et al., 1987), wheremany of the operations necessary to re®ne a struc-ture can be done automatically, and the remainingmanual interventions are easier because the SAre®nement usually results in a more interpretableelectron density map. In the same sense, we feelthat the current automated procedure will be a veryuseful tool in the early stages of a structure determi-nation as well as in the ®nal re®nement stage.

Materials and Methods

NMR spectroscopy and resonance assignment

The NMR experiments were run on a Bruker AMX-600 spectrometer using a 1 mM sample either in 90%2H2O/10% 1H2O or 100% 2H2O. All the 2D NMR spectawere acquired in phase-sensitive mode (TPPI; Marion &WuÈ thrich, 1983) either with selective excitation of thewater resonance (WATERGATE; Piotto et al., 1992), orwith presaturation of the residual water when thesample was in 2H2O. Mixing times of 25 to 40 ms wereused for the clean TOCSY (Griesinger et al., 1988), and 30and 80 ms for the NOESY (Jeener et al., 1979). A 3DTOCSY-NOESY (Oschkinat et al., 1988) was recorded aswell. All the experiments were recorded at 303 K and pH6.5 with 2000 data points in the acquisition domain and1000 in t1 for the 2D experiments, and with2048 � 192 � 192 data points for the 3D experiment.

The proton frequencies were assigned using sequentialassignment in the standard way (WuÈ thrich, 1986). The3D-TOCSY-NOESY was used to resolve severe ambigu-ities.

Cool2,Cool1 minimization

2000! 1000 1000! 100

100 100

5! 500 5005! 500 5000.01! 4 4

0.78 0.7850.0 50.0

1! 50 502.0 2.01.0 1.0

5000 2000/250

erendsen et al., 1984) with a coupling constant of 10 psÿ1.signed methylene and propyl groups were varied for the ¯oatingbond angles and chirality, respectively, for atoms involving thesewere constant through the simulated annealing protocol, at

ngles, planarity and chirality.rd-Jones parameters. With the parallhdg.pro parameters, the DIS-

0.8, apart from oxygen atoms, which have slightly smaller radii.puted only between Ca atoms and one carbon atom for each

training potential (Nilges et al., 1988a,b).


Structure calculation and automated assignment

All structure calculations were done with an ab initiosimulated annealing method, starting from random poly-peptide chains, using an extended version of X-PLORversion 3.1 (BruÈ nger, 1992). The simulated annealingmethod (Table 4) is similar in spirit to that described byNilges et al. (1988b) but has been extensively modi®edand adapted to calculations with ADRs. Floating chiral-ity assignment (Weber et al., 1988) was used for all meth-ylene and isopropyl groups with separate chemicalshifts. The PARALLHDG force-®eld (Nilges et al., 1988a;Kuszewski et al., 1992) was modi®ed to be moreself-consistent, and more consistent with the CSDX par-ameters (Engh & Huber, 1991), as far as this was possiblewithout introducing more atom types.

Most of the structure analysis was performed withX-PLOR. The programs PROCHECK (Morris et al., 1992),PROSA (Sippl, 1993), and WhatIf (Vriend & Sander,1993) were used for additional structure analysis.

Average structures were calculated, and structuressuperposed to well-de®ned regions de®ned by iterativelyexcluding all residues for which the average CA distancefrom the average structure exceeds two standard devi-ations (Nilges et al., 1987).

Automated peak-picking

The NOE spectra were peak-picked and quanti®edwith the automatic picking routine of AURELIA (Neidiget al., 1995). The most obvious artefacts, in particulararound the H2O frequency, were removed by editing theresulting peak lists. The edited lists were then directlyconverted into X-PLOR restraints lists, essentially asdescribed (Nilges, 1995). The peak lists have generally aformat ``peak-number F1 F2 volume'', plus some otherinformation that is not used here. With the VECTor DOcommand, we read the proton chemical shifts into anarray in X-PLOR (e.g. the Q array). Atoms can then beselected based on the value of this vector (i.e. the chemi-cal shift), using the ATTRibute factor of the atom selec-tion. As frequency windows around the picked value foratom selection we have used uniformly �0.02 ppm inthe F2 dimension, and 0.04 ppm in the F1 dimension.

In summary, a restraint resulting from an entry fromthe peak list

15 2.385 4.933 3008995

becomes the restraint

ASSIgn

(ATTRibute Q > 2.355 AND ATTRibute Q < 2.415)

(ATTRibute Q > 4.918 AND ATTRibute Q < 4.948)

1.0 1.0 1.0

VOLUme=307005 PEAK=15 PPM1=2.381 PPM2=4.921

Note that the volumes are read directly into ourextended version of X-PLOR, and the distances and errorestimates are set to arbitrary values. The volumes areconverted into distances with appropriate error limitsinternally by the calibration procedure described inCalculation Strategy. The peak number is added in therestraint to facilitate tracing the peaks in the originalspectra from the restraint list. The frequencies have thesame purpose. They can also provide a measure of the``goodness of ®t'' of the NOE assignment, which is use-

ful to mark peaks that should be checked manually. Atpresent, the restraints speci®ed in this way in terms ofthe chemical shifts are converted into lists of atoms bythe X-PLOR atom selection directly when the restraintsare read in.

Modelling of hydrogen bonds

Hydrogen bonds were treated in a manner similar toambiguous NOEs. Especially at the ends of secondarystructure elements, irregular and bifurcated hydrogenbonds can occur, and distance restraints between speci®cdonors and acceptors may lead to local errors in thestructure (Billeter, 1992). On the other hand, the slowexchange adds very important experimental information,and hydrogen bonds are very powerful restraints forde®ning the structure.

The effective distance from a given donor to severalacceptors is calculated as for the NOE via equation (1).To make the restraining term more ``selective'' for asingle acceptor rather than several at the same time, wehave used a higher exponent (20 instead of 6), whichweights the distance more to the shortest contributingone. The hydrogen-acceptor distance was restrained be-tween 1.7 and 2.2 AÊ , and the donor±acceptor distancebetween 2.7 and 3.2 AÊ . The lower bound on the donor±acceptor distance, together with the upper bound on thehydrogen±acceptor distance puts an effective anglerestraint on the hydrogen bond geometry (the donor±hydrogen±acceptor angle has to be larger than approxi-mately 110�). Note that the present treatment of hydro-gen bonds is different from the use of a standardhydrogen bond potential in the distance geometry calcu-lation (Mierke & Kessler, 1993).

Non-bonded interactions: refinement in water

The structures were re®ned with a more realistic rep-resentation of non-bonded interactions than is possiblein distance geometry-like calculations. In order to avoiddistortions of the geometry (especially bond angles andplanarity) that are inevitable with a standard moleculardynamics force-®eld, even with very low energy con-stants for the experimental terms, we have used a hybridof PARALLHDG (for the covalent interactions) and non-bonded interactions derived by LeMaster et al. (1988)from the OPLS force-®eld (Jorgensen & Tirado-Rives,1988) and the all-atom AMBER force-®eld (Weiner et al.,1984). The re®nement is in explicit solvent primarily toavoid artefacts due to missing van der Waals interactionswith solvent in a re®nement in vacuo, which lead to un-realistic packing of ¯exible loops and side-chains (datanot shown).

We have followed essentially the same protocol andhave used the same parameter set as previously (Prom-pers et al., 1995). The structures were surrounded by a9 AÊ shell of TIP3P water (Jorgensen et al., 1983). Allwater molecules for which the water oxygen atom wasless than 4 AÊ away from a protein heavy-atom were re-moved. The water was ®rst minimized and equilibratedwith the protein held in its starting position by positionalrestraints (Bruccoleri & Karplus, 1986). The system wasthen heated to 500 K, re®ned for 2000 steps at 500 K, andsubsequently cooled and minimized. Coulomb inter-actions were calculated with ``shift'' (Brooks et al., 1983)and an atom-based cutoff of 9 AÊ .


References

Antz, C., Neidig, K. P. & Kalbitzer, H. R. (1995). A gen-eral Bayesian method for an automated signal classrecognition in 2D NMR spectra combined with amultivariate discriminant analysis. J. Biomol. NMR,5, 287±296.

Berendsen, H. J. C., Postma, J. P. M., van Gunsteren,W. F., DiNola, A. & Haak, J. (1984). Moleculardynamics with coupling to an external bath. J. Chem.Phys. 81.

Billeter, M. (1992). Comparison of protein structuresdetermined by NMR in solution and by X-ray dif-fraction in single crystals. Quart. Rev. Biophys. 25,325±377.

Boelens, R., Koning, T. M. G. & Kaptein, R. (1989). De-termination of biomolecular structures from proton-proton NOEs using a relaxation matrix approach.J. Mol. Struct. 173, 299±311.

Bonvin, A. M. & BruÈ nger, A. T. (1995). Conformationalvariability of solution nuclear magnetic resonancestructures. J. Mol. Biol. 250, 80±93.

Brooks, B. R., Bruccoleri, R. E., Olafson, B. D., States,D. J., Swaminathan, S. & Karplus, M. (1983).CHARMM: a program for macromolecular energy,minimization, and dynamics calculations. J. Comput.Chem. 4, 187±217.

Bruccoleri, R. E. & Karplus, M. (1986). Spatially con-strained minimization of macromolecules. J. Comput.Chem. 7, 165±175.

BruÈ nger, A. T. (1992). X-PLOR. A System for X-rayCrystallography and NMR, Yale University Press,New Haven.

BruÈ nger, A. T., Kuriyan, J. & Karplus, M. (1987). Crys-tallographic R factor re®nement by moleculardynamics. Science, 235, 458±460.

Casari, G., de Daruvar, A., Sander, C. & Schneider, R.(1996). Bioinformatics and the discovery of genefunction. Trends Genet. 12, 244±245.

Downing, A. K., Driscoll, P. C., Gout, I., Salim, K.,Zvelebil, M. J. & Water®eld, M. D. (1994). Three-dimensional solution structure of the pleckstrinhomology domain from dynamin. Curr. Biol. 4,884±891.

Eck, M. J., Dhe-Pagnanon, S., TruÈ b, T., Nolte, R. T. &Shoelson, S. E. (1996). Structure of the IRS-1 PTBdomain bound to the juxtamembrane region of theinsulin receptor. Cell, 85, 584±592.

Engh, R. A. & Huber, R. (1991). Accurate bond andangle parameters for X-ray structure re®nement.Acta Crystallog. sect. A, 47, 392±400.

Ferguson, K. M., Lemmon, M. A., Schlessinger, J. &Sigler, P. B. (1994). Crystal structure at 2. 2 AÊ resol-ution of the pleckstrin homology domain fromhuman dynamin. Cell, 79(2), 199±209.

Ferguson, K. M., Lemmon, M. A. & Schlessinger, J.(1995). Structure of the high af®nity complex of ino-sitol trisphosphate with a phospholipase C pleck-strin homology domain. Cell, 83, 1037±1046.

Fletcher, C. M., Jones, D. N. M., Diamond, R. &Neuhaus, D. (1996). Treatment of NOE constraintsinvolving equivalent or nonstereoassigned protonsin calculations of biomacromolecular structures.J. Biomol. NMR 8, 292±310.

Fushman, D., Cahill, S., Lemmon, M. A., Schlessinger,J. & Cowburn, D. (1995). Solution structure ofpleckstrin homology domain of dynamin by hetero-nuclear NMR spectroscopy. Proc. Natl Acad. Sci.USA, 92, 816±820.

Garcia, P., Gupta, R., Shah, S., Morris, A. J., Rudge,S. A., Scarlata, S., Petrova, V., McLaughlin, S. &Rebecchi, M. J. (1995). The pleckstrin homologydomain of phospholipase c-delta 1 binds with highaf®nity to phosphatidylinositol 4,5-bisphosphate inbilayer membranes. Biochemistry, 34, 16228±16234.

Griesinger, C., Otting, G., WuÈ thrich, K. & Ernst, R. R.(1988). Clean TOCSY for 1H spin system identi®-cation in macromolecules. J. Am. Chem. Soc. 110,7870±7872.

GuÈ ntert, P., Berndt, K. D. & WuÈ thrich, K. (1993). Theprogram ASNO for computer-supported collectionof NOE upper distance constraints as input for pro-tein structure determination. J. Biomol. NMR, 3,601±606.

Harlan, J. E., Hajduk, P. J., Yoon, H. S. & Fesik, S. W.(1994). Pleckstrin homology domains bind to phos-phatidylinositol-4,5-bisphosphate. Nature, 371, 168±170.

Havel, T. & WuÈ thrich, K. (1984). A distance geometryprogram for determining the structures of smallproteins and other macromolecules from nuclearmagnetic resonance measurements of intramolecular1H-1H proximities in solution. Bull. Math. Biol. 46,673±698.

Hyberts, S. G., Goldberg, M. S., Havel, T. F. & Wagner,G. (1992). The solution structure of eglin c based onmeasurements of many NOEs and coupling con-stants and its comparison with X-ray structures.Protein Sci. 1, 736±751.

HyvoÈnen, M., Macias, M. J., Nilges, M., Oschkinat, H.,Saraste, M. & Wilmanns, M. (1995). Structure of thebinding site for inositol phosphates in a PHdomain. EMBO J. 14, 4676±4685.

Jeener, J., Meier, B. H., Bachmann, P. & Ernst, R. R.(1979). Investigation of exchange processes by two-dimensional NMR spectroscopy. J. Chem. Phys. 71,4546±4553.

Jorgensen, W. L. & Tirado-Rives, J. (1988). The OPLSpotential function for proteins. Energy minimizationfor crystals of cyclic peptides and crambin. J. Am.Chem. Soc. 110, 1657±1666.

Jorgensen, W., Chandrasekhar, J., Madura, J., Impey,R. & Klein, M. (1983). Comparison of simple poten-tial functions for simulating liquid water. J. Chem.Phys. 79, 926±935.

Kabsch, W. & Sander, C. (1983). A solution for the bestrotation to relate two sets of vectors. Biopolymers,22, 2577±2637.

Kuszewski, J., Nilges, M. & BruÈ nger, A. T. (1992).Sampling and ef®ciency of metric matrix distancegeometry: a novel partial metrization algorithm.J. Biomol. NMR, 2, 33±56.

LeMaster, D. M., Kay, L. E., BruÈ nger, A. T. &Prestegard, J. H. (1988). Protein dynamics and dis-tance determinations by NOE measurement. FEBSLetters, 236, 71±76.

Lemmon, M. A., Ferguson, K. M. & Schlessinger, J.(1996). PH domains: diverse sequence with a com-mon fold recruit signaling molecules to the cellsurface. Cell, 85, 621±624.

Macias, M. J., Musacchio, A., Ponstingl, H., Nilges, M.,Saraste, M. & Oschkinat, H. (1994). Structure of thepleckstrin homology domain from beta-spectrin.Nature, 369, 675±677.

Marion, D. & WuÈ thrich, K. (1983). Application of phase-sensitive two-dimensional correlated spectroscopy(COSY) for measurements of 1H-1H spin-spin coup-


ling constants in proteins. Biochem. Biophys. Res.Commun. 113, 967±974.

Meadows, R. P., Olejniczak, E. T. & Feisk, S. W. (1994).A computer-based protocol for semiautomatedassignments and 3D structure determination ofproteins. J. Biomol. NMR, 4, 79±96.

Mierke, D. F. & Kessler, H. (1993). Improved moleculardynamics simulations for the determination of pep-tide structures. Biopolymers, 33, 1003±1017.

Morris, A. L., MacArthur, M. W., Hutchinson, E. G. &Thornton, J. (1992). Stereochemical quality of pro-tein structure co-ordinates. Proteins: Struct. Funct.Genet. 12, 345±364.

Mumenthaler, C. & Braun, W. (1995). Automated assign-ment of simulated and experimental NOESY spectraof proteins by feedback ®ltering and self-correctingdistance geometry. J. Mol. Biol. 254, 465±480.

Musacchio, A., Gibson, T., Rice, P., Thompson, J. &Saraste, M. (1993). The PH domain: a commonpiece in the structural patchwork of signallingproteins. Trends Biochem Sci. 18, 343±348.

Neidig, K.-P., Geyer, M., GoÈrler, A., Antz, C., Saffrich,R., Beneicke, W. & Kalbitzer, H.-R. (1995). AURE-LIA, a program for computer-aided analysis of mul-tidimensional NMR spectra. J. Biomol. NMR, 6, 255±270.

Nilges, M. (1995). Calculation of protein structures withambiguous distance restraints. Automated assign-ment of ambiguous NOE crosspeaks and disulphideconnectivities. J. Mol. Biol. 245, 645±660.

Nilges, M., Clore, G. M. & Gronenborn, A. M. (1987). Asimple method for delineating well-de®ned andvariable regions in protein structures determinedfrom interproton distance data. FEBS Letters, 219,17±21.

Nilges, M., Clore, G. M. & Gronenborn, A. M. (1988a).Determination of three-dimensional structures ofproteins by hybrid distance geometry-dynamicalsimulated annealing calculations. FEBS Letters, 229,317±324.

Nilges, M., Gronenborn, A. M., BruÈ nger, A. T. & Clore,G. M. (1988b). Determination of three-dimensionalstructures of proteins by simulated annealing withinterproton distance restraints: application to cram-bin, potato carboxypeptidase inhibitor and barleyserine proteinase inhibitor 2. Protein Eng. 2, 27±38.

Oschkinat, H., Griesinger, C., Kraulis, P., Sorensen, O.,Ernst, R. R., Gronenborn, A. M. & Clore, G. M.(1988). Three-dimensional NMR spectroscopy of aprotein in solution. Nature, 2, 374±376.

Piotto, M., Saudek, V. & Sklenar, V. (1992). Gradient-tai-lored excitation for single-quantum NMR spec-troscopy of aqueous solutions. J. Biomol. NMR, 2,661±665.

Prompers, J. J., Folmer, R. H. A., Nilges, M., Folkers,P. J. M., Konings, R. N. H. & Hilbers, C. W. (1995).Re®ned solution structures of the Tyr41! Hismutant of the M13 gene V protein. A comparisonwith the crystal structure. Eur. J. Biochem. 232, 506±514.

Sippl, M. J. (1993). Recognition of errors in three-dimen-sional structures of proteins. Proteins: Struct. Funct.Genet. 17, 355±362.

Timm, D., Salim, K., Gout, I., Guruprasad, L.,Water®eld, M. & Blundell, T. (1994). Crystal struc-ture of the pleckstrin homology domain fromdynamin. Nature Struct. Biol. 1, 782±788.

Vriend, G. & Sander, C. (1993). Quality control of pro-tein models: directional atomic contact analysis.J. Appl. Crystallog. 26, 47±60.

Weber, P. L., Morrison, R. & Hare, D. (1988). Determin-ing stereo-speci®c 1H nuclear magnetic resonanceassignments from distance geometry calculations.J. Mol. Biol. 204, 483±487.

Weiner, S. J., Kollmann, P. A., Case, D. A., Singh, U. C.,Ghio, C., Alagona, G., Profeta, S., Jr & Weiner, P.(1984). A new force ®eld for molecular mechanicalsimulation of nucleic acids and proteins. J. Am.Chem. Soc. 106, 765±784.

Wilmanns, M. & Nilges, M. (1996). Molecular replace-ment with NMR models using distance-derivedpseudo B factors. Acta Crystallog. sect. D, 52, 973±982.

WuÈ thrich, K. (1986). NMR of Proteins and Nucleic Acids,John Wiley, New York.

Yoon, H. S., Hajduk, P. J., Petros, A. M., Olejniczak,E. T., Meadows, R. P. & Fesik, S. W. (1994). Sol-ution structure of a pleckstrin-homology domain.Nature, 369, 672±675.

Zhang, P., Talluri, S., Deng, H., Branton, D. & Wagner,G. (1995). Solution structure of the pleckstrin hom-ology domain of Drosophila b-spectrin. Structures, 3,1185±1195.

Zhou, M.-M., Ravichandran, K. S., Olejniczak, E. T.,Petros, A. M., Meadows, R. P., Sattler, M., Harlan,J. E., Wade, W. S., Burakoff, S. J. & Fesik, S. W.(1996). Structure and ligand recognition of the phos-photyrosine binding domain of Shc. Nature, 378,584±592.

Edited by P. E. Wright

(Received 2 December 1996; received in revised form 10 March 1997; accepted 12 March 1997)

Note added in proof: The coordinates have been deposited with the PDB (accession code 1 mph).

Documents

Automated NOESY Interpretation with Ambiguous Distance ......Automated NOESY Interpretation with Ambiguous Distance Restraints: The Refined NMR Solution Structure of the Pleckstrin