Computer-assisted mass spectrometric analysis of naturally occurring and artificially introduced cross-links in proteins and protein complexes Leo J. de Koning 1 , Piotr T. Kasper 1 , Jaap Willem Back 1 , Merel A. Nessen 1 , Frank Vanrobaeys 2 , Jozef Van Beeumen 2 , Ermanno Gherardi 3 , Chris G de Koster 1 and Luitzen de Jong 1 1 Biomolecular Mass Spectrometry group, Swammerdam Institute for Life Sciences, University of Amsterdam, the Netherlands 2 Laboratory of Protein Biochemistry and Protein Engineering, University of Gent, Belgium 3 MRC Centre, Cambridge, UK Mass spectrometry has become a major tool in the structural analysis of proteins and protein complexes and in large scale analysis of the function of genes (proteomics) [1]. For mass spectrometric analysis, the proteins and proteomes under study are usually first subjected to proteolytic digestion or chemical cleavage. A large number of informatics tools has been developed that helps in extracting relevant information from the com- plex mass spectrometric data [2]. Most of these pro- grams match the in silico predicted digest with the corresponding mass spectrometric data for protein identification and for mapping protein modifications. Novel strategies and methodologies in proteomics urge for dedicated programs that further integrate mass spectrometric analyses with biochemical experiments. Keywords cross-linking; data analysis; protein structure; mass spectrometry; NK1 Correspondence L. de Jong, Swammerdam Institute for Life Sciences, Mass spectometry group, University of Amsterdam, Nieuwe Achtergracht 166, Amsterdam, 1018 WV, the Netherlands Fax: +31 20 525 6971 Tel: +31 20 525 5691 E-mail: l.dejong@science.uva.nl (Received 23 September 2005, revised 28 October 2005, accepted 7 November 2005) doi:10.1111/j.1742-4658.2005.05053.x A versatile software tool, virtualmslab, is presented that can perform advanced complex virtual proteomic experiments with mass spectrometric analyses to assist in the characterization of proteins. The virtual experimen- tal results allow rapid, flexible and convenient exploration of sample prepar- ation strategies and are used to generate MS reference databases that can be matched with the real MS data obtained from the equivalent real experi- ments. Matches between virtual and acquired data reveal the identity and nature of reaction products that may lead to characterization of post-trans- lational modification patterns, disulfide bond structures, and cross-linking in proteins or protein complexes. The most important unique feature of this program is the ability to perform multistage experiments in any user-defined order, thus allowing the researcher to vary experimental approaches that can be conducted in the laboratory. Several features of virtualmslab are demonstrated by mapping both disulfide bonds and artificially introduced protein cross-links. It is shown that chemical cleavage at aspartate residues in the protease resistant RNase A, followed by tryptic digestion can be opti- mized so that the rigid protein breaks up into MALDI-MS detectable frag- ments, leaving the disulfide bonds intact. We also show the mapping of a number of chemically introduced cross-links in the NK1 domain of hepato- cyte growth factor ⁄ scatter factor. The virtualmslab program was used to explore the limitation and potential of mass spectrometry for cross-link studies of more complex biological assemblies, showing the value of high performance instruments such as a Fourier transform mass spectrometer. The program is freely available upon request. Abbreviations BS 3 , bis(sulfosuccinimidyl)suberate; HGF/SF, hepatocyte growth factor ⁄ scatter factor; NEM, N-ethylmaleimide; RNase A, ribonuclease A; SAXS, small angle X-ray scattering; TFA, trifluoroacetic acid. FEBS Journal 273 (2006) 281–291 ª 2005 The Authors Journal compilation ª 2005 FEBS 281 To support our protein studies we have developed a tool, virtualmslab, which allows us to perform a variety of advanced virtual proteomics experiments with MS analyses. Besides matching the in silico pre- dicted reaction products with the corresponding mass spectrometric data using mass band filtering, a most important, unique feature of virtualmslab is its experiment editor, allowing to calculate the results of: (a) any virtual, complete or partial, protein modifica- tion reaction including cleavages, either simultaneously or in any desired order; and (b) in and out filtering of defined reaction products. Our aim is to establish general, rapid and relatively simple procedures for the analysis of naturally occur- ring cross-links, e.g. disulfide bonds, and artificially introduced cross-links in proteins. Cross-links impose distance constraints on amino acid residues that can be used to model the 3-D structure of proteins and pro- tein complexes [3–7]. Mass spectrometric analysis of peptides derived from digested cross-linked proteins is exceptionally suited for the rapid, sensitive and precise mapping of the cross-links [3,6,8]. To support mass spectrometric analysis of cross-links in proteins, soft- ware tools have been developed [9–12] for the identifi- cation of digest fragments where peptides are linked together. However, available software suffers from lim- itations, often preventing general application in cross- link analysis [6]. Here we demonstrate several features of the virtual- mslab program for protein cross-link analysis. As a model system for the analysis of the disulfide bond structure of a protein we used ribonuclease A (RNase A), for which the 3-D structure is known in detail [13], and the disulfide bond structure has been established already in 1960 [14]. We use the virtual- mslab program to explore a successful experimental strategy to assess the disulfide bond structure from a single MALDI-TOF mass spectrum. In a separate study the Met receptor tyrosine kin- ase and its ligand, hepatocyte growth factor ⁄ scatter factor (HGF ⁄ SF) were used to explore and test a cross-linking strategy with virtualmslab. Signal transduction via the Met receptor is involved in cell growth and migration during embryogenesis as well as in cancer [15] but both the assembly of the HGF ⁄ SF complex and the basis for receptor activa- tion remain poorly understood. Insight into the spa- tial arrangement of the HGF ⁄ SF–Met complex can be obtained by chemical cross-linking. To examine the viability of a mass spectrometric analysis of chemically induced cross-links for this complex, the experimental strategy has been tested by carrying out virtual cross-linking with successive MS analysis. Following the virtual experiments, mapping of cross- links in the NK1 domain of HGF ⁄ SF treated with an amine specific cross-linking agent has been accomplished, based on the virtualmslab assisted analysis of the MS data from the corresponding un- fractionated tryptic digest. Results and discussion General setup of VIRTUALMSLAB virtualmslab is used to perform complex virtual proteomic experiments and integrate these with mass spectrometric analyses. The virtual experimental results allow rapid and convenient exploration of proteomics strategies and are used to generate MS reference data- bases that can be matched with the real MS data obtained from the equivalent real experiments. Mat- ches between virtual and real data reveal the identity and nature of reaction products that may lead to the characterization of post-translational modification pat- terns, disulfide bond structures, chemical modifications and cross-linking in protein mixtures, complexes, and assemblies. Proteins A single protein, a list of proteins from a mixture or from a protein complex or a complete proteome under study, can be entered or imported (in fasta format) into the program as amino acid sequences. Amino acid residues, N- and C-terminal end groups, and modifica- tions can be custom defined, including specific isotopic and ⁄ or virtual labelling to keep track of specific amino acid residues in the analyses. The entered proteins or a custom selection can be concurrently added to the experiments. The virtual experiment The protein or protein mixture can be subjected to an experiment including several subsequent and ⁄ or paral- lel steps. The individual steps include: l any customizable chemical and proteolytic cleavage, with optional specific isotope or virtual element substi- tution; l modifications of amino acid residues, partial sequences and ⁄ or end groups, with optional specific isotope or virtual element substitution; l in- and ⁄ or out-filtering of reaction products contain- ing any combination of specific amino acid residues, partial sequences and end groups; l mass band-filtering; Computer-assisted mass spectrometric analysis of cross-links L. J. de Koning et al. 282 FEBS Journal 273 (2006) 281–291 ª 2005 The Authors Journal compilation ª 2005 FEBS l partial unintentional modifications (such as oxida- tion, deamidation, etc.) of specific amino acid residues, partial sequences and end groups. Multipass experiment editor A unique feature of virtualmslab is the ability to perform the above listed calculations in succession and in any desired order. Cleavage, modification and filter- ing may be carried out in different steps, and the resulting virtual experimental peptide mixture may sug- gest alternatives for performing the real experiment in a certain sequence in the laboratory. For instance, if amines are modified prior to enzy- matic cleavage, the result is different from a modifi- cation to amines that has been introduced after proteolysis; in the first instance cleaved peptides carry free amino termini, in the second instance these amines are considered to be modified. Upon running the pro- grammed experiment, the resulting peptide mixture database is displayed with various sorting criteria for inspection. Mass spectrometric data To match virtual with real data, mass spectra are imported into the program as monoisotopic mass ⁄ intensity lists in ascii format. virtualmslab is capable of providing reference lists for use in internal calibrations. Masses (m ⁄ z-values) in any generated digest or MS ⁄ MS prediction, including those of multi- ply charged ions, can be double clicked for inclusion in a reference list that can subsequently be exported in ascii format. Lists like these serve as input for internal calibration in many MS software packages. LC ⁄ MS data can be time-segmented and the segments are indi- vidually processed, normalized to the base peak in the segment and imported as a series. Each individually imported mass spectrum can be activated or deactiva- ted for adding to a combined spectrum number ⁄ mass ⁄ intensity list, which is used for matching. Data matching Data matching can be achieved in matching quests. In each quest, matching criteria can be defined for search- ing unmodified and post-translationally modified pep- tides, peptides with an internal disulfide or chemically induced cross-link (intrapeptide cross-link products), and peptide pairs bonded together with a disulfide bridge or a chemically induced cross-link (interpeptide cross-link products). Each mass in the combined mass list is matched within a custom defined mass window with the masses of the peptides from the virtual experi- ment, selected according to the quest criteria. A match can be performed for a number of quests simulta- neously. For instance, a digest of a disulfide-containing protein (described in more detail below) can be analysed for the presence of unmodified peptides (quest 1), pep- tides containing an internal disulfide linkage (quests 2), or peptide pairs connected by a disulfide bond (quest 3). The resulting output sheet, illustrated in Figure 1 shows the experimental mass list with the match quests assign- ments. For convenient analyses of the assignments the result table can be sorted on each heading. Platform virtualmslab runs on a Microsoft Visual Basic plat- form and is freely available from the author LJdK, ldk@science.uva.nl. Mapping of disulfide bonds with aid of VIRTUALMSLAB Disulfide bonds in proteins can be mapped by mass spectrometric identification of the corresponding digest peptides [16]. For this, efficient cleavage between cys- teine containing sections of the protein, leaving the disulfide bridges intact, is essential. However, disulfide bonded proteins often have a rigid structure rendering the native protein resistant to cleavage by proteases. In that case, chemical cleavage may be considered, such as the use of cyanogen bromide to cleave at methion- ine residues, or pH 2 at elevated temperature to cleave peptides bonds at the C- or N-terminal side of aspar- tate residues. RNase A was used as a model protein to show the development of a procedure with the aid of virtualmslab for mapping disulfide bonds in a rigid protease resistant protein [14].Virtual experiments with the virtualmslab program showed that MALDI-MS detectable fragments, with masses ranging from 800 to 4000 atomic mass units, could be generated by ini- tial specific acid cleavage in front of and behind aspar- tate residues [17,18] to break-up the rigid protein, followed by tryptic cleavage which takes place behind lysine and arginine residues. Experimentally, RNase A was cleaved by treatment at pH 2, followed by trypsin digestion and mass analy- sis of the resulting peptide mixture. Based on a single MALDI-FTICR mass spectrum, 42 fragments were assigned by virtualmslab within a mass window of 4 p.p.m., corresponding to a sequence coverage of > 90%. Figure 1 shows part of the output sheet for the assignment over three quests. The first quest matches all unmodified peptide masses (specified by L. J. de Koning et al. Computer-assisted mass spectrometric analysis of cross-links FEBS Journal 273 (2006) 281–291 ª 2005 The Authors Journal compilation ª 2005 FEBS 283 the question mark) to the experimental masses. The second quest matches the combined masses of all pairs of peptides, each containing at least one cysteine minus the mass of two hydrogen atoms, assigning the disul- fide linked peptides. The third quest matches the mass of all peptides containing cysteine minus the mass of two hydrogen atoms, assigning the peptides with an internal disulfide link. From the assignments, a peptide map was construc- ted as shown in Fig. 2. Due to partial cleavage at both D and R ⁄ K, many overlapping peptides were observed. About 80% of all peaks in the MALDI- FTICR mass spectrum with intensity above 5% of the base peak could be assigned, assuming cleavage at D or K ⁄ R. This demonstrates the high specificity of chemical cleavage at aspartate residues. We were aware of the possible occurrence of deamidations of asparagines and subsequent partial cleavage at the resulting aspartate residues. However, virtualmslab analysis allowing partial modification of N to D fol- lowed by partial cleavage on the newly formed D resi- dues, showed no matches for the resulting peptides. This indicates the absence of severe deamidations under our experimental conditions. Of the 42 assigned fragments, a total of 23 were unambiguously attrib- uted to peptides with a correct disulfide bridge, consid- ering four disulfide linkages in RNase A. Of the 23 disulfide-containing fragments, three were assigned to the C26–C84 linkage, 12 to C40–C95, four to C58– C110, and four to C65–C72. Several disulfide-linked peptides were also present as free SH-containing pep- tides, indicating partial in-source reduction of disul- fides [19]. It should be noted that this phenomenon enables assignment of pairs of in-source cleavage prod- ucts to corresponding disulfide linked peptides, the sum of the masses of the cleavage products, due to incorporation of two H atoms, being 2 atomic mass units more than the mass of the parent compounds. This information can be used to confirm the results of the virtualmslab analysis. Despite the overwhelming evidence for the correct disulfide linkages, three minor peaks were assigned by virtualmslab to peptides with conflicting disulfide linkages; two of these correspond to a peptide with Fig. 1. Part of the output sheet of the VIRTUALMSLAB analysis of the MALDI-FTICR-MS data of the RNase A digest peptide mixture. The first column lists the mass spectrum with spectrum number. The second column lists the numbers of the matches corresponding to the quest numbers on the VIRTUALMSLAB console shown in the inset. Column 3 lists the theoretical masses of the assignments with the match error in p.p.m. Columns 4 and 5 list the peptide assignments with the precursor proteins (in this experiments this is only RNase A), the peptide posi- tion in the protein and the residue sequence. Computer-assisted mass spectrometric analysis of cross-links L. J. de Koning et al. 284 FEBS Journal 273 (2006) 281–291 ª 2005 The Authors Journal compilation ª 2005 FEBS an internal C40–C58 linkage, the third corresponds to a peptide with an internal C84–C95 1inkage. These species can conceivably be naturally occurring disul- fide-bridge variants, or can be the result of disulfide interchange reactions during the experiment. Disulfide interchanges can in principle be catalysed by free thiols at neutral or high pH. If this were the case, a thiol scavenger should be able to prevent disulfide interchange. To investigate this possibility we added N-ethylmaleimide (NEM) to the acid-cleaved RN- ase A preparation before the start of the digestion at pH 8.0 by trypsin. It should be noted that at this pH NEM not only reacts with SH groups, but to a lesser extent also with amines. The presence of NEM during trypsin digestion therefore results in complex peptide mixtures, due to partial modification at the amino terminus and at lysine residues, and because modifica- tion at lysine residues prevents cleavage by trypsin. Accordingly, analysis using virtualmslab including modifications with NEM in the match quests results in the assignment of no fewer than 84 peptides. Of these, 31 represent free SH-containing peptides, as the result of in-source decay, and 53 are correct disulfide- linked species. No unambiguous evidence was found for peptides with internal C40–C58, C84–C95 or any other conflicting linkages under these conditions, indi- cating that their minor presence in the absence of NEM must have been the result of disulfide inter- change reactions. A possible explanation is the phe- nomenon of b-elimination [20], occurring under the alkaline conditions during trypsin digestion, creating the necessary catalyst for the interchange reaction. Even trace amounts of free sulfhydryl groups can trigger a cascade of reshuffling of disulfide-linked peptides, which may explain the minor formation of the detected peptides with an internal C40–58 or C84–95 disulfide bond. Ambiguities caused by these interchange reactions can be resolved by adding NEM before and during digestion. In conclusion, it appears that well-controlled acidic cleavage followed by tryptic digestion effectively breaks up the rigid RNase A molecule into MALDI-MS detectable fragments, leaving the vulnerable disulfide bonds intact. The virtualmslab analysis of the data from a single MALDI-mass spectrum acquired with a high performance FTICR mass spectrometer unambig- uously reveals the origin of all disulfide bonds. Identification of cross-links in the NK1 domain of HGF/SF HGF ⁄ SF and its receptor Met stimulate cell growth, cell differentiation and migration during embryogenesis. In 124 V S A D 120 F H V P V Y P N G E 110 C A V I I H K N A Q 100 T T K Y A C N P Y K 90 S S G T E R C D T I 80 S M T S Y S Q Y C N 70 T Q G N K C A V N K 60 Q S C V A Q V D A L 50 S E H V F T N V P K 40 C R D K T L N R S K 30 M M Q N C Y N S S S 20 A A S T S S D M H Q 10 R E F K A A A T E 1K Fig. 2. Peptide map constructed from the VIRTUALMSLAB assign- ments of the MALDI-FTICR-MS data of the RNase A digest peptide mixture. The first column shows the sequence with the four well established disulfide links. The second column shows the peptides resulting from the in-source MALDI reduction of S–S-linked pep- tides. Column 3 shows the linked peptides, clearly confirming all four established disulfide links. Column 4 shows the peptides asso- ciated with conflicting internal disulfide bridges. L. J. de Koning et al. Computer-assisted mass spectrometric analysis of cross-links FEBS Journal 273 (2006) 281–291 ª 2005 The Authors Journal compilation ª 2005 FEBS 285 cancer they promote invasive growth in surrounding tissues and metastasis of the tumour. Both proteins are produced as inactive singular proenzymes, which upon cleavage form an active disulfide-linked a ⁄ b heterodimer. Several individual domains of both Met and HGF ⁄ SF have been elucidated, but the 3-D struc- tures of the full-length proteins are not yet resolved. The NK1 domain of the a-chain of HGF ⁄ SF is found to be the main interaction site with Met, while the b-chain might make additional interactions. To obtain a model of the interaction of Met and HGF⁄ SF, the complex has been subjected to solution phase small angle X-ray scattering (SAXS) (Gherardi, E., Sandin, S., Petoukhov, M. V., Finch, J., O ¨ fverstedt, L G., Nunez, R., Blundell, T. L., Vande Wonde, G. F., Skoglund, U. & Svergun, D. I., unpubished data). Experimentally determined constraints on the distances of amino acid residues should be helpful to either discard or confirm the solu- tions obtained by SAXS. Identification of the sites of artificially induced cross-links can provide such distance constraints and, with these constraints, a detailed model of the interaction between the two proteins can be designed, based on SAXS data and the known 3-D structures of single protein domains. Such a model will be of great value both to understand how HGF ⁄ SF interaction with Met leads to receptor dimerization and signal transduction and to design Met inhibitors as anticancer drugs [15]. Mass spectrometric analysis of digests of cross-linked proteins is known to be a powerful way to identify sites of cross-linking [3,6,8]. However, the identification of cross-linked sites in biological assemblies as complicated as the HGF ⁄ SF-Met complex are unprecedented. We use the amine-specific homobifunctional cross-linker bis(sulfosuccinimidyl)suberate (BS 3 ). Besides reaction with amines, the activated ester is also susceptible to hydrolysis, which may lead to single labelling, i.e. modi- fication of amines without actual cross-linking. Clearly, the above analyses of the naturally occurring disulfide- linkages in RNase A must be taken a step further for this complex which is build from four peptide chains over two disulfide-linked ab heterodimers. The complex has more than 1600 amino acid residues adding up to a mass of over 180 kDa, and it has 98 lysine residues which can be heterogeneously cross-linked or singly labelled by the cross-linking reagent. To anticipate limitations of a mass spectrometric analysis of this complicated system, analysis has first been completed with the virtualmslab program. The above HGF ⁄ SF-Met complex was subjected to reduc- tion and alkylation of cysteine residues by iodaceta- mide, followed by digestion with trypsin, allowing a maximum of three miscleavages. Mass filtering between 200 and 4500 Da resulted in a digest mixture of 534 peptides. From this, a database was generated of all possible realistic peptide pairs linked together with BS 3 via their lysine residue, excluding lysines cleaved by trypsin. From this database of 16 554 BS 3 - linked peptide pairs, the mass list was extracted and taken as our virtual mass spectrum. Figure 3 shows the mass distribution of cross-linked peptide pairs, illustrating that most of the cross-linked peptide pairs have masses > 3000 Da. Each entry of this mass spec- trum was then matched against the complete theoret- ical set of peptides, including unmodified peptides, peptides that are modified by a partially hydrolysed cross-linker, intrapeptide cross-linking products and interpeptide cross-linking products. The match presents all peptide candidates for assignment of each mass in the spectrum as a function of the match mass window. It shows how many alternative peptide candidate assignments can be anticipated if the experimental mass spectrum is searched for cross-linked peptides at a specific instrumental mass accuracy. In Fig. 4 the results are summarized as the average number of pep- tide candidates for all 16 554 masses in the virtual spectrum, segmented in four mass ranges, vs. the mass window. As expected, the number of candidates comes down to almost 1 for all mass ranges if the mass win- dow is zoomed in to 0 p.p.m. Still, for about 15% of the mass entries an alternative candidate, beside the 0 100 200 300 400 500 600 700 800 900 1000 700 1700 2700 3700 4700 Mass (Dalton) Fig. 3. Calculated mass distribution of the BS 3 cross-linked peptide pairs in the tryptic digest of the HGF ⁄ SF Met protein complex allowing cross-links between all lysine residues. Computer-assisted mass spectrometric analysis of cross-links L. J. de Koning et al. 286 FEBS Journal 273 (2006) 281–291 ª 2005 The Authors Journal compilation ª 2005 FEBS authentic cross-linked peptide pair is given. Most of these alternatives are due to shifted tryptic cleavage places for the peptides with RK, RR, KK and KR sequence elements which will yield peptides with identi- cal elemental composition. Nevertheless, these alter- native assignments will pinpoint the same cross-link. When the mass window is zoomed out, the number of candidate peptides gradually increases to 2.5 for the low mass segment of m 1000–2000 Da. This number appears to level off if the window becomes broader than ±60 p.p.m. The gradual increase indicates that for this mass range the density of the candidate pep- tide masses is relatively low. The levelling-off points out that the distribution of the alternative candidate peptide masses around the mass of the authentic cross- linked peptide pair is about ±60 p.p.m. wide. This limited width is a consequence of the known discon- tinuous mass distribution of peptides [10]. For compar- ison, the gap between m ⁄ z 2000 and m ⁄ z 2001 is 500 p.p.m. For the highest mass segment of m 4000– 5000 Da, which covers most of the cross-linked pep- tides (see Fig. 3) the number of peptide candidates rap- idly increases with increasing detection mass window, while this number only begins to level off to about 10 outside ±90 p.p.m. This indicates that, for the higher mass range, the density of candidate peptides masses is much higher and the mass distribution width has increased to over ±90 p.p.m. For comparison, the gap between m ⁄ z 5000 and m ⁄ z 5001 is 200 p.p.m. The above virtual analysis reveals that instrumental mass accuracy is crucial. For mass accuracies better that 2 p.p.m., such as can be obtained with a high performance Fourier transform mass spectrometer, most of the identifications can be based on accurate mass with additional tandem mass spectrometric valid- ation. For mass accuracies better that 20 p.p.m. the identification is filtered to three or four possible candi- dates (see Fig. 4). This moderate number of alternative candidates should still allow unambiguous identifica- tion based on additional tandem mass spectrometric validation. It thus appears that a cross-linking approach to obtain structural information about an assembly as complicated as the HGF ⁄ SF-Met complex is feasible, especially with adequate fractionation of the peptide mixture, e.g. by reversed phase HPLC. To experimentally test this finding, we have carried out the mass spectrometric analysis of a cross-linked peptide mixture with at least the same or higher com- plexity as a reversed phase HPCL fraction of a peptide mixture derived from cross-linked HGF ⁄ SF-Met. We chose the NK1 domain of HGF ⁄ SF as the test protein for these experiments. The size of NK1, with 183 resi- dues adding up to almost 22 kDa, is roughly one-tenth of that of the entire HGF ⁄ SF complex and therefore of similar complexity as an average reversed phase HPLC fraction from the complex, assuming sorting of the peptides in at least 10 fractions. Moreover, a 3-D structure of the NK1 domain is available, so that cross-link identification can be validated. BS 3 was used to covalently cross-link amines within the NK1 sub- unit. Cross-linked and control preparations were sub- jected to SDS ⁄ PAGE. Subsequently, protein bands corresponding to the monomeric NK1 were treated with trypsin and the resulting peptide mixtures were mass analysed. The processed MS data were loaded into the virtualmslab program and matched with the corresponding virtual experimental results. A total of 13 peaks in the MALDI-TOF mass spectrum of the cross-linked NK1 digest could be related to cross-link- ing products. Some of these peaks were matched with one or two alternative assignments within a mass win- dow of ±30 p.p.m. corresponding to the mass accu- racy of our MALDI-TOF instrument. As anticipated, the relatively limited average number of possible pep- tide assignments found for the cross-linked NK1 is smaller than the average number of three candidate assignments found by the virtualmslab program for the entire HGF ⁄ SF-Met complex in a mass window of ±30 p.p.m. (Fig. 4). Based on the peptide assignments, a list of candi- date cross-links is given in Table 1. Four of these candidate cross-links have been confirmed by tandem mass spectrometric analyses of the corresponding cross-linked peptides using either ESI-QTOF or 0 1 2 3 4 5 6 7 8 9 10 0 20406080100 Mass accuracy (ppm) 1000-2000 Dalton 2000-3000 Dalton 3000-4000 Dalton 4000-5000 Dalton Average number of peptide candidates Fig. 4. Calculated average number of peptide candidates within a mass window at different mass ranges in a tryptic digest mixture of BS 3 cross-linked HGF ⁄ SF Met protein complex. (for details see text). L. J. de Koning et al. Computer-assisted mass spectrometric analysis of cross-links FEBS Journal 273 (2006) 281–291 ª 2005 The Authors Journal compilation ª 2005 FEBS 287 MALDI-TOFTOF (Fig. 5). These validated cross- links were fit into an available crystal structure of the protein (PDB: 1BHT) [21]. It was found that the measured distances between amino groups are com- patible with the calculated distance of 11.4 A ˚ which can be spanned by the BS 3 cross-linker (Fig. 6). Another candidate cross-linked peptide pair connect- ing K44 and K91 was assigned by virtualmslab. Tandem MS data allowed neither confirmation nor rejection of the assignment, still leaving open the pos- sibility that it corresponds to an unknown species. However, also this candidate cross-link fits nicely into the 3-D structure of NK1 (Fig. 6). The candidate cross-links in Table 1 suggest cross- linking between the N-terminal part of the protein [Y28 (N-terminus) and K34] with the region including K132, K137 and K170, which are close together. However, the first seven residues of the protein N-ter- minal region, specified as amino acids 28–34, are not resolved in the crystal structure and links to their amine groups cannot be drawn. This can be explained by assuming flexibility of the seven N-terminal resi- dues that might localize preferentially into this region. Alternatively, we may assume that K132, K137 and K170 have a relatively high reactivity towards the cross-linking agent, enabling them to trap the flexible amino terminus. The results imply that a single MALDI-TOF mass spectrum with moderate mass accuracy of an unfract- ionated proteolytic digest of a cross-linked protein can disclose significant information on the protein struc- ture. This opens new avenues in the computer assisted analysis of more complex biological assemblies, by combining advanced peptide separation techniques Table 1. Candidate cross-links found in NK1 using BS 3 as a cross- linking agent. The cross-link candidates are nominated by the VIRTUALMSLAB program by assigning peaks in the MALDI-TOF mass spectrum of the tryptic digest of cross-linked NK1 to the corres- ponding cross-linked peptides. Residue Y28 is the N-terminal resi- due in the construct used. Residue 1 Residue 2 Assigned peaks (m ⁄ z) Experimental mass discrepancy (p.p.m) 28 34 1191.65 d )13 28 34 1347.75 c +14 28 132 1805.93 c +4 28 137 1972.04 b )8 28 170 2171.02 b )18 34 47 1301.82 c )6 34 132 1357.77 b +1 34 137 1523.88 b )34 44 47 1127.70 a +3 58 60 1264.79 a )47 44 91 1523.56 b )20 132 170 2337.14 a )34 137 170 2503.25 a,e )15 a Identification of the corresponding assigned cross-linked peptide has been confirmed by tandem MS. b Assigned cross-linked peptide shows no alternative noncross-linked peptide assignments. c As- signed cross-linked peptide shows one alternative noncross-linked peptide assignments. d Assigned cross-linked peptide shows two alternative noncross-linked peptide assignments. e MS ⁄ MS data is shown in Fig. 5. A B Fig. 5. MALDI-TOF ⁄ TOF MS ⁄ MS analysis of a NK1 cross-linked peptide with m ⁄ z 2503.3. NK1 K137 is linked to NK1 K170 (see Table 1). (A) Structures of the cross- linked peptide. Observed fragment ions are indicated. (B) MALDI-TOF ⁄ TOF MS ⁄ MS data: fragment ion annotations correspond to the annotations in A. Computer-assisted mass spectrometric analysis of cross-links L. J. de Koning et al. 288 FEBS Journal 273 (2006) 281–291 ª 2005 The Authors Journal compilation ª 2005 FEBS with mass analysis, and by taking advance of the high mass accuracy of FTICR-MS. In conclusion, it appears that advanced mass spectro- metric studies on proteins can significantly be promo- ted by software tools, like the virtualmslab program, that can merge and tune mass spectrometric analysis with biochemical experiments. In contrast to other available software such as asap [10], ms2assign [9] and searchxlinks the unique multistage experiment editor in our program is a convenient tool to predict and optimize possible outcomes beforehand, which saves time in finding successful experimental strategies. asap and searchxlinks [11] have the order of events hard coded into the program and do not allow for multipass experiments. ms2assign has the unique feature to han- dle MS ⁄ MS data, which all other programs, including virtualmslab cannot. virtualmslab also allows for a large number of candidate proteins to be input in one single analysis. The recently described program cplm [12] is flawed, in the sense that it only candidates the match with the least mass deviation for a given observed mass, thus bypassing critical assessment and verification. The potential of our software program has been shown for the cross-link studies presented in this paper. However, the applications can be extended with other studies, including studies comprising entire cellu- lar proteomes. Experimental procedures Materials N-ethylmaleimide, HCl, and the gradient grade solvents: acetonitrile, ethanol and water were from Merck (Darms- tadt, Germany). The cross-linking agent BS 3 was from Pierce (Rockford, MA, USA). Ribonuclease A and lyso- zyme were from Sigma-Aldrich Chemie GmbH (Steinheim, Germany). Trypsin (sequencing grade) was from Roche Diagnostics GmbH (Mannheim, Germany). The NK1 fragment of HGF ⁄ SF was expressed in the yeast Pichia pastoris and purified from culture supernatants [22]. Cross-linking Protein cross-linking was carried out with BS 3 by incuba- ting the protein at a concentration of 0.5 mgÆmL )1 (23 lm) in a 50 mm Na-phosphate buffer, 150 mm NaCl, pH 7.4, with 1 mm cross-linker, for 30 min at room temperature. Cross-link spacer distances were approximated as described by Green et al. [23]. Preparation of peptides For cleavage at asparte [18], proteins (0.1 mgÆmL )1 ) were dissolved in 0.013 m HCl (pH 2) and incubated in a closed plastic Eppendorf vial, in an oven at 108 ° C for 2 h. Diges- tion by trypsin, both in the presence and absence of 10 mm NEM, was carried out in 100 mm NH 4 HCO 3 at 37 °C for 4 h using a protease : substrate ratio of 1 : 50 (w ⁄ w). In gel digestion by trypsin of Coomassie stained protein bands was carried according to published procedures [24]. Peptide mixtures were desalted and concentrated by ZipTip lC 18 pipette tips (Millipore Corporation, Billerica, MA, USA), washed with 0.1% (v ⁄ v) trifluoroacetic acid (TFA) or 1% (v ⁄ v) formic acid solution and eluted with a solution con- taining 50% (v ⁄ v) acetonitrile and 0.1% (v ⁄ v) TFA or 1% (v ⁄ v) formic acid. Mass spectrometry MALDI-MS analyses were performed with a TofSpec 2EC mass spectrometer (Micromass, Wythenshawe, UK) in the reflectron mode. Peptides were mixed in a 1 : 1 ratio Fig. 6. Space filled model of the NK1-domain of HGF ⁄ SF (1BHT). Four confirmed (solid lines) and one candidate cross-link (dashed line) are shown in this model. Measured distances between the linked amino acids are indicated. The different angles between the two views A and B are indicated by the arrows. The model was visualized using PYMOL (http://www.pymol.org). L. J. de Koning et al. Computer-assisted mass spectrometric analysis of cross-links FEBS Journal 273 (2006) 281–291 ª 2005 The Authors Journal compilation ª 2005 FEBS 289 (v ⁄ v) with a 10 mgÆmL )1 matrix (a-cyano-4-hydroxycin- namic acid) solution in a 50 : 50 (v ⁄ v) ethanol ⁄ acetonitrile mixture. For analyses, 0.5 lL of the mixture was spotted on a MALDI steel target plate and allowed to dry. MALDI ultra high resolution accurate mass analysis was performed with a 7T ApexQ FTICR-MS instrument (Bruker Dalton- ics, Bremen, Germany). For the analyses, an aliquot of 0.5 lL peptide mixture was mixed with a 10 mgÆmL )1 dihydroxybenzoic acid solution containing 0.1% (v ⁄ v) TFA in a 30 : 70 (v ⁄ v) acetonitrile ⁄ water mixture, spotted onto a Bruker Daltonics AnchorChip TM , and allowed to dry. MALDI MS ⁄ MS analyses were performed with TOF ⁄ TOF 4700 Proteomics Analyser (Applied Biosystems, Framing- ham, CA, USA). The sample (0.5 lL) was cocrystallized with an equal volume of matrix solution (7 mgÆmL )1 a-cy- ano-4-hydroxycinnamic acid dissolved in 50% v ⁄ v acetonit- rile ⁄ 0.1% TFA in water) and applied to the target. Prior to analysis, the instrument was externally mass calibrated with a standard peptide mixture, as outlined by the manufac- turer. Electrospray ionization MS and MS ⁄ MS analyses were performed with a QTOF mass spectrometer (Micro- mass). Peptide mixtures were directly infused from gold pla- ted nanospray tips (New Objective, Woburn, MA, USA) into the ESI-QTOF. Selected ions were collided with Argon in the hexapole collision cell, at a pressure of 4 · 10 )5 mbar measured on the quadrupole Penning gauge. Recorded spectra were internally mass calibrated on signals from trypsin autodigestion fragments and unambiguously identi- fied digest fragments from the proteins studied. Mass spec- tra were deconvoluted to lists of monoisotopic masses, which were analysed using the virtualmslab program. Suggested nomenclature [9,25] for fragment ions from cross-linked peptides has been used. Acknowledgements This work was supported by grants of the Netherlands Organization for Scientific Research (NWO), Chemical Sciences division (CW) and Regieorgaan Genomics. The ApexQ FTICR-mass spectrometer was largely funded by NWO-CW and the TofSpec 2EC and QTOF by NWO, Medical Sciences division. References 1 Aebersold R & Mann M (2003) Mass spectrometry- based proteomics. Nature 422, 198–207. 2 Cristoni S & Bernardi LR (2004) Bioinformatics in mass spectrometry data analysis for proteomics studies. Exp Rev Proteom 1, 469–483. 3 Back JW, de Jong L, Muijsers AO & de Koster CG (2003) Chemical cross-linking and mass spectrometry for protein structural modeling. J Mol Biol 331, 303– 313. 4 Geisler N, Schunemann J & Weber K (1992) Chemical cross-linking indicates a staggered and antiparallel protofilament of desmin intermediate filaments and characterizes one higher-level complex between protofi- laments. Eur J Biochem 206 , 841–852. 5 Hermanson GT (1996) Bioconjugate Techniques. Aca- demic Press, San Diego, USA. 6 Sinz A (2003) Chemical cross-linking and mass spectro- metry for mapping three-dimensional structures of proteins and protein complexes. J Mass Spectrom 38, 1225–1237. 7 Wong SS (1991) Chemistry of Protein Conjugation and Cross-Linking. CRC Press, Boca Raton, USA. 8 Borch J, Jorgensen TJ & Roepstorff P (2005) Mass spectrometric analysis of protein interactions. Curr Opin Chem Biol 9, 509–516. 9 Schilling B, Row RH, Gibson BW, Guo X & Young MM (2003) MS2Assign, automated assignment and nomenclature of tandem mass spectra of chemically crosslinked peptides. J Am Soc Mass Spectrom 14, 834–850. 10 Clauser KR, Baker P & Burlingame AL (1999) Role of accurate mass measurement (±10 ppm) in protein iden- tification strategies employing MS or MS ⁄ MS and data- base searching. Anal Chem 71, 2871–2882. 11 Wefing S, Schnaible V & Hoffman D (2001) SearchX- Links in http://www.searchxlinks/de. 12 Tang Y, Chen Y, Lichti CF, Hall RA, Raney KD & Jennings SF (2005) CLPM: a cross-linked peptide map- ping algorithm for mass spectrometric analysis. BMC Bioinformatics 6 (Suppl. 2), S9. 13 Wlodawer A, Svensson LA, Sjolin L & Gilliland GL (1988) Structure of phosphate-free ribonuclease A refined at 1.26 A. Biochemistry 27, 2705–2717. 14 Spackman DH, Stein WH & Moore S (1960) The disul- fide bonds of ribonuclease. J Biol Chem 235, 648–659. 15 Birchmeier C, Birchmeier W, Gherardi E & Vande Woude GF (2003) Met, metastasis, motility and more. Nat Rev Mol Cell Biol 4, 915–925. 16 Gorman JJ, Wallis TP & Pitt JJ (2002) Protein disulfide bond determination by mass spectrometry. Mass Spec- trom Rev 21, 183–216. 17 Li A, Sowder RC, Henderson LE, Moore SP, Garfinkel DJ & Fisher RJ (2001) Chemical cleavage at aspartyl residues for protein identification. Anal Chem 73, 5395– 5402. 18 Inglis AS (1983) Cleavage at aspartic acid. Methods Enzymol 91, 324–332. 19 Patterson SD & Katta V (1994) Prompt fragmentation of disulfide-linked peptides during matrix-assisted laser desorption ionization mass spectrometry. Anal Chem 66, 3727–3732. 20 Kim JS & Kim HJ (2001) Matrix-assisted laser desorption ⁄ ionization time-of-flight mass spectrometric Computer-assisted mass spectrometric analysis of cross-links L. J. de Koning et al. 290 FEBS Journal 273 (2006) 281–291 ª 2005 The Authors Journal compilation ª 2005 FEBS [...]... evaluation of the lengths of homobifunctional protein Computer-assisted mass spectrometric analysis of cross-links cross-linking reagents used as molecular rulers Protein Sci 10, 1293–1304 24 Shevchenko A, Wilm M, Vorm O & Mann M (1996) Mass spectrometric sequencing of proteins silver-stained polyacrylamide gels Anal Chem 68, 850–858 25 Pearson KM, Pannell LK & Fales HM (2002) Intramolecular cross-linking...L J de Koning et al observation of a peptide triplet induced by thermal cleavage of cystine Rapid Comm Mass Spectrom 15, 2296–2300 21 Ultsch M, Lokker NA, Godowski PJ & de Vos AM (1998) Crystal structure of the NK1 fragment of human hepatocyte growth factor at 2.0 A resolution Structure 6, 1383–1393 22 Chirgadze DY,... of proteins silver-stained polyacrylamide gels Anal Chem 68, 850–858 25 Pearson KM, Pannell LK & Fales HM (2002) Intramolecular cross-linking experiments on cytochrome c and ribonuclease A using an isotope multiplet method Rapid Comm Mass Spectrom 6, 139–159 FEBS Journal 273 (2006) 281–291 ª 2005 The Authors Journal compilation ª 2005 FEBS 291 . Computer-assisted mass spectrometric analysis of naturally occurring and artificially introduced cross-links in proteins and protein complexes Leo. modifications and cross-linking in protein mixtures, complexes, and assemblies. Proteins A single protein, a list of proteins from a mixture or from a protein complex