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Biochemisches Institut, Universität Zürich, Zürich, Switzerland
Correspondence: Address reprint requests to A. Caflisch, Biochemisches Institut, Universität Zürich, Winterthurerstrasse 190, 8057 Zürich, Switzerland. Fax: 411-635-6862; E-mail: caflisch{at}bioc.unizh.ch.
| ABSTRACT |
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-value analysis of its transition state, represents a sort of testing table for computational investigations of protein folding. Here, parallel molecular dynamics simulations of the src-SH3 domain have been performed starting from denatured conformations. By rescuing and restarting only trajectories approaching the folding transition state, an ensemble of conformations was obtained with a completely structured central ß-sheet and a native-like packing of residues Ile-110, Ala-121, and Ile-132. An analysis of the trajectories shows that there are several pathways leading to the formation of the central ß-sheet whereas its two hairpins form in a different but consistent way. | INTRODUCTION |
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value is defined as the ratio 
GTSD/
GND, where 
GTSD is the change in free energy difference between the TSE and the denatured state induced by a mutation of residue i, and 
GND the change in free energy difference between the native state and the denatured state due to the same mutation. The
value is an indicator of the nativeness of residue i in the TSE: a
value of 1 indicates that residue i has a native-like structure in the TSE, whereas a value of 0 implies that, in the TSE, residue i is as unfolded as in the denatured state.
The TSE of chymotrypsin inhibitor 2 has been characterized by a synergistic interplay of experimental techniques (
-value analysis and NMR studies) and atomistic molecular dynamics (MD) simulations of protein unfolding at high temperature (Li and Daggett, 1996
). The transition state structures identified in the simulations are consistent with the available experimental data and were used for interpreting
values at atomic level of detail (Daggett et al., 1996
). The successful combination of experimental data and MD simulations allowed the description of the TSE of chymotrypsin inhibitor 2 as a state close to the native structure with an almost intact
-helix and a quite disrupted ß-sheet. Furthermore, a folding nucleus consisting of Ala-16 in the
-helix and Leu-49 and Ile-57 in the ß-sheet was identified (Daggett et al., 1996
).
Monte Carlo simulations of lattice models have also been used to investigate the TSE (Dinner and Karplus, 1999a
; Du et al., 1998
; Li et al., 2000
; Ozkan et al., 2001
). Their efficiency allows the validation of putative transition state conformations by calculating the transmission coefficient, which is the probability of a given structure to fold before it unfolds. The transmission coefficient should be close to 0.5 for conformations in the TSE. The main drawback of lattice models is the coarse description of the protein structure and interactions. Off-lattice simulations of a C
model with a Go potential have allowed the construction of the TSE of acylphosphatase from published
values (Vendruscolo et al., 2001
). Furthermore, they have shed light on some aspects of the folding of SH3 (Borreguero et al., 2002
; Ding et al., 2002
), including the role of the desolvation process (Cheung et al., 2002
); however, they do not allow the evaluation of the importance of non-native interactions.
The protein folding TSE arising from experiments and calculations performed on small two-state folding proteins is generally a distorted or expanded version of the native state (Daggett and Fersht, 2003
; Schymkowitz et al., 2002
), and little is known about the early phase of folding. Hence, the present study was motivated by the following question: is it possible to analyze the precritical phase of the folding process, i.e., from the denatured to the TSE? A positive answer to this question will also help in clarifying what the predominant driving forces are in protein folding. To address this issue, a possible approach is represented by atomistic MD simulation with an implicit representation of the solvent. Recently, MD simulation technique has allowed a statistically relevant analysis of the reversible folding of structured peptides (Ferrara and Caflisch, 2000
, 2001
), of the unfolding of small proteins at moderate temperatures (Gsponer and Caflisch, 2001
) even with explicit water molecules (Mayor et al., 2003
), and of the folding of the src-SH3 domain from the TSE (Gsponer and Caflisch, 2002
). The all-ß-domain src-SH3 is a two-state folder with a native state structure consisting of a ß-hairpin (formed by the terminal segments) packed orthogonally on top of a three-stranded antiparallel ß-sheet. Here, starting from the denatured state of src-SH3, we run loosely coupled parallel simulations which are periodically stopped and restarted from the snapshot closest to the experimentally determined TSE. Following previous works by Li and Daggett (1996
, 1994
) and Vendruscolo et al. (2001)
,
values are interpreted in terms of native-like side-chain contacts. The main difference between the present approach and that of Li and Daggett (1996
, 1994
) is that the latter employs a conformational cluster analysis to identify TSE structures along unfolding trajectories whereas in the present study we use experimental information to efficiently sample the transition from the denatured state to the TSE. The present approach differs from Vendruscolo et al. (2001)
in several aspects. Here, instead of considering only the C
positions, along with a Go-like force field and a Monte Carlo sampling, most of the atomic degrees of freedom are taken into account and a more accurate CHARMM empirical potential is used in the MD simulations. This allows us to extend the investigation to the pathways from the denatured state to the TSE. We anticipate that non-native contacts are observed using the present approach whereas they are penalized in the Go model. Furthermore, since the constraints defined by
-values enclose a considerable region of the phase space of the protein, accurate energetics may allow the sampling of only the parts of this region that are more relevant, excluding those parts that present unphysically high energies. The main drawback of the present approach is that the required simulation time is larger than in the case of the C
Go-model.
A large part of the secondary and tertiary structure of SH3, including the putative folding nucleus (Grantcharova et al., 2000
; Northey et al., 2002a
; Riddle et al., 1999
), assumes the correct three-dimensional conformation during the simulations presented here. The formation of the folding nucleus of SH3 is reported with atomistic detail, and comparison with experimental data (mutational studies) is presented.
| THEORY AND METHODS |
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![]() | (1) |
(r) = 2r) was used for the electrostatic interactions. The CHARMM PARAM19 default cutoffs for long-range interactions were used, i.e., a shift function (Brooks et al., 1983
-parameters: one for carbon and sulfur atoms (
C,S = 0.012 kcal mol-1 Å-2), and one for nitrogen and oxygen atoms (
N,O = -0.060 kcal mol-1 Å-2) (Ferrara et al., 2002
-parameters do not have a temperature-dependence, inasmuch as this was shown to be weak in the 330360 K range by a previous implicit solvent model calibrated on amino acid hydration free energies (Elcock and McCammon, 1997
-parameters have been used in MD simulations of folding of structured peptides (
-helices and ß-sheets) ranging in size from 15 to 31 residues (Ferrara and Caflisch, 2000
60 residues (Gsponer and Caflisch, 2001
1 ns (Ferrara et al., 2000
0.1 µs, experimentally, Eaton et al., 2000
10 ns (Ferrara et al., 2000
1 µs, Eaton et al., 2000
100 ns (Cavalli et al., 2002
10 µs, De Alba et al., 1999
Denatured conformations
The unfolded state ensemble consists of a large number of different conformers (Cavalli et al., 2003
). Hence, it is not possible to sample it at equilibrium either at very high temperature or at physiological temperatures. It was decided to adopt as representative of the denatured state conformations obtained at 550 K to remove any memory of the native state. Indeed, the denaturation of the protein at transition temperature would have shown very long unfolding times. Denatured conformations of the src-SH3 domain were obtained by two 6-ns MD simulations at 550 K started from the folded state. Twenty structures were selected with a very low number of native contacts (<5%) and all
-angles in trans conformation.
Characterization of TSE
For a given conformation
and amino acid i, a
-value can be approximated (Gsponer and Caflisch, 2002
; Li and Daggett, 1994
; Vendruscolo et al., 2001
) by
![]() | (2) |
is the number of contacts of the ith side chain that are present for more than two-thirds of the simulation time of a control 6-ns run at 300 K from the folded state (Gsponer and Caflisch, 2001
) is the number of native contacts in the conformation
. The distance from the experimentally determined TSE for a given conformation
is defined using the
rmsd (Gsponer and Caflisch, 2002
![]() | (3) |
is the experimentally determined
-value for residue i, M
is the number of terms in the sum, and the sum is extended to a selected subset of mainly hydrophobic residues (see below).
Loosely coupled MD simulations (LCMD)
A computational protocol was developed to run multiple MD simulations and continue only those that approach the TSE. An LCMD run (Fig. 1) consists of a sequence of MD simulations starting from an evolving parent conformation defined in the following way:
rmsd is localized and its
rmsd is compared with the
rmsd of the current parent conformation. The new conformation is accepted and replaces the current parent conformation with a probability that follows a Metropolis-like ansatz,
![]() | (4) |
rmsd of the parent conformation is observed over a total simulation time of 150 times the length of the single MD simulation.
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rmsd. The time length of the MD simulations in a LCMD run was fixed. Values of 0.02 ns, 0.05 ns, 0.1 ns, 0.2 ns, 1 ns, and 10 ns were used in different LCMD runs. The continuous segments of trajectory leading from the initial parent conformation to the last accepted parent conformation define the LCMD trajectory.
The LCMD runs were performed using two subsets of
in Eq. 3. The first one (B) is the same as in Gsponer and Caflisch (2002)
, and the second one (A) is a modified version of B taking into account experimental insights on the importance of particular residues in the folding process, not necessarily directly contained in their
-values. The
-values of the diverging turn were artificially increased by 0.3 units in A to take into account the presence of structure in the denatured state of these residues (Riddle et al., 1999
). Moreover, a
exp = 0.8 for Ile-110 was introduced to take into account the relevance of this residue in the folding nucleus of fyn-SH3 domain that has a sequence and a structure very similar to src-SH3 (Northey et al., 2002a
). Pro-133 was introduced into the
rmsd calculation because it is hydrophobic and buried and has a high
-value (Riddle et al., 1999
). Ser-123 and Thr-126 were also added to the
rmsd definition because they form a network of hydrogen bonds in TSE also present in the native state (Grantcharova et al., 2000
).
The LCMDs were run on two Beowulf clusters equipped with 64 MP1800+ and 64 MP2100+ Athlon processors, respectively. The number of parallel jobs for each LCMD run ranged from 10 to 30.
Identification of structures close to the TSE
Fifty-four LCMD runs were performed with different starting structures, MD simulation time lengths, and values of Tini for a total of
20 µs of simulation time. In each simulation the value of the
rmsd parameter was monitored. The final structures of the LCMD trajectories where the
rmsd decreased below a threshold of 0.2 (Gsponer and Caflisch, 2002
) and 0.25, for
rmsd subsets B and A, respectively, constitute an ensemble defined as MDTSE (Table 1), i.e., the ensemble of structures having minimal
rmsd (Gsponer and Caflisch, 2002
; Vendruscolo et al., 2001
). Most of the residues of these structures have
calc close to
exp.
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| RESULTS |
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rmsd decrease were observed in the LCMD runs. Eight of them led to MDTSE conformations (Table 1). The other runs led to conformations that represent local minima of the
rmsd from which the system could not escape during the course of the simulations. Some of these conformations show a small fraction of the features of MDTSE but the overall agreement with experimental TSE is low, as evidenced by
calc
exp. Thus, in the following we focus only on the MDTSE conformations. The
averaged over the eight MDTSE conformations for the 21 mainly hydrophobic residues used in the subset A
rmsd definition have a linear correlation coefficient
of 0.93 with the corresponding
(Fig. 2 a). The
for
and
considering 34 residues (both hydrophobic and hydrophilic) is 0.77 (Fig. 2 b). The cross-validated correlation coefficient
cv for the 13 residues not used in the definition of
rmsd A is 0.68. The main outlier is represented by His-122, which is partially solvent-exposed in the x-ray structure of src-SH3. Leaving out His-122 results in a
= 0.88 for 33 residues and
cv = 0.71 for 12 residues not included in
rmsd calculation. The major deviations from the x-ray structure in the MDTSE ensemble are localized on the C-terminus (residues 134140) and the N-terminal segment up to the end of the RT-loop (residues 85105) (Fig. 2 c). The central ß-sheet (residues 106133) shows smaller deviations from the x-ray conformation than the other parts of the protein. The RMSD from the x-ray structure of this portion of the protein is 2.3 ± 0.5 Å averaged over the MDTSE ensemble (the values in Fig. 2 c for the ß2-ß3-ß4 are larger because the superposition is optimized over all of the protein).
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-value analysis and previous observations for the TSE of src-SH3 (Gsponer and Caflisch, 2002
rmsd calculation present relatively large RMSD for the central ß-strand with respect to the x-ray structure and two of them show also a relatively looser packing of the nucleus residues than the native state (Table 1). In these structures the ß2-ß3 strand has more than one-half of the native contacts formed, whereas the ß3-ß4 strand is less structured. These features are in contrast with data from glycine loop insertion and disulphide cross-link experiments (Grantcharova et al., 2000
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rmsd decreases along these pathways according to the definition of the LCMD procedure. Along each LCMD trajectory the RMSD of the residues in the central three-stranded ß-sheet (residues 106133) has a high correlation with the
rmsd (correlation coefficient of 0.8) in agreement with the fact that the TSE of src-SH3 domain is mainly structured in the central three-stranded ß-sheet (Riddle et al., 1999
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The main purpose of the present work was to investigate the early events of folding. Nevertheless, to test the robustness of the approach two LCMD runs were started from the native structure. In the final conformations obtained from these simulations, the average RMSD from x-ray structure, radius of gyration, and fraction of native contacts (3.6 Å, 10.7 Å, and 0.6, respectively) show that they are similar to the TSE conformations obtained from unfolding simulations presented in Gsponer and Caflisch (2002)
. Since these LCMD simulations were started from the native state, the final conformations are more native-like than the MDTSE. The agreement with
exp is as good as for MDTSE (average set A
rmsd = 0.07). These simulation results suggest that the ensemble that minimizes the
rmsd (and, thus, is in agreement with TSE determined by
exp) spans conformations with different degrees of nativeness.
In 40 of the conventional MD simulations started from MDTSE conformations (Table 2) the average C
-RMSD from the x-ray structure decreased >1 SD below the initial value. On the contrary, in 68 simulations this value increased 1 SD above the initial value. In the 68 remaining simulations, the average RMSD did not significantly increase or decrease. In particular, in the simulations from r-4 and r-5, the ß2-ß3-ß4 sheet was conserved on average whereas the other parts of the protein acquired a more native-like conformation. More fluctuations were seen in the other simulations. In 95% of the simulations from r-5 and in 25% of the simulations from r-1 the total RMSD from the x-ray structure reached values <6.0 Å and in some cases between 5.0 and 4.0 Å. Notwithstanding the fact that a fraction of the trajectories approached the native conformation, none of them reached the folding conditions as defined in Gsponer and Caflisch (2002
; i.e., RMSD < 2.5 Å and Q > 0.875). As a comparison, an average RMSD of 2.9 ± 0.2 Å was observed in a 40-ns 300-K simulation started from the x-ray structure.
| DISCUSSION |
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calc
exp (Riddle et al., 1999
-values are reproduced with high accuracy even for most of the residues that were not used in the definition of
rmsd. The degree of accuracy is similar to that previously achieved along unfolding trajectories at 375 K (Gsponer and Caflisch, 2002
-values >1.0 in the n-src loop region that may be due to non-native contacts made by those residues in TSE (see below). The packing of the residues forming the folding nucleus of SH3 domain (Northey et al., 2002a
-values. The disorder in these segments may be overestimated with respect to TSE conformations, as suggested by the comparison of the experimental entropy loss after the disulphide cross-link of the RT-loop base with theoretical estimations that reveal nonrandom-coil structure in denatured RT-loop (Grantcharova et al., 2000
rmsd, is very similar. Recent biased sampling simulations of src-SH3 with explicit water (Guo et al., 2003
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-value analysis (Grantcharova et al., 1998
The two hairpins form in different ways: in the case of the ß3-ß4 hairpin, the formation of local contacts at its tip, which are favorable for entropic reasons, precedes those at the distal end of the hairpin. This picture is not in contrast with the proposed looping of the ß3-ß4 hairpin in its middle (Grantcharova et al., 2000
; i.e., disorder in the packing of side chains in the middle of the hairpin), because the progressive ordering of the backbone is followed by a partial ordering of the corresponding side chains that is compatible with the experimental
-values (Grantcharova et al., 1998
). On the other hand, the ß2-ß3 hairpin collapses more cooperatively than ß3-ß4 even if the earliest proximal contacts are non-native. The native contacts close to the tip (i.e., the native n-src loop) progressively substitute the non-native contacts after the initial collapse. In this case the energy decrease due to the early hydrophobic collapse of Leu-108, Ile-110, and Val-111 on strand ß2, and Leu-120 and Ala-121 on strand ß3, as opposed to the entropy increase, may lead the process. The looping of this hairpin is evident even at the backbone contact level; however, it takes place at the tip and not in the middle of the hairpin, like in the ß3-ß4 (see above and Grantcharova et al., 2000
). The looping in the middle of the hairpin was also observed for one of the hairpins in protein L (Kim et al., 2000
) and has been proposed as a common theme in protein folding (Grantcharova et al., 2000
). The present results show that the looping may also occur at the tip of the hairpin and non-native contacts may play a relevant role in that case. The importance of the non-native contacts in initiating the formation of the ß2-ß3 hairpin could explain the experimental
-values >1.0 (Grantcharova et al., 1998
) for many of the residues of the n-src loop and agrees with the suggestion that non-native contacts may speed up the folding process (Li et al., 2000
).
A detailed description of the formation of the folding nucleus of the src-SH3, that is, the precritical phase of the folding process, has been addressed in this work. Clearly, validation is needed and this might require novel experimental approaches (Schymkowitz et al., 2002
).
The role of the constraints in determining the pathways to TSE can be inferred by comparing the results obtained with the two sets A and B. Set A contains constraints on the
-value of 22 residues whereas set B only involves 18 residues. Also, the
exp of residues in the diverging turn of set A have been increased implying a further increase of the number of constraints (i.e., more native contacts are required to lower the
rmsd). Some LCMD runs with set B reached false-positive TSE structures (i.e., structures where important features of the TSE are not fully present, as shown in the Results section); yet, the runs that reached TSE structures consistent with experimental data (r-1 and r-2, see Table 1) show patterns of formation of the folding nucleus of src-SH3 similar to those obtained with set A (Figs. 4 and 5). In addition, the length of the single MD simulations in LCMD runs, that is, the frequency used to enforce the constraints along the run, does not affect these patterns or the total simulation time needed for the formation of the three-stranded ß-sheet (Fig. 4). From this comparison, it would emerge that the constraints only affect the efficiency of the LCMD to reach TSE conformations, whereas the main characteristics of the observed pathways seem to be independent from them.
The presence of parallel microscopic flow processes has also been indicated as a possible explanation of abnormal
-values (Ozkan et al., 2001
). At the light of such interpretation of our data, the mutation of residues in the n-src loop with abnormal
-values may shift the equilibrium wild-type sequence of formation of the two ß-hairpins in one direction or the other, favoring, for example, the early formation of ß2-ß3 and a later formation of the ß3-ß4 hairpin. Simulations with mutants of the src-SH3 domain would allow us to rule out this hypothesis, but this is beyond the scope of the present work. The different packing of residues in the native and in the transition state is another possible explanation of the abnormal
-values (Northey et al., 2002b
).
The conventional MD simulations started from the MDTSE conformations show that the central ß-sheet, characteristic of the TSE ensemble, does not vanish as the pressure on the decrease of the
rmsd is released. This allows us to conclude that the bias introduced through the LCMD procedure does not strongly affect the dynamics of the protein by forcing the sampling of very high free energy regions. These and the pfold data may also indicate that the saddlepoint in the free energy landscape representing the TSE of this protein with this force field is quite flat, and does not allow the system to fold or unfold within the timescales that have been sampled in the present worksimilar to findings in the case of acylphosphatase (Paci et al., 2002
). This fact is not in disagreement with the results presented in Gsponer and Caflisch (2002)
because in that case very strict conditions were assumed to define the unfolded state (i.e., RMSD > 7.0 Å and Q < 0.375). Indeed, these conditions are already met by several of the MDTSE structures, whereas during the unbiased MD simulations that started from these conformations the trajectories approach the native structure passing through those thresholds. The simulation results indicate that, within the region of phase space where
rmsd is low, LCMD allows us to reach locally more stable conformations (i.e., with higher diffusion times) than unfolding simulations. The different pfold of MDTSE and TSE structures obtained from unfolding simulations could also depend on the force field that might not be accurate enough to reproduce the pfold of the analyzed conformations (Paci et al., 2002
). Statistical variations may also determine this difference; however, 10 simulations that clearly reach well-defined unfolded or folded states like in Gsponer and Caflisch (2002)
are sufficient to estimate pfold with a maximal standard deviation of the order of 0.16 as computed from a binomial distribution.
Compared to the distributed computing approach to protein folding pioneered by Pande's group (Shirts and Pande, 2001
; Snow et al., 2002
), the LCMD procedure presents a key difference that addresses the major problem inherent to that method (Fersht, 2002
; Paci et al., 2003
). In LCMD, only simulations that approach the experimentally determined transition state are continued, so that the system has a minor chance of exploring minor pathways and statistically irrelevant regions of the conformational space. On the other hand, LCMD is possible only if the TSE of the system under study has been experimentally probed with
-value analysis. The diversity found in the folding pathways of the central ß-sheet of the src-SH3 domain offers an a posteriori validation of the LCMD procedure; different folding pathways are explored but they reach TSE conformations consistent with experimental data. Furthermore, the independence of the rate of central ß-sheet formation from the time length of the individual MD simulations indicates that the loose coupling of simulations does not apparently affect the LCMD runs.
| ACKNOWLEDGEMENTS |
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This work was supported by the Swiss National Competence Center in Structural Biology and the Swiss National Science Foundation (grant No. 31-64968.01 to A.C.). J.G. is a fellow of the Swiss MD-PhD program (grant No. 3236-057617).
Submitted on July 29, 2003; accepted for publication October 22, 2003.
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