Molecular Dynamics Investigations on the Effect of ... - ACS Publications

J. Phys. Chem. B 2009, 113, 8983–8992

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Molecular Dynamics Investigations on the Effect of D Amino Acid Substitution in a Triple-Helix Structure and the Stability of Collagen V. Punitha,† S. Sundar Raman,† R. Parthasarathi,† V. Subramanian,*,† J. Raghava Rao,† Balachandran Unni Nair,† and T. Ramasami‡ Chemical Laboratory, Central Leather Research Institute, Council of Scientific Industrial Research, Sardar Patel Road, Adyar, Chennai 600 020, India, and Department of Science and Technology, New Mehrauli Road, New Delhi 110 016, India ReceiVed: October 1, 2008; ReVised Manuscript ReceiVed: April 24, 2009

Studies on the structure and stability of peptides and proteins during LfD configurational change are certainly important for the designing of peptides with new biological activity and protein engineering. The LfD amino acid (D AA) changes have been observed in aged proteins such as collagen. Hence, in this study, an attempt has been made to explore the effect of the replacement of L amino acid (L AA) in the model collagen-like peptides with D AA and the origin of structural stability (destability) has been traced using the molecular dynamics (MD) method employing the AMBER force field. Our results reveal that the substitution of D AA produces a large local disruption to the triple-helical structure. Formation of a kink (bulge) at the site of substitution is observed from the detailed analysis of MD trajectory. However, this local perturbation of kinked helix changes the direction of the helices and affects the relative orientation of the respective AA residues for helix-helix interaction, enough to affect the overall stability of the model collagen-like peptide. The destabilization energy per D Ala substitution is 7.87 kcal/mol, which is similar to the value for the GlyfAla mutation in collagen. Since the GlyfAla mutation is involved in genetic disorders such as osteogenesis imperfecta (OI), the LfD configurational change may produce a similar effect on collagen. 1. Introduction In nature, biological compounds are stereospecific. For example, the amino acids (AA) in proteins are exclusively found as L stereoisomers.1,2 Due to aging, the LfD configurational change has been observed in proteins such as collagen.3-6 The exposure to UV radiation and high-temperature conditions can also induce LfD conversion in proteins.7-9 These stereochemically modified proteins exhibit higher thermal stability and resistance to protease activity.8-10 The rate of conversion from one configuration to another is an intrinsic property of each amino acid. Typically, for aspartic acid (Asp), alanine (Ala), glutamic acid (Glu), leucine (Leu), and isoleucine (Ile), the rate varies respectively as Asp > Ala ) Glu > Leu ) Ile.11 Collagen is a fibrous protein that constitutes more than 25% of the protein content in the human body.12 It plays an important role in genetic disorders and diseases, wound healing, cell proliferation, and embryogenesis and acts as a drug carrier.13-22 Detailed sequence analysis of collagen reveals that it consists of three polypeptide chains (R) with the characteristic triplet sequence G-XAA-YAA, where G is glycine (Gly) and XAA and YAA can be any amino acid. Imino acids such as proline (Pro) and hydroxyproline (Hyp) are frequently found at the XAA and YAA positions. These features have profound implication on the formation of triple-helical structure and the close packing of the three chains about the common axis. In addition, there is one residue staggering between the three polypeptide chains. In order to avoid sterical hindrance, Gly can only be accommodated at every third position in the three chains. The three * Corresponding author. Tel: +91 44 24411630. Fax: +91 44 24911589. E-mail: [email protected] and [email protected]. † Central Leather Research Institute. ‡ Department of Science and Technology.

polypeptide chains adopt a polyproline II conformation due to the presence of imino acids in the XAA and YAA positions. The interchain hydrogen bonds (H-bonds), a water-mediated H-bond with the hydroxyl group of proline residues, and the weak interchain backbone of CR-H · · · O are the important interactions that stabilize the triple-helical structure of collagen.23-30 The ordered water structure around the triple helix also plays a vital role in conformational stability. Propensities for each L AA to adopt the triple-helical conformation have been investigated in detail using the host-guest method.31,32 Studies on the incorporation of Dresidues in the collagen-like polypeptide sequences are scarce. However, the LfD configuration change has been exploited in the field of de novo design of peptides and proteins.33-36 The effect of residue configuration can be readily understood with the help of Ramachandran maps for various AA residues. The maps for the D-residues are derived by inverting the corresponding classical L AA map through the origin. Most of the stereochemically allowed regions for the L-residues correspond to negative values of φ, while for the D-residues, the allowed regions correspond to positive values of φ. The D AA may be used in the de novo peptide design when positive φ values are required to form a desired structure.37-39 The use of D AA to provide helix termination signals and D Pro in the design of various secondary structural elements has been described. 37-39 It is found from the designing studies that the presence of D AA residues in the peptides enhances their stability and suppresses the protease activity.36,40-47 The inhibition of protease activity may be due to less accessibility of peptide bonds formed by the D AAs when compared to the bonds formed by the L AAs.8,9,48 Hence, several peptides containing D AA residues have been designed and synthesized. The biological activities of these heterochiral peptides, such as antimicrobial, antibacterial, and

10.1021/jp808690m CCC: $40.75  2009 American Chemical Society Published on Web 06/11/2009

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TABLE 1: Amino Acid Sequences of Model Collagen-like Peptidesa model name

sequence

GPO GpO GAO GaO GDO GdO

(Ace-(G-P-O)7-Nme)3 (Ace-(G-P-O)3-(G-p-O)-(G-P-O)3-Nme)3 (Ace-(G-P-O)3-(G-A-O)-(G-P-O)3-Nme)3 (Ace-(G-P-O)3-(G-a-O)-(G-P-O)3-Nme)3 (Ace-(G-P-O)3-(G-D-O)-(G-P-O)3-Nme)3 (Ace-(G-P-O)3-(G-d-O)-(G-P-O)3-Nme)3

a AAs are represented in the single letter codes. Upper and lower case letters represent L- and D-AA, respectively. The hydroxyproline residue is represented as O. The terminals are blocked with acetyl (Ace) and N-methyl (Nme) groups.

Figure 1. Rmsd of collagen-like peptides with respect to the initial structure.

anticancer, have been determined using various experimental methods.49-53 Computational modeling studies have also been undertaken to understand the biological activities of modified peptides.33-36 In leather science, there is always a need for the development of a unified theory for the stabilization of collagen in order to gain more thermal stability and resistance against enzyme activities. There have been several attempts made to increase the thermal stability of collagen and to inhibit the collagenase activity on collagen.54-57 Sequence-dependent thermal stability of collagen is evident from previous studies. Further, as mentioned earlier, LfD configurational changes have been observed in aged collagen.3-6 Therefore, it is worth exploring the effect of the incorporation of D AA residues in the structure and stability of collagen-like peptides. Recently, Dannenberg and co-workers have shown that the thermal stability of the collagen-like peptides increases upon the mutation of GlyfD Ala using quantum chemical calculations.34 It is found from their study that substitution increases the thermal stability of collagen, which is contrary to earlier findings. Hence, this observation calls for further investigation.

Punitha et al. Raines et al. have experimentally proved that such replacements cannot stabilize the triple helix in an aqueous phase.33 Further, a change in the environment from water to methanol stabilizes the triple helix. These observations raise several questions related to the roles of D AAs in the stabilization of aged collagen. In order to address the various questions, the host-guest approach has been selected. The propensity of various AAs to adopt collagen-like conformation has already been developed using this method.31,32 The structural basis for the propensity of various AAs to form stable triple-helical structures has been assessed using the host-guest method combined with the classical molecular dynamics (MD) approach.31,32 The same combination of methods has been used to understand the role of the sequence length (or the number of triplets) in the stability of collagen.58 The results reveal that at least five triplets are required to form the stable triple helix. Further analysis shows that the intermolecular structural rigidity of the imino acid residues, H-bonding, and water structure around the three chains of the triple helix play a dominant role in the structure, folding, and stabilization.58 Importance of the Lys ion pair (K ion pair) formation in the stabilization of collagen-like peptides has been probed.59 The results obtained from the comprehensive MD analyses using the host-guest approach clearly brought out the nature of the forces involved in the stabilization of the triple helix. Since the host-guest peptide approach combined with MD simulation provides valuable insight into the structure and stability of collagen, the same strategy has been used in this study to explore the effect of the replacement of a L AA by a D AA residue. In this study, the XAA residue of the central triplet of the (Ace-(G-P-O)7-Nme)3 has been replaced with D Pro (p), D Ala (a), and D Asp (d), which leads to the replacement of three L AA residues in the entire triple helix (upper and lower case letters represent L- and D-AA respectively, see Table 1). The following questions related to this replacement have been carefully addressed: (i) How does the collagen-like peptide sterically accommodate D AA? (ii) What are the changes in the triple-helical structure and its dynamics upon the incorporation of D AA? (iii) How does the D AA influence the stability of collagen-like peptide? 2. Computational Details Because of its tendency to form the most stable triple-helical conformation and highly occurring triplet in the collagen, (G-P-O)7 was chosen as the host peptide.58-67 Systematic experimental and theoretical studies on collagen-like peptides demonstrate that at least five triplets are essentially required to form a stable triple helix.58,68 Therefore, triple-helical models were built with a sequence having seven triplets per chain. The details of the different sequences considered in this investigation are given in Table 1. The host-guest peptides with D AA as guests were built using GENCOLLAGEN, which is a tool used to generate the three-dimensional coordinates of the triple helix for a given sequence.69 MD simulations were carried out using the AMBER 9.0 package,70,71 and the ff99SB force field was used for all the naturally occurring AAs.72 Hyp residues were treated using the force field developed by Park et al.73 Despite QM studies showing the marginal difference in the energy of L-AA and D-AA, they can be handled with the same force field because other inaccuracies in the force field energy discretion will shadow this effect. All of the simulations were carried out in an implicit solvent environment using the generalized Born model (GB). All simulations were carried out in the NVT ensemble. Temperature of the system was kept at 300 K using

Collagen Stability and

D

Amino Acid Substitution

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Figure 2. Average rmsd of each model from the initial structure and its fluctuation from the mean: (A) calculated for each triplet and (B) calculated for each position.

TABLE 2: Structural Properties of Model Collagen-like Peptides radius of gyration triple helix

rmsd [Å] single chain

triple helix

single chain

model

average

SD

average

SD

average

SD

average

SD


18.24 18.10 18.50 18.09 18.58 17.96

0.16 0.21 0.18 0.21 0.18 0.36

18.58 18.45 18.85 18.49 18.93 17.85

0.22 0.25 0.23 0.24 0.22 0.59

1.98 2.31 1.62 2.32 1.57 2.52

0.35 0.50 0.35 0.50 0.33 0.76

1.32 1.19 1.22 1.74 1.69 2.73

0.33 0.32 0.31 0.47 0.44 0.99

a Nose-Hoover thermostat. The nonbonded cutoff was fixed at 15 Å. The nonbonded atom pair list was updated for every 100 fs. The equilibration of the system was monitored by averaging the fluctuation in the potential energy, kinetic energy, and

temperature over time. All the systems were well equilibrated within 100 ps. After equilibration, a production run was carried out for 10 ns. The trajectories were saved for every 0.2 ps interval for further analysis. The analyses of the trajectories were

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Figure 3. Average diameter of the models.

TABLE 3: Difference in the Eigenvalues of the First Eight Normal Modes upon DAA Substitution normal modes

proline

alanine

aspartic acid

bending along x bending along y bending along z rotation along x screw along y stretching along x stretching along y stretching along z

-0.19215 -0.07115 -0.13359 -0.15428 -0.13973 -0.0339 -0.04076 -0.21396

–0.25747 –0.26372 0.35789 –0.10091 –0.08149 0.02467 –0.27669 –0.11009

–0.92233 –0.55925 0.01409 –0.97201 –0.68792 –0.86026 –1.41345 –1.26674

3. Analysis 3.1. Root-Mean-Square Deviation (rmsd). The rmsd of each residue of all of the peptides was calculated with respect to the initial conformation as a function of time using eq 1:

[ | N

rmsd(t) )

∑

1 r (t) - ri(0) N i)1 i

|]

1/2

2

(1)

where ri is the distance between atoms at time t and is compared with the distance between the same atoms at time zero, and N is the total number of backbone atoms. 3.2. Radius of Gyration. Radius of gyration is especially useful to measure the compactness of a structure. It was calculated from the trajectory by using eq 2:

Rg ) Figure 4. Ramachandran plot for the models (A) GPO, (B) GpO, (C) GAO, (D) GaO, (E) GDO, and (F) GdO. The blue and the green regions are allowed and generously allowed regions, respectively.

made using the PTRAJ package. To find the effect of D AAs in the collagen-like peptides, various parameters were obtained from the MD trajectories. The definitions of these parameters are provided in the following Analysis section.

( ) ∑ i

ri 2mi

||

∑ mi

1/2

(2)

i

where mi is the mass of atom i, and ri the position of atom i with respect to the center of mass of the molecule. The radius of gyration was computed with all the CR atoms present in the triple helix. 3.3. Diameter of the Triple Helix. Upon LfD configuration changes, the winding and unwinding of the collagen super helix


D



Figure 5. Intermolecular backbone Gly-N-H · · · XAA-O H-bond properties of the models.

TABLE 4: Geometry and Properties of New H-Bonds Observed in the Host-Guest Model Collagen-like Peptides donor

acceptor

H-bond properties

H-bond type

chain

residue no.

chain

residue no.

N-H · · · O N-H · · · O

C C

11 11

B B

11 12

N-H · · · O N-H · · · O N-H · · · O N-H · · · O

C C C A

11 11 11 11

B B A C

11 12 13 8

occupancy (%)

distance (Å)

angle (deg)

lifetime (ps)

47.03 27.24

2.92 3.21

139.09 138.44

3.20 2.40

23.57 18.23 16.51 12.84

3.06 3.16 3.04 3.10

139.78 153.83 155.10 136.95

2.80 3.80 10.00 2.40

GaO

GdO

is possible, which can be quantified from the diameter of the triple helix. The diameter of the circle encompassed by the three CR atoms of all three chains was calculated as given in eq 3. The triple-helix diameter (D) at the ith position was calculated as a function of time as

Di )

(

2

(a)(b)(c)

√(a + b + c)(b + c - a)(a + b - c)(c + a - b)

)

(3)

where a, b, and c are the distance between each CR atom of each chain. The average diameter of the triple helix was calculated using the eq 4:

Diameter ) average(D1, D2, ..., Di)

fitted trajectory data were used to construct a covariance matrix C as given in eq 5:

C )

(5)

where represents the mean. The superscript T indicates the transpose. An eigenvalue decomposition (or diagonalization) of the symmetric matrix C was performed to determine Λ, a diagonal matrix of eigenvalues, and T, a matrix of column eigen vectors forming a new orthonormal basis set (6), satisfying:

C ) TΛTT

(6)

(4)

where Di represents the diameter of a circle encompassed by the ith set of the three CR atoms of the chains. The average diameter of the triple helix was calculated over the entire trajectory. 3.4. Principal Component Analysis. To compute normal modes, coordinates for each time step were fitted to an initial structure to remove translational and rotational motion.74 The

A zero mean trajectory matrix, X, was constructed by subtracting from the coordinate vector for each time step to form the rows of X. The matrix of the projections of each time step onto each eigen vector, P, was obtained by multiplying the trajectory matrix, X, by T:

P ) XT

(7)

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Figure 6. Shannon information entropy for the imino acid puckering. (A) Proline and (B) hydroxyproline.

3.5. H-bond Analysis. The variation between the intermolecular H-bonds present in the three R chains of collagen with time was obtained from the trajectory using the geometrical criteria as given in eq 8:

{

1, ((d(Hi · · · Oi) e 3.5 Å) and

Hi ) (140o e angle (Oi · · · Hi - Ni) e 180o)) 0, otherwise

3.6. Calculation of Information Entropy of Imino Acids Ring Puckering. The pseudorotation angle of Pro and Hyp (five-member rings) was monitored as a function of time using the method developed by Westhof and Sundaralingam.75 The puckering values were converted to entropy using Shannon information entropy and the following equation:

(8)

n

H(X) ) E(I(X)) ) -

∑ p(xi) log2 p(xi)

(10)

i)1

where Hi is the possible ith backbone intermolecular H-bond in the triple helix. The occupancy of the H-bonds was determined according to the expression in eq 9:

Occupancy of H-bond Hiin %} ) Total no. of Hi ) 1state 100 (9) Total no. of conformation

[

]

where I(X) is the information content or self-information of X (puckering of imino acid), which is itself a random variable, and p(xi) ) P(X ) xi) is the probability mass function of X. 3.7. Cluster Analysis. The trajectories were subjected to cluster analysis based on the rmsd between each structure. The structures were grouped into five sets in such a way that the difference in rmsd values from one group to another is at least


D



Figure 7. Representative structure of different sets obtained from clustering the MD trajectory based on the rmsd.

1.2 Å. The recently implemented clustering algorithm in AMBER package was used.76 3.8. Relative Destabilization Energy. To estimate the changes in the energetics due to Lf D conversion, the relative destabilization energy (RDE) was computed using eq 11:

RDE ) ED,form - EL,form

(11)

where EL,form and ED,form represent the total energy of the model peptides with only L AA and D AA substitution. The total energy of average structures obtained from the MD simulation for the model peptides was used for the calculation. 4. Results and Discussion It is well-known fact that the structural stability of collagen is attributed to the polyproline II conformation.77-80 Any deviation from the polyproline II conformation can lead to structural destabilization in collagen. Hence, deviations in the various structural parameters have been compared to the most stable collagen-like peptide, ((G-P-O)7)3, which has a polyproline II conformation. The variation of rmsd versus time for various model collagen-like peptides is presented in Figure 1. It can be seen from the figure that the collagen-like model host peptide, consisting of only L AA residues ((G-P-O)7)3, has less structural fluctuations. On the other hand, the host-guest

peptides with the D AA residue have relatively higher fluctuations. The average radius of gyration and rmsd values for various models reinforce these findings. It would be interesting to explore the reason for the increase in the rmsd fluctuations and the decrease in the radius of gyration upon replacement of L AA with D AA. Further, it is of immense interest to compare how single chains respond to configurational change vis-a`-vis the response of the entire triple-helical unit. To understand this point, the radius of gyration of the entire triple helix and the individual chains have been calculated, and the results are presented in Table 2. Comparison of the various model peptide results reveals that each polypeptide chain fluctuates more than the triple-helix chain. This clearly indicates that the LfD configurational change first locally perturbs the individual chains and later the overall triple-helical structure. This local perturbation leads to changes in the polyproline II conformation of the individual chains. To gain finer details of the local structural changes, tripletwise (G-XAA-YAA) and triad-wise G(chain-1)-XAA(chainII)-YAA(chain-III) rmsd have been computed. The triplet-wise rmsd provides perturbations in the single polypeptide chain, whereas the triad-wise rmsd yields changes in the triple-helical conformation at each position along the length of the triple helix. These parameters are presented in Figure 2. It can be seen from Figure 2 that the introduction of any AA in the (G-P-O) stretches can influence the uniformity in the triple-helical

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TABLE 5: Calculated Occupancy of Model Collagen Peptides from Cluster Analysis

TABLE 6: Destabilization Energies (kcal/mol) of the Host-Guest Peptides from MD Simulation

model

set1

set2

set3

set4

set5


14.2 22.0 17.5 11.9 20.2 19.6

22.7 14.5 18.2 22.2 16.6 27.1

16.6 26.7 20.9 20.8 22.9 9.8

19.7 19.9 20.8 18.6 19.6 31.5

26.8 16.9 22.5 26.5 20.8 11.9

structure and increase the fluctuation in the neighboring triplets. D AA substitution in the host system seems to affect largely the conformation of each chain when compared to that of the triple helix. It can be noticed that D aspartic acid induces the largest deviations at the site of substitution when compared to the other residues. To quantify further, the position-wise diameters of various models were calculated. It can be seen from Figure 3 that an incorporation of nonimino L AA in the place of XAA causes the diameter of the triple helix to decrease by ∼0.3 Å (in the substituted regions only). This may be attributed to the decrease in the rigidity which arises due to the substitution of Pro residue (five-membered ring structure) and the associated increase in the rotational degrees of freedom about the backbone dihedral angle (φ).81 The diameter calculated from the X-ray structure reveals similar findings.81 It can be observed from the diameter calculation that incorporation of D AA in the triple helix increases the diameter up to 2.8 Å. This indicates that in the substituted regions, the polypeptide chains cannot come closer to maximize the Hbonding interaction, and this disrupts the formation of a uniform triple helix. This could be one of the reasons for the lower thermal stability of the D AA-containing collagen-like peptides. It can also be seen from Figure 3 that incorporation of D AA residues disrupts the local structure, and this effect propagates marginally along the length of the triple helix. With a view to gain insight into the changes in the polyproline II conformation, the Ramachandran maps for the average structures of all model collagen-like peptides have been obtained from the MD simulation. The results are plotted in Figure 4. The Ramachandran angles of the models with only L AA amino acids (except tail residues, which do not form the collagen-like conformation) fall into the collagen region on the map. It can be found that D proline has a positive ψ angle and a negative φ angle, and hence, it falls in the left-handed R-helical region on the map. It is interesting to note that D Ala (φ,ψ) occupies the negative and positive regions on the map and is probably the one D AA residue that has dihedral angles closer to the triplehelical conformation. Introduction of D aspartic acid disrupts the other polyproline conformation of other AA residues, and thus, (φ,ψ) values of the other AAs fall in the region away from that of collagen in the Ramachandran map. Raines et al. have also reported similar findings in the case of the substitution of D AA at the Gly position in the G-XAA-YAA repeats.33 They have shown that Ramachandran dihedral angles corresponding to D residues do not favor formation of triple-helical structure. These results further substantiate the conclusions drawn from the rmsd and radius of gyration analyses. The D AA in globular proteins enhances the structural stability, but this is not the case for collagen. Collagen has a unique 3-fold symmetry in the structure, and therefore, it has particular normal modes of vibrations. The origin of the destabilization in collagen can be understood with the help of normal-mode analysis. The important modes are bending, stretching, rotation, and screw. The substitution of D AA may

energy components

Pro

Ala

Asp

bond energy bending energy rotational energy total bonded energy

0.74 6.84 15.07 22.65

0.83 4.36 7.42 12.61

1.13 7.48 9.58 18.19

1-4 vdw energy vdw energy total vdw energy

–2.65 11.80 9.15

–0.82 0.57 –0.25

–1.37 5.22 3.85

1-4 electrostatic energy electrostatic energy total electrostatic energy

–12.42 78.46 66.04

–13.76 29.33 15.58

–20.02 50.76 30.74

solvation energy total nonbonding energy total destabilization energy

–64.27 10.92 33.58

–4.31 11.02 23.63

–19.92 14.67 32.86

produce changes in the magnitude of these modes, which can alter the stability of the structure. To study the normal modes, principal component analysis (PCA) on the MD trajectory has been carried out. The eigenvalues obtained from the PCA have been used to find the difference in the magnitude of each mode. The differences in the eigenvalues of first eight modes are reported in the Table 3. The negative signature of the eigenvalues indicates that D AA substitution enhances larger motions on these modes and leads to a less stable structure. As mentioned in the Introduction, the H-bonding interaction between the chains and the ordered puckering of imino acid rings stabilize the triple-helical structure.77 Therefore, it is necessary to find out the differences in the H-bonding interactions between the host and host-guest collagen-like models. The conventional G-N-H · · · XAA-O intermolecular backbone H-bonds between the chains have been obtained from the average structure and are presented in Figure 5. The results reveal that ordered patterning of H-bonding is observed in the host peptide and the host-guest peptides containing only the L AAs. Since the simulation has been carried out using the implicit solvation method, the properties of H-bonding interaction vary with respect to those in the explicit solvent environment. An 8% decrease in the occupancy of H-bonding, the elongation of H-bond distance by 0.2 Å, and the decrease in the H-bond angle (20°) have been observed. Although the strength of the H-bond interaction decreases slightly, it does not affect the overall stability of the triple-helical structure. It can be found that an increase in the diameter upon incorporation of D AA residues in turn decreases the H-bonding interaction between the chains. Further, the substitution of D AA residues influences the H-bonding pattern of the neighboring residues. The absence of H-bonds can be a crucial factor for the decrease in the thermal stability of the D AA containing the host-guest peptides.81 It was interesting to observe few noncanonical (unconventional) H-bonds82 in the collagen-like peptides with D AA. The geometrical parameters of noncanonical H-bonds are presented Table 4. Ordering of the imino acid ring in the preferred conformation during the simulation has been computed as Shannon information entropy. The Shannon information entropy values for Pro and Hyp residues are depicted in Figure 6. A decrease in the entropy value indicates the enhancement in the order. The substitution of D Pro increases the order in the ring conformation. However, in the Hyp, the same decreases cause a decrease in the ordered puckering, which destabilizes the structure and stability of the triple-helical structure.


D


To identify the most predominant conformation observed during the MD simulation, clustering analysis has been carried out on five sets of structures. Each set has at least 1.2 Å rmsd from the other set structures. The representative structures of various sets are shown in Figure 7, and their occupancies are listed in Table 5. These cluster analyses show that the predominant structure has a kinked region, which arises due to incorporation of D AA residues. To quantify the associated energetics involved in LfD configurational change, the relative destabilization energies for various peptides have been calculated, as explained in the Computational Details section. The destabilization energy and its components for various model peptides are presented in the Table 6. From Table 6, it can be found that the destabilization energy is higher for Pro and Asp substitutions, whereas it is less for Ala. These results indicate that the electrostatic repulsion is the major interaction that destabilizes the collagen-like peptides with D AA residues. Further, it can be noted that the destabilization energy per D AA substitution for Ala is ∼7.87 kcal/mol. This value is akin to that of GlyfAla mutation in collagen which is implicated in the disorder osteogenesis imperfecta (OI).83 Hence, replacement of LfD on the collagen structure may cause a similar effect on various species. 5. Conclusion In this study, MD simulations have been carried out on the model collagen-like peptides to understand the effect of D AA substitution on the structure and stability of collagen. The following observations have emerged from this investigation. 1. The presence of D AA in the triple helix tends to destabilize the triple helix. D AA substitution in the host system seems to affect largely the conformation of each chain compared to that of the triple helix. In particular, D Asp induces large structural changes at the site of substitution. 2. Destabilization occurs only in the local region where it is substituted and it propagates marginally along the length of the entire triple helix. These results are in accordance with the previous experimental and theoretical observations on the normal and mutated collagen-like peptides.81 3. The normal-mode analysis of various collagen-like peptides reveals that the presence of D AA enhances the fluctuation and tends to destabilize the collagen-like peptides. This effect is exactly opposite of the trend that has been observed in the case of globular proteins. 4. The absence of H-bonds in the D AA substituted positions and electrostatic repulsions are the predominant factor that destabilizes triple-helical conformation. 5. Cluster analysis reveals the formation of the kink (bulge) at the site of the D AA substitution. A similar finding has been observed in the X-ray structural studies on the GlyfAla mutated collagen-like peptides.83 6. D Ala substituted triple-helical model is more stable when compared to that of D Pro and D Asp. Acknowledgment. We acknowledge the DST and CSIR, Government of India, New Delhi, for financial support. V. P. and S. S. R. wish to thank the CSIR, New Delhi, for providing the Senior Research Fellowship. References and Notes (1) Lehninger, A. L.; Nelson, D. L.; Cox, M. M. Principles of Biochemistry , 2nd ed.; CBS Publications, Worth Publishers: New York, 1993; p 114. (2) Bonner, W. A. Chirality 2000, 12, 114.

J. Phys. Chem. B, Vol. 113, No. 26, 2009 8991 (3) Gineyts, E.; Cloos, P. A. C.; Borel, O.; Grimaud, L.; Delmas, P. D.; Garnero, P. Biochem. J. 2000, 345, 481. (4) Verzijil, N.; Degroot, J.; Thorpe, S. R.; Bank, R. A.; Shaw, J. N.; Lyons, T. J.; Bijlsma, J. W. J.; Lafeber, F. P. J. G.; Bayness, J. W.; Tekoppele, J. M. J. Biol. Chem. 2000, 275, 39027. (5) Cloos, P. A. C.; Fledelius, C. Biochem. J. 2000, 345, 473. (6) Bada, J. L.; Schroeder, R. A.; Protsch, R.; Berger, R. Proc. Natl. Acad. Sci. U.S.A. 1974, 71, 914. (7) Friedman, M.; Levin, C. E.; Noma, A. T. J. Food Sci. 1984, 49, 1282. (8) Friedman, M. J. Agric. Food Chem. 1999, 47, 3457. (9) Friedman, M. J. Agric. Food Chem. 1999, 47, 1295. (10) Axelsson, S. Med. Hypotheses 1998, 51, 47. (11) Bada, J. L.; Kvenvolden, K. A.; Peterson, E. Nature 1973, 245, 308. (12) Ramachandran, G. N.; Mitra, A. K. J. Mol. Biol. 1976, 107, 85. (13) Lutolf, M. P.; Hubbell, J. A. Nat. Biotechnol. 2005, 23, 47. (14) Beck, K.; Chan, V. C.; Shenoy, N.; Kirkpatrick, A.; Ramshaw, J. A. M.; Brodsky, B. Proc. Natl. Acad. Sci. U.S.A. 2000, 97, 4273. (15) Wang, A. Y.; Foss, C. A.; Leong, S.; Mo, X.; Pomper, M. G.; Yu, M. S. Biomacromolecules 2008, 9, 1755. (16) Lee, C. H.; Singla, A.; Lee, Y. Int. J. Pharm. 2001, 221, 1. (17) Yannas, I. V. Angew. Chem., Int. Ed. 1990, 29, 20. (18) Reddi, A. H. Tissue Eng. 2000, 6, 351. (19) Huynh, T.; Abraham, G.; Murray, J.; Brockbank, K.; Hagen, P. O.; Sullivan, S. Nat. Biotechnol. 1999, 17, 1083. (20) Thakar, R. G.; Ho, F.; Huang, N. F.; Liepmann, D.; Li, S. Biochem. Biophys. Res. Commun. 2003, 307, 883. (21) Koster, S.; Evans, H. M.; Wong, J. Y.; Pfohl, T. Biomacromolecules 2008, 9, 199. (22) Elsaid, K. A.; Chichester, C. O. Clin. Chim. Acta 2006, 365, 68. (23) Engel, J.; Bachinger, H. J. Top. Curr. Chem. 2005, 247, 7. (24) Treatise on Collagen; Ramachandran, G. N., Ed.; Academic Press: New York, 1964. (25) Rich, A.; Crick, F. H. J. Mol. Biol. 1961, 3, 483. (26) Bella, J.; Eaton, M.; Brodsky, B.; Berman, H. M. Science 1994, 266, 75. (27) Raman, S. S.; Parthasarathi, R.; Subramanian, V.; Ramasami, T. J. Phys. Chem. B 2006, 110, 20678. (28) Bella, J.; Eaton, M.; Brodsky, B.; Berman, H. M. Structure 1995, 3, 893. (29) Salem, G.; Traub, W. FEBS Lett. 1975, 51, 94. (30) Dai, N.; Wang, X. J.; Etzkorn, F. A. J. Am. Chem. Soc. 2008, 130, 5396. (31) Perisikov, A. V.; Ramshaw, J. A. M.; Kirkpatrick, A.; Brodsky, B. Biochemistry 2000, 39, 14960. (32) Chan, V. C.; Ramshaw, J. A. M.; Kirkpatrick, A.; Beek, K.; Brodsky, B. J. Biol. Chem. 1997, 272, 31441. (33) Horng, J.; Kotch, F. W.; Raines, R. T. Protein Sci. 2007, 16, 208. (34) Tsai, M.; Xu, Y.; Dannenberg, J. J. J. Am. Chem. Soc. 2005, 127, 14130. (35) Shah, N. K.; Brodsky, B.; Kirkpartrick, A.; Ramshaw, J. A. M. Biopolymers 1999, 49, 297. (36) Krause, E.; Bienert, M.; Schmieder, P.; Wenschuh, H. J. Am. Chem. Soc. 2000, 122, 4865. (37) Aravinda, S.; Sharmala, N.; Desiraju, S.; Balaram, P. Chem. Commun. 2002, 20, 2454. (38) Venkatraman, J.; Shankaramma, S. C.; Balaram, P. Chem. ReV. 2001, 101, 3131. (39) Aravinda, S.; Sharmala, N.; Roy, R.; Balaram, P. Proc.-Indian Acad. Sci., Chem. Sci. 2003, 115, 373. (40) Anil, B.; Song, B.; Tang, Y.; Raleigh, D. P. J. Am. Chem. Soc. 2004, 126, 13194. (41) Anil, B.; Craig-Schapiro, R.; Raleigh, D. P. J. Am. Chem. Soc. 2006, 128, 3144. (42) Fairman, R.; Anthony-CaChill, S. J.; DeGrado, W. F. J. Am. Chem. Soc. 1992, 114, 5458. (43) Mitchell, J. B. O.; Smith, J. Proteins 2003, 50, 563. (44) Valiyaveetil, F. I.; Sekedat, M.; MacKinnon, R.; Muir, T. W. Proc. Natl. Acad. Sci. U.S.A. 2004, 101, 17045. (45) Xie, C.; Prahl, A.; Ericken, B.; Wu, Z.; Zeng, P.; Li, X.; Lu, W. Y.; Lubkowski, J.; Lu, W. J. Biol. Chem. 2005, 280, 32921. (46) Imperiali, B.; Moats, R. A.; Fisher, S. L.; Prins, T. J. J. Am. Chem. Soc. 1992, 114, 3182. (47) Struthers, M. D.; Cheng, R. P.; Imperiali, B. J. Am. Chem. Soc. 1996, 118, 3073. (48) Liardon, R.; Friedman, M. J. Agric. Food Chem. 1987, 35, 661. (49) Fischer, P. M. Curr. Protein Pept. Sci. 2003, 4, 339. (50) Frau, J.; Price, S. L. J. Comput. - Aided Mol. Des. 1996, 10, 107. (51) Pohl, E.; Sheldrick, G. M.; Fisher, S.; Lackner, H. Acta Crystallogr., Sect. C: Cryst. Struct. Commun. 1994, 50, 100. (52) Marrifield, R. B.; Juvvadi, P.; Andreu, D.; Ubach, J.; Boman, A.; Boman, H. G. Proc. Natl. Acad. Sci. U.S.A. 1995, 92, 3449.

8992


(53) Wade, D.; Boman, A.; Wahlin, B.; Drain, C. M.; Andreu, D.; Boman, H. G.; Marrifield, R. B. Proc. Natl. Acad. Sci. U.S.A. 1990, 87, 4761. (54) Gayatri, R.; Sharma, A. K.; Rajaram, R.; Ramasami, T. Biochem. Biophys. Res. Commun. 2001, 283, 229. (55) Usha, R.; Raman, S. S.; Subramanian, V.; Ramasami, T. Chem. Phys. Lett. 2006, 430, 391. (56) Gayatri, R.; Rajaram, R.; Ramasami, T. Biochim. Biophys. Acta 2000, 1524, 228. (57) Gustavson, K. H. The Chemistry of Tanning Process; Academic Press, Inc.: New York, 1956. (58) Raman, S. S.; Parthasarathi, R.; Subramanian, V.; Ramasami, T. J. Phys.Chem. B 2008, 112, 1533. (59) Raman, S. S.; Vijayaraj, R.; Parthasarathi, R.; Subramanian, V.; Ramasami, T. J. Mol. Struct. (THEOCHEM) 2008, 851, 299. (60) Shah, N. K.; Ramshaw, J. A. M.; Kirkpatrick, A.; Shah, C.; Brodsky, B. Biochemistry 1996, 35, 10262. (61) Shah, N. K.; Sharma, M.; Kirkpatrick, A.; Ramshaw, J. A. M.; Brodsky, B. Biochemistry 1997, 36, 5878. (62) Fields, G. B.; Prockop, D. J. Biopolymers 1996, 40, 345. (63) Stultz, C. M. Protein Sci. 2006, 15, 2166. (64) Bachinger, H. P.; Bruckner, P.; Timpl, R.; Prockop, D. J.; Engel, J. Eur. J. Biochem. 1980, 106, 619. (65) Babu, I. R.; Ganesh, K. N. J. Am. Chem. Soc. 2001, 123, 2079. (66) Sacca, B.; Renner, C.; Moroder, L. J. Mol. Biol. 2002, 324, 309. (67) Kwak, A.; Capua, A. D.; Locardi, E.; Goodman, M. J. Am. Chem. Soc. 2002, 124, 14085. (68) Long, C. G.; Braswell, E.; Zhu, D.; Apigo, J.; Baum, J.; Broadsky, B. Biochemistry 1993, 32, 11688. (69) Huang, C. C.; Couch, G. S.; Pettersen, E. F.; Ferrin, T. E.; Howard, A. E. Pac. Symp. Biocomput. 1998, 349.

Punitha et al. (70) Klein, T. E.; Huang, C. C. Biopolymers 1999, 49, 167. (71) Pearlman, D. A.; Case, D. A.; Caldwell, J. C.; Seibel, G. L.; Singh, U. C.; Weiner, P.; Kollman, P. A. Comput. Phys. Commun. 1995, 91, 1. (72) Hornak, K. V.; Abel, R.; Okur, A.; Strockbine, B.; Roitberg, A.; Simmerling, C. Proteins 2006, 65, 712. (73) Park, S.; Radmer, R.; Klevin, T.; Pande, V. S. J. Comput. Chem. 2005, 26, 1612. (74) Mongan, J. J. Comput. - Aided Mol. Des. 2004, 18, 433. (75) Westhof, E.; Sundaralingam, M. J. Am. Chem. Soc. 1983, 105, 970. (76) Shao, J.; Tanner, S. W.; Thompson, N.; Cheatham, T. E. J. Chem. Theory Comput. 2007, 3, 2312. (77) Brodsky, B.; Persikov, A. V. AdV. Protein Chem. 2005, 70, 301. (78) Persikov, A. V.; Brodsky, B. Proc. Natl. Acad. Sci. U.S.A. 2002, 99, 1101. (79) Buevich, A. V.; Silva, T.; Brodsky, B.; Baum, J. J. Biol. Chem. 2004, 279, 46890. (80) Buevich, A. V.; Dai, Q. H.; Liu, X.; Brodsky, B.; Baum, J. Biochemistry 2000, 39, 4299. (81) Bella, J.; Eaton, M.; Brodsky, B.; Berman, H. M. Science 1994, 266, 75. (82) (a) Parthasarathi, R.; Subramanian, V. Hydrogen Bonding: New Insights; Challenges and AdVances in Computational Chemistry and Physics 3; Grabowski, S. J., Ed.; Kluwer: New York, 2006. (b) Parthasarathi, R.; Amutha, R.; Subramanian, V.; Nair, B. U.; Ramasami, T. J. Phys. Chem. A 2004, 108, 3817. (c) Parthasarathi, R.; Raman, S. S.; Subramanian, V.; Ramasami, T. J. Phys. Chem. A 2007, 111, 7141. (83) Beck, J.; Chan, V. C.; Shenoy, N.; Kirkpatrick, A.; Ramshaw, J. A. M.; Brodsky, B. Proc. Natl. Acad. Sci. U.S.A. 2000, 97, 4273.

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