Evaluation and refinement of all-atom force fields for reproducing collagen structure and dynamics

Abstract

Collageneous protein domains, characterized by the XYGly sequence repeat motif, trimerize and fibrilize to serve as the molecular skeleton of extracellular matrices and their mutations are frequently associated with disease. Because of experimental challenges in studying the effect of mutations on the properties of collagen, accurate atomistic Molecular Dynamics (MD) simulations are an invaluable tool. We evaluate the accuracy of state of the art MD force fields using recent experiments on model peptide homotrimers composed of Proline-4(R)-Hydroxyproline-Glycine (POG) repeats: the stabilizing POG motif appears with high frequency in several types of collagen. POG-repeats are used as templates to explore the role of amino acid substitutions in modulating collagen structure. We have compared the structure and dynamics of collagen POG₁₀ homotrimers with various force fields from the CHARMM, AMBER, and GROMOS families together with various water models to aggregated crystal structure data, NMR data, and SAXS form factors. Of the tested force fields, we find those from AMBER and CHARMM give an acceptable description of collagen structure. AMBER force fields accurately reproduce collagen dihedrals, side chain torsions, amide spin relaxations, and SAXS data. CHARMM force fields were found to systematically shift backbone $\varphi$ and $\psi$ dihedrals, adopt incorrect side chain torsional angles, and overstructure POG₁₀, increasing the persistence length relative to POG₁₀ in AMBER force fields. However, by scaling the CHARMM36 CMAP terms of all dihedrals in POG₁₀, we are able to capture a level of accuracy relative to experiment similar to that for the AMBER force fields. We suggest the use of AMBER ff99sb force fields or CHARMM36 with CMAP terms involving Pro, Hyp, and Gly rescaled by a factor of 1/2 (which we term CHARMM36mGP) for modeling collagen-like peptides.

INTRODUCTION

Collagen proteins are principally responsible for determining the structure and mechanical properties of tissues(1). Long, repeating XYGly-repeat domains, up to lengths of 1017 residues in the fibrillar collagens(2), are the defining characteristic of collagen proteins. The X- and Y-positions in the motif are red occupied by Proline and 4(R)-Hydroxyproline (Hyp; O), respectively(3, 4). Collagen proteins comprise approximately 15% of all proteins in mammals by molar ratio, and as much as 50% of protein in tendons, as recently quantified in healthy mice by measuring Hydroxyproline content(5). XYGly-repeat domains of three collagen strands fold into a single triple helix in the Endoplasmic Reticulum, chaperoned by HSP47, prior to secretion and incorporation into extracellular matrices(6, 7). The collagen triple helix structure features each protein in a polyproline-II (all-trans $\omega$-angle) secondary structure, with Glycine alpha carbons sitting near the center of the helix (Fig. 1.A)(8). The triple helix is stabilized by hydrogen bonds formed between Glycine alpha hydrogens and backbone oxygens at the X-position of adjacent strands (Fig. 1.B)(9). Substituting Glycine with a different amino acid interferes with triple helix folding and reduces triple helix stability, such that mutations of Gly in XYGly repeat domains result in either nonviable or malformed tissues associated with various diseases(10, 11). Substitutions of X- or Y-position amino acids from Pro or Hyp generally do not break the triple helix, although these decrease the thermal stability of triple helices with the noted exception of charged residues that form intra-helix salt bridges that are a popular tool employed in collagen-like peptide design(12).

Figure 1:

(A) Structure of the POG₁₀ triple helix studied via MD in this investigation with Pro, Hyp, and Gly in orange, purple, and blue respectively. (B) Sequence of three acetylated and amidated POG₁₀ aligned by relative displacement along their principal axis, with canonical Gly-Pro hydrogen bonds indicated in blue. Lighter gray sequences represent a periodic image of the trailing (top) and leading (bottom) strands in the triple helix to visualize the location of the hydrogen bonds of the sixth POG triplet as an example. (C) Proline can be hydroxylated at several different sites, though 4(R) is observed as the canonical product of its hydroxylation (purple). The omega angle (orange) of all Pro and Hyp are in the trans form in the triple helix, and this cis-trans isomerization is the rate limiting step in triple helix folding. The Pro and Hyp rings exhibit a pucker, presenting the $\text{C}\gamma$ above or below the plane of the ring. This pucker can be measured by the ring dihedrals, among which we choose to evaluate ${\chi }_2$. (D) View of POG₁₀ triple helix down the principal axis, demonstrating the positions of Gly in the helix center.

Experimental investigations of collagen structure, dynamics, and mechanics have long been hampered by significant experimental challenges. These include the ∼ 300-nm length of collagen proteins, the tens of hours-long intrinsic time scale for collagen folding due to the long time scale of cis-trans isomerization in Pro and Hyp (Fig. 1.B)(13, 14), (in vivo this process is accelerated by proline isomerases and collagen-specific chaperones) and the challenges of obtaining and purifying samples of triple helical collagens(15). Because POG-repeat domains stabilize the triple helix even in short, 30-residue long collagen-like peptides, POG-repeat sequences have been used as a “host” for “guest” substitutions, made to residues in the center of the sequence, to explore the effect of different sequences on the structure and thermal stability of the collagen triple helix(3). As such, the majority of biophysical measurements of the structure and dynamics of collagen-like peptides have been made in the context of the POG-repeat sequence.

All-atom molecular dynamics (MD) simulations avoid the experimental limitations to preparing samples and measuring structure, dynamics, and mechanics, but depend on the accuracy of the underlying force field or energy function, as well as the ability to sample events of interest which may occur on long time scales. All-atom MD simulations of collagen(16–24) have thus far focused principally on computationally accessible simulations of POG-repeats, since the first simulations of the collagen triple helix in 1976(25). However, even modern protein force fields have been developed and validated mainly for their ability to reproduce the structure of single-domain folded globular proteins. In particular, although collagen simulations are exquisitely sensitive to parameters for Pro and Gly residues, these parameters have less impact on globular proteins as they are less frequent and often serve as structure-breakers in protein folds. Despite this, the current body of work employing MD simulation to investigate collagen-like peptide structure has made the assumption that current protein force fields would achieve a decent reproduction of the conformational ensemble of collagen provided the triple helical state was stable in simulations. With the advent of complex simulations of fibril cross-sections featuring full-length collagens(26, 27), it is crucial to ensure that the most accurate force fields are being used when performing large size and time scale calculations. Owing to the wealth of experimental data characterizing the POG-repeat triple helix structure and dynamics, it is possible to confidently determine the best MD force field for modeling collagen in general.

Here, we utilize collagen-like peptide crystal structures, the Pro and Hyp ring propensities for endo- or exo-state pucker as measured by NMR (Fig. 1.C)(28), the dynamics of collagen as characterized by NMR ¹⁵N spin relaxation(29), and the shape of the triple helix conformational ensemble as characterized by SAXS experiments(30, 31), to validate the ability for several MD force fields and water models to reproduce the structure and dynamics of homotrimeric POG₁₀ with quantitative accuracy. Among these force fields and water models tested, AMBER ff99sb with the TIP4P/2005 or OPC water models achieve the highest accuracy. A systematic error in the backbone dihedrals observed in simulations using the CHARMM22+CMAP and CHARMM36 force fields was corrected by changing the CMAP term strength, bringing CHARMM36 in line with the accuracy of ff99sb and achieving better performance in reproducing J-couplings for the GPGG peptide, originally used to validate CHARMM36. GROMOS force fields did not maintain the structure of the triple helix at the microsecond time scale, either partially or completely unfolding. This work enables future work on collagen using all-atom MD simulations with confidence in their quantitative accuracy and motivates a more systematic re-evaluation and re-parameterization of Pro and Gly residues in the CHARMM force field. We offer rescaled CMAP terms involving Pro, and Gly as an empirical fix for improving modeling involving these residues for use together with CHARMM36m CMAP modifications which we term CHARMM36mGP.

MATERIALS AND METHODS

MD Simulation

PDB:3B0S, a crystal structure of GPO₉ homotrimer at 277 K(32), was used to parameterize a collagen superhelix reproducing the twist and rise of N, Cα, and C backbone atoms to construct collagen trimers of arbitrary length. CHARMM IC tables were used to assign carbonyl oxygen, sidechain, and hydrogen positions and protonation states representative of neutral pH(33). MD simulations were performed using GROMACS 2018.5 using CPU+GPU and CPU-only platforms at mixed precision for conventional MD and REMD respectively(34, 35). Of the CHARMM force fields, CHARMM36 with and without CMAP terms(36) and CHARMM22(37) with CMAP terms(38) were evaluated in combination with their native CHARMM TIP3P water model(37) and the TIP4P/2005 water model(39). To test the efficacy of adjusting the CMAP term strength on correcting the structure and dynamics of POG₁₀ in CHARMM36 simulations, simulations using CHARMM36 tuning the CMAP term down by 0.9 to 0.1 times its strength in intervals of 0.1 were performed. Of the AMBER force fields, ff99sb (indistinguishable from ff99sb* for Pro, Hyp, and Gly)(38, 40), ff99sbws (featuring 1.1x-enhanced protein-water interactions)(41), ff99sb-ILDNP (featuring stiffer Pro and Hyp torsions from those of ff99sb(40))(42), ff14sb(43), and ff19sb(44), were evaluated in combination with the TIP3P, TIP4P/2005, and OPC water models, and with the GBneck2 implicit solvent model(45). The GROMOS force fields GROMOS43A1(46) and GROMOS54A7(47) were evaluated in combination with SPC(48) and SPC/E(49) water models. MD simulations of solvated POG₁₀ and water were performed at 310.15 K in dodecahedral, octahedral, and cubic boxes of dimensions with at least 3.6-nm of additional space along the collagen principal axis and 150 mM NaCl. All systems investigated and their simulation time scale are tabulated in Table S1.

To validate the accuracy of CHARMM36 with rescaled CMAP terms involving Pro and Gly in TIP3P water, we prepared simulations of GPGG peptide previously used to validate the CHARMM36 force field on $J$-couplings(50) and followed the same simulation strategy(36). For comparison, GPGG was also simulated with ff99sb and ff14sb with TIP3P water. These simulations were performed in a dodecahedral periodic box with an extended initial conformation of GPGG with 150 mM NaCl, using 28 exponentially-distributed temperatures from 274 to 400 K and were simulated for 150 ns (Table S2). To test the capacity for persistence length to be reproduced at longer triple helix lengths, we simulated POG₂₀, POG₃₀, and POG₄₀ with AMBER99sb and TIP3P water for 500 ns, which was sufficient to observe decorrelation of pairs of N- and C-terminal tangents along the coordinates used to represent the triple helix as a worm-like chain. The center of masses of Glycines in each triplet were used to represent the triple helix. To validate the capacity for force fields to reasonably reproduce the structure of collagen-like peptides featuring other XYGly-repeats, we selected solved crystal structures with PDB accession codes 1BKV, 6HG7, 8GZO, 8TW0. We constructed triple helices using the idealized POG-repeat superhelix in the same manner, and performed simulations for 400 ns. The last 200 ns of these simulations were analyzed for the capacity for force fields to produce the structure of collagen at non-POG triplets. We performed these simulations with three force fields that reasonably reproduced POG₁₀ structure.

All systems were initially minimized using steepest descent and then equilibrated in the NPT ensemble using weak coupling thermo- and barostats(51) with $\tau =1$ and $\tau =20$ ps at 310.15 K and at 1 bar and 4.5×10⁻⁵ bar⁻¹ compressibility, respectively, for 5 ns with a 1 fs time step. Conventional MD and REMD simulations were performed in the NVT ensemble using the velocity-rescaling thermostat in GROMACS(52) with $\tau =1$ ps or a Langevin thermostat in Amber with a friction coefficient $\gamma =1$ ps⁻¹ and a 2 fs time step. Bonds between hydrogen and heavy atoms in collagen were constrained using LINCS(53) in GROMACS and SHAKE(54) in AMBER, and constraints within water were solved using SETTLE(55).

Appropriate cutoff schemes were employed for computing short-range interactions in all force fields. Simulations with CHARMM force fields were performed using a force-switch function, starting the switch at 10 Å and ending at the 12 Å cutoff. Simulations with AMBER force fields were performed using a cutoff at 10 Å. Simulations with GROMOS force fields were performed with a single-range cutoff scheme rather than the twin-range cutoff scheme used in their parmeterization as GROMACS 2018.5 cannot facilitate twin-range cutoffs with the Verlet nearest neighbor method. We used a 14 Å cutoff for GROMOS force fields, as Diem and Oostenbrink have demonstrated that at single-range 14 Å cutoff results in negligible changes in densities and amino acid solvation free energies of at most 0.4% and 0.5 kJ/mol(56). Particle Mesh Ewald was used for performing long-range electrostatic calculations with the exception of implicit solvent simulations(57).

All conventional MD simulations of POG₁₀ were performed for 1.5 μs, saving all and protein-only coordinates at 1 ns and 10 ps intervals, respectively. Conventional MD simulations of solvent-only systems were performed for 100 ns, saving coordinates every 50 ps, REMD(58) simulations of GPGG were performed for 150-ns, achieved an average exchange likelihoods of approximately 66% in all simulations, and configurations sampled at 310.15 K and 274 K were used for analyses, respectively.

Backbone dihedral angles

Dihedral angles for Pro, Hyp, and Gly were determined from crystal structures of 37 collagen-like peptide structures deposited in the PDB (Figure S1). Dihedral angles of amino acids at the X-positions, Y-positions, and Bly-positions throughout these structures were found to each produce a normal distribution of $\varphi$ and $\psi$ angles which fit to find a mean and standard deviation by which simulated POG dihedral angles could be evaluated (Figure S1). The mean and standard deviation for the $\varphi$ angle in each of these Gaussians are −72.24° ± 6.31, −60.01° ± 4.46, and −69.97° ± 4.51 for Pro, Hyp, and Gly, respectively. The mean and standard deviation for the $\psi$ angle are 161.14° ± 7.04, 150.54° ± 4.40, and 176.79° ± 8.58 for Pro, Hyp, and Gly, respectively. We evaluate how well the non-terminal triplets of POG₁₀ sampled in each protein force field-water model combination fit by calculating the reduced chi-squared statistic $\left({\chi }^2\right)$ in reference to the means and variances of these Gaussians, ${\chi }^2=\frac{1}{N}{\sum }_i^N{\left({\overline{O}}_i^{\text{sim}}-{\overline{O}}_i^{\text{expt}}\right)}^2/{\sigma }^{2,\text{expt}}$, where ${\overline{O}}_i^{\text{sim}}$ is the ensemble-average of observable $i$ from simulation and ${\overline{O}}_i^{\text{expt}}$ the observable $i$ reported from experiment for $N$ observables. ${\sigma }_i^{2,\text{expt}}$ is the variance of the experimental observable $i$, which we calculate as the square of the experimental error.

NMR amide spin relaxation

For each glycine residue, the trajectory of the backbone amide N-H vector $r_i(t)=r_i^{\text{H}}-r_i^{\text{N}}$ was first computed from the all-atom trajectory saved at 10-ps intervals, where $r_i^{\text{H}}$ and $r_i^{\text{N}}$ are the positions of the amide hydrogen and nitrogen atoms respectively. The correlation function(59)

$$C_i(t)=〈P_2({\overrightarrow{\mu }}_i(t)\cdot {\overrightarrow{\mu }}_i(0)〉$$ (1)

was calculated, where $P_2(x)=\frac{1}{2}\left(3x^2-1\right)$ is the second Legendre polynomial and $\overrightarrow{\mu }(t)=\frac{{\overrightarrow{r}}_i(t)}{\left|{\overrightarrow{r}}_i(t)\right|}$. Relaxation rates were obtained from the spectral densities $J_i(\omega )$,

$$J_i(\omega )=2{\int }_0^{\infty }{C}_i(t)\cos \omega tdt.$$ (2)

In practice, the Fourier transform was performed by fitting a triple exponential to $C_i(t)$ and using the analytical transform of the fitted function. Relaxation rates $R_{1,i}$ and $R_{2,i}$ and steady-state NOEs, ${\eta }_i$ for residue $i$ were given by: (59)

$$R_{1,i}=D\left(J\left({\omega }_H-{\omega }_N\right)+3J\left({\omega }_N\right)+6J\left({\omega }_H+{\omega }_N\right)\right)+CJ\left({\omega }_N\right)$$ (3)

$$R_{2,i}=\frac{D}{2}\left(4J(0)+J\left({\omega }_H-{\omega }_N\right)+3J\left({\omega }_N\right)+6J\left({\omega }_H\right)+6J\left({\omega }_H+{\omega }_N\right)\right)+\frac{1}{6}C\left(4J(0)+3J\left({\omega }_N\right)\right)$$ (4)

$${\eta }_i=1+D\frac{{\gamma }_{\text{H}}}{{\gamma }_{\text{N}}}{R}_{1,i}^{-1}\left(6J\left({\omega }_H+{\omega }_N\right)-J\left({\omega }_H-{\omega }_N\right)\right)$$ (5)

where the constants $D$ and $C$ are given respectively by

$$D=\frac{1}{20}\frac{{\left({\mu }_0/4\pi \right)}^2{ħ}^2{\gamma }_{\text{H}}^2{\gamma }_{\text{N}}^2}{r_{\text{NH}}^6}$$ (6)

and

$$C=\frac{1}{15}{\omega }_{\text{N}}^2{\text{Δ}}_{\text{CSA}}^2.$$ (7)

In which, $ħ=\frac{h}{2\pi }$, $h$ is Planck’s constant, ${\mu }_0$ is the vacuum magnetic permeability, ${\gamma }_{\text{H}}$ and ${\gamma }_{\text{N}}$ are the gyromagnetic ratios of ¹H and ¹⁵N, respectively, $r_{\text{NH}}$ is the effective length of the amide N-H bond (0.1041 nm)(60), ${\text{Δ}}_{\text{CSA}}$ is the chemical shift anisotropy (−170 ppm)(61), and ${\omega }_{\text{H}}$ and ${\omega }_{\text{N}}$ are, respectively, the Larmor frequencies of the ¹H and ¹⁵N nuclei at the magnetic field of interest. We fit the spectral densities for the correlation times up to 30-ns. The correlation times were ultimately scaled by the ratio of water viscosity at 310.15 K to 298.15 K to correct for the change in viscosity between the simulated temperature and the experimental temperature of Acevedo-Jake et al.(29). We evaluated the accuracy of dynamics by calculating the RMSE of $R_1$ and $R_2$ for non-terminal glycines in reference to the experimental means and standard deviations.

Scattering profiles

SAXS form factors were calculated using the methodology and accompanying GROMACS implementation of the explicit solvent approach of Hub and coworkers(62, 63), inspired by Park et al.(64). This method requires the use of a solvated solute simulation and a solvent-only simulation to subtract the solvent contribution to scattering intensities. This requires defining an envelope of a particular distance from the surface of the solute at which the scattering intensities of solvent at the envelope surface and bulk solvent become indistinguishable. A 0.7-nm minimum distance solvent envelope was constructed as a triangular mesh to encapsulate the ensemble of rotationally and translationally-fit configurations of POG₁₀ homotrimers sampled at equilibrium to represent the shell of solvent that contributes, along with the protein, to the excess scattering intensity. Solvent-only simulations were used to compute the form factors in absence of the solute and the solute-associated solvent. Cromer-Mann parameters(65, 66) and the corrections of Sorenson et al.(67) were used to compute atomic form factors. To fit simulation intensities to the SAXS data recorded by Iqbal et al.(30), we fit our calculated intensities from $q=0-2.5$ nm⁻¹ by optimizing the scale (a) and shift (b) to fit $I{(q)}_{\text{sim}}=aI{(q)}_{\text{expt}}+b$. This approach, taken by Hub and coworkers, is used to perform the typical scaling necessary to compare scattering intensities between experimental measurements and those computed via simulation, and the constant, $b$, should be small, only to allow for experimental uncertainty in subtraction of the background. We compute the ${\chi }^2$ of the fitted $I{(q)}_{\text{sim}}$ to $I{(q)}_{\text{expt}}$ to validate the accuracy of conformational ensembles produced by various force field and water model combinations.

RESULTS AND DISCUSSION

To evaluate the ability of multiple MD force fields to reproduce the correct backbone structure of collagen triple helices, we use POG₁₀ as a model system due to the availability of several experimental data sets amenable to direct comparison with simulation and the importance of Pro, Hyp, and Gly residues in collagen structure. We evaluate the CHARMM force fields, CHARMM22+CMAP (C22+CMAP: CHARMM 22 force field with additional CMAP terms for backbone $\varphi$, $\psi$ dihedrals, sometimes referred to as CHARMM27), CHARMM36 (C36, which includes CMAP terms as standard, is the same as CHARMM36m for Pro, Hyp, and Gly), CHARMM36 without CMAP terms (C36-CMAP), the AMBER force fields ff99sb (for POG-repeat this is equivalent to ff99sb* and ff99sb-ILDN as these have the same Pro, Hyp, and Gly parameters), ff99sb-ILDNP, ff14sb, and ff19sb, and the GROMOS force fields 43A1 (GRO43A1) and 54A7 (GRO54A7). In combination with the AMBER force fields, we evaluate the TIP3P water model, the TIP4P/2005 water model, and the OPC water model. In combination with the CHARMM force fields we evaluate the CHARMM TIP3P water model and the TIP4P/2005 water model. In combination with the GROMOS force fields we evaluate the SPC and SPC/E force fields. The accuracy of each protein force field-water model combination is evaluated based on its ${\chi }^2$ using experimental uncertainties or otherwise the root mean squared error (RMSE) against experimental measures of structure and dynamics. These data sets are (1) the expected backbone dihedral angles of Pro, Hyp, and Gly determined from crystal structures, (2) the Pro and Hyp ring puckering propensities quantified via NMR, (3) the dynamics of Glycine amides quantified via NMR relaxation data, and (4) the shape of the conformational ensemble of the triple helix quantified via SAXS experiments.

Pro, Hyp, and Gly backbone dihedrals

We evaluated the backbone dihedral angles of residues 4–27 of Prolines, Hydroxyprolines, and Glycines in the POG₁₀ homotrimer with various MD force fields against available crystal structure data. While in general the structural properties of macromolecules in solution will differ from their crystal structures, for relatively rigid molecules such as folded proteins or collagen, one expects the mean structures in solution to be comparable to the mean crystal structures (68). Irrespective of water model used, AMBER ff99sb-based force fields most-accurately reproduce the mean $\varphi$ and $\psi$ angles of the triple helix expected from Gaussian fits to the angle distributions calculated from 37 collagen-like peptide crystal structures (Fig.2, Figure S1, Table S3). AMBER ff14sb and ff19sb force fields achieve the next-most accurate backbone dihedral accuray, including in simulations employing GBNeck2 implicit solvation. For example, ${\chi }^2$ values for Pro, Hyp, and Gly dihedrals in AMBER99sb force field were 0.12, 0.08, and 0.10, and AMBER14sb were 0.37, 1.38, and 0.06, in simulations using TIP3P water.

Figure 2:

Backbone dihedral angles within residues 4–27 of the POG₁₀ homotrimer measured in various protein force fields with water models that best-reproduce water viscosity for CHARMM, GROMOS, and AMBER force fields for the (A) Proline residues, (B) 4(R)-Hydroxyproline residues, and (C) Glycine residues. The grey crosshair and ellipse represent the mean value and standard deviation of the dihedral angles fit from 37 collagen-like peptide crystal structures (Figure S1). The black ellipse represents the mean and standard deviation of the dihedral angle sampled in each force field.

CHARMM force fields tested with (C22+CMAP, C36) and without (C36-CMAP) CMAP parameters did not accurately reproduce the backbone structure, with upshifted $\varphi$ and downshifted $\psi$ angles in Pro and Hyp residues and upshifted $\psi$ angles for Gly residues. Interestingly, turning off the CMAP parameters in C36 resulted in the opposite effect – downshifted $\varphi$ and upshifted $\psi$ angles for Pro and Hyp residues, and downshifted $\psi$ angles in Gly residues – implying that a simple reparameterization of the CMAP parameter strength may be sufficient to correct the backbone structure in simulations with CHARMM force fields. GROMOS force fields are far from accurately reproducing the correct backbone structure at equilibrium. Particularly, GROMOS43A1 does not maintain any semblance of a trimer and collapses to a globular state within the microsecond timescale. While GROMOS54A7 performs better, the backbone $\varphi$, $\psi$ angles are still shifted from their values in crystal structures by tens of degrees.

Pro and Hyp ring puckering

The puckering of the 5-membered ring of Pro and Hyp is directly coupled with the state of the backbone dihedrals(69). In the PPII helix, the switch from exo-pucker (“up”-pucker) to endo-pucker (“down”-pucker) is observed to result in a $\sim -{10}^{\circ }\varphi$ and $\text{a}\sim +5^{\circ }\psi$ change in the backbone dihedral(70). We also observe this in all simulations. Chow et al.(28) determined the endo puckering of Pro and Hyp in POG-repeat triple helices to occur with a 58 and 6% propensity at 310.15 K, respectively. Producing the correct propensity for the ring pucker is not only essential for accurately modeling the backbone, but is also ultimately plays a role in interactions between collagen triple helices, important for understanding collagen dimerization and assembly.

We have characterized the puckering using the ${\chi }_2$ side-chain torsion angle; although in general five membered rings are described by two degrees of freedom (e.g. ring puckering coordinates), a single degree of freedom is sufficient here as the peptide bond results in Cα, N and Cδ being coplanar. We find that, among the AMBER force fields, ff99sb, ff99sb-ILDNP, and ff99sbws all produce qualitatively accurate estimates of the ring puckering propensity, while ff14sb and ff19sb provide even more accurate estimates of these propensities, with Hyp populating the endo-pucker at 3% (Figure 3, Table 1, Table S4). Pro and Hyp ring parameters were included as part of the re-parameterization of side chain torsional angles during the development of ff14sb and ff19sb. Despite impressive accuracy in producing puckering propensity, these new Pro and Hyp parameters do not produce backbone dihedrals as accurately as ff99sb and other ff99sb modifications (Table S3). The ring puckering in standard CHARMM force fields are not consistent with experimental trends in collagen-like peptides. C22+CMAP and C36 both adopt the incorrect pucker in Pro and Hyp. Disabling the CMAP term in CHARMM36 significantly increases the Pro and Hyp endo-puckering propensities. The GROMOS54A7 Pro and Hyp ring pucker propensities are also inaccurate. The CHARMM Pro and Hyp side chains likely require careful attention for correction in the context of updated CMAP terms for all involved dihedrals.

Figure 3:

Pro (A) and Hyp (B) 5-membered ring puckerings measured via ${\chi }_2$ torsion angles, in which positive ${\chi }_2$ are exoand negative ${\chi }_2$ are endo-puckering conformations. The $\varphi$ angle is presented to illustrate the coupling between exo- and endo-puckering and the backbone dihedral angle. Propensities for each conformation are presented in color bars made in hexagonal bins.

Table 1:

Pro and Hyp ring endo-puckering propensities (1-p(Exo)) measured using the ${\chi }_2$ torsion of the side chain. All protein force fields used TIP3P with exception of TIP4P/2005 for ff99sbws, SPC for GRO54A7, and OPC for ff19sb. p(Endo) Pro and p(Endo) Hyp are expected to be 58% and 6% by NMR-determined puckering propensities at 310.15 K by Chow et al.(28).

Force field	C22+CMAP	C36	C36-CMAP	ff99sb	ff99sb-ILDNP	ff99sbws	14sb	19sb	GRO54A7
p(Endo) Pro	28%	29%	81%	55%	54%	54%	50%	47%	29%
p(Endo) Hyp	77%	77%	95%	33%	33%	30%	3%	3%	41%

Triple Helix Shape and Twist via SAXS

The shape of collagen-like peptide triple helix conformational ensembles are essentially rod-like(30). The distribution of intramolecular distances within a triple helix can be captured in the small-angle regime of x-ray scattering, providing a measure of its size and shape. The POG₁₀ homotrimer was previously characterized via SAXS by Iqbal et al. at high precision, capturing the shape of the triple helix in 137 mM PBS buffer at 7.4 pH and at 298.15 K(30). We evaluated the capability of various protein force field and water model combinations to reproduce the conformational ensemble of POG₁₀. To predict the SAXS form factors of our MD simulations including not only the solute but also the solute-solvent interactions around the triple helix, we used GROMACS-SWAXS(62, 63) to compute form factors for the solute and solute-solvent term. To compare these with the experimental data, we shifted and scaled the calculated form factors to obtain the best fit to the experimental ones (Fig.4.A), prior to evaluating the differences between them (Fig.4.B). Generally, we find that all force fields investigated reasonably produce cylindrical shape in their conformational ensembles, as measured by radius of gyration and radii of gyration along the principal and orthogonal axes, $R_g$, $R_{g\Vert }$, and $R_{g\perp }$. Note that the apparent differences from the experimental data in the small-q regime arise from the larger q region being weighted more heavily in the fits (Tables 2, Table S5). AMBER and CHARMM force fields, with the exception of C36-CMAP, were found to have good agreement with experimentally-determined SAXS data. GROMOS54A7 exhibited larger deviations from experimental data, despite maintaining a cylindrical shape and having a similar radius of gyration to AMBER and CHARMM. GROMOS43A1 did not maintain a cylindrical triple helix, reaching $R_{g\Vert }\sim 1.0$ nm and $R_{g\perp }\sim 0.75$ nm at the end of the trajectory, and its SAXS form factor was dramatically different from experiment, having ${\chi }^2=467.08$.

Figure 4:

Comparison of calculated SAXS form factors from simulations with different force fields using 3-point water models with most recent experimental data.(30) (A) Form factors $I(q)$ (as labelled in legend); (B) corresponding residuals (points) and smooth fits (lines). (C) Pair distance distributions of all heavy atoms, demonstrating superhelix structure in oscillations past 1.4 nm.

Table 2:

Comparison of SAXS data for POG₁₀ homotrimer in various force fields with TIP3P water model for CHARMM and AMBER force fields and SPC water model for GROMOS54A7. Simulated SAXS form factors were computed using GROMACS-SWAXS and scaled $\left(aI{(q)}^{\text{sim}}+b=I{(q)}^{\text{expt}}\right)$ to fit form factors reported by Iqbal et al.(30). Guinier fits of $R_g$ performed up to $q=0.5$ nm⁻¹. Radii of gyration $\left(R_g\right)$ along principal and orthogonal axes demonstrate that POG₁₀ maintains a cylindrical shape.

Force field	C22+CMAP	C36	C36-CMAP	ff99sb	ff99sb-ILDNP	ff14sb	GRO54A7
${\chi }^2$	2.38	2.61	8.11	3.95	2.80	3.22	62.22
$R_g$(nm)	2.50 ± 0.02	2.50 ± 0.02	2.57 ± 0.04	2.61 ± 0.02	2.61 ± 0.02	2.60 ± 0.03	2.61 ± 0.07
$R_{g\Vert }$(nm)	2.48 ± 0.02	2.48 ± 0.02	2.56 ± 0.04	2.59 ± 0.02	2.59 ± 0.02	2.58 ± 0.03	2.59 ± 0.07
$R_{g\perp }$(nm)	0.43 ± 0.02	0.43 ± 0.02	0.45 ± 0.03	0.44 ± 0.03	0.44 ± 0.03	0.44 ± 0.03	0.46 ± 0.03

It is curious that $R_g$ produced by GROMOS54A7 is indistinguishable from those produced by AMBER force fields despite having a significantly poorer agreement with the experimentally-determined form factor. Investigating the pair distance distribution for all heavy atoms (Fig. 4.C), we see that, while the shoulder at the largest distances occurs at a similar point, there are significant differences in the oscillatory period of the distribution from 1.4-nm to longer distances. These oscillations correspond to the rise per residue in the triple helix, and are thus expected to be ∼2.9-Å for the POG-repeat superhelix(9). However, this rise is distinctly different depending on the force field. Examining the peak period, we find AMBER force fields to exhibit a rise of 2.84 ± 0.13 Å, CHARMM force fields applying CMAP to exhibit a rise of 2.74 ± 0.16 Å, and GROMOS54A7 to exhibit a rise of 3.00 ± 0.08 Å. As such, CHARMM force fields with CMAP terms produce an overly twisted superhelix and GROMOS54A7 produces an under-twisted superhelix, relative to the AMBER force fields. CHARMM force fields thus produce a shorter radius of gyration due to this over-twisting. However, GROMOS54A7 results in a similar radius of gyration to the AMBER force fields because of some additional fraying at the N- and C-termini. Quantitative evidence for this fraying is seen in the Pro-Gly hydrogen bonding propensities discussed below.

Backbone dynamics via ¹⁵N NMR

The dynamics of the collagen backbone Glycine amides had previously been measured via ¹⁵N NMR to determine the accessibility of water to the triple helix core and as a method to confirm triple helix formation(29, 71). The spin relaxation of the amide nitrogens of the 1st, 2nd, 3rd, 5th, 8th, 9th, and 10th Gly in the leading, middle, and trailing strands of the triple helix were each measured at 298.15 K and pH 3.8 in 10mM PO₄ buffer by Acevedo-Jake, Jalan, and Hartgerink(29). Acevedo-Jake et al. found the non-terminal glycines to exhibit comparable relaxation rates such that their relaxation rates could be averaged together. We used these $R_1$ and $R_2$ relaxation rates to validate the reproduction of the dynamics of POG₁₀ modeled in MD simulations using water models which produce a reasonably accurate solvent viscosity. For AMBER force fields we used the OPC water model, for CHARMM force fields we used the TIP4P/2005 water model, and for GROMOS force fields we used the SPC/E water model. We calculated the $R_1$, and $R_2$ relaxation rates of the Glycines protected from the termini, Gly6-Gly27, and compared them directly with the experimentally-determined relaxation rates (Fig.5). We found that CHARMM36 and AMBER force fields best-reproduce these dynamics. (Tables 3, S6, and S7), in particular the values of $R_1$, suggesting that high frequency motions of the backbone are accurately captured. Larger deviations of $R_2$, which includes a contribution from $J(0)$, suggest that slower motions such as molecular tumbling are less well reproduced.

Figure 5:

Comparison with NMR amide spin relaxation data. (A) ¹⁵ $N{R}_1$ and (B) ¹⁵ $N{R}_2$ relaxation rates of the amide glycines for each triplet in POG₁₀. Terminal triplet glycines $\left(\text{G}{1}_{\text{L}},\dots ,\text{G}{10}_{\text{T}}\right)$, have significantly different experimentally-determined relaxation rates from each other and are thus not represented by one average relaxation like $\text{G}2$, $\text{G}3,\dots \text{G}9$ (black lines)(29). All simulations performed with water models that reasonably reproduce solvent viscosity.

Table 3:

Root mean squared error of non-terminal Glycine NMR spin relaxation rates $R_1$ and $R_2$ in reference to the measurements of Acevedo-Jake et al.(29).

Force field Water model	C22+CMAP TIP4P/2005	C36 TIP4P/2005	C36-CMAP TIP4P/2005	ff99sb OPC	ff99sb-ILDNP OPC	ff99sbws TIP4P/2005	14sb OPC	19sb OPC	GRO54A7 SPC/E
RMSE $\left(R_1\right)$	0.407	0.075	0.032	0.069	0.101	0.086	0.054	0.154	0.583
RMSE $\left(R_2\right)$	0.873	5.897	4.508	2.558	3.460	6.792	1.926	1.616	7.336

Hydrogen bond propensity and persistence length

In addition to comparisons with the experimental data for POG₁₀, an analysis of the stability of the triple helix and its mechanical properties provide additional insight into the relative propensity of these force fields to structure the triple helix. We examined the propensity for the canonical Gly-Pro hydrogen bonds formed via each POG-triplet and the persistence length of the triple helix. Examining the propensities for hydrogen bonding, we found CHARMM force fields to exhibit the highest propensity for the triple helix-stabilizing hydrogen bond (Fig. 6.A). The Gly-Pro hydrogen bonding likelihoods involve the N-terminal triplet are significantly lower than those involving the C-terminal triplet, indicating the slightly higher propensity for N-terminal fraying regardless of force field. This behavior corresponds to the ≥ 5°C lower fraying temperature for the N-terminal residues relative to the C-terminal and non-terminal residues measured by Acevedo-Jake et al.(29). Removing the CMAP term from CHARMM force fields significantly destabilized the triple helix, lower hydrogen bonding likelihoods from 0.7 to 0.2 for hydrogen bonds involving non-terminal glycines. All AMBER force fields established non-terminal Gly-Pro hydrogen bonding propensities of 0.6. GRO54A7, which maintained a trimeric state, established Gly-Pro hydrogen bonding per non-terminal triplet of approximately 0.4. These hydrogen bonding propensities were insensitive to water model employed, including implicit solvation (Table S8).

Figure 6:

Structure formation in POG₁₀. (A) Probability of canonical Gly-Pro hydrogen bonds formed involving each POG-triplet in various force fields with 3-point water models, providing a measure of the relative stability of the triple helix. (B,C) Average dot product separating vectors of two subsequent pairs of Gly triplets by distance $r$, used to determine the persistence length of (B) POG₁₀ in various force fields with 3-point water models and (C) POG_n in AMBER ff99sb with TIP3P for different lengths $n$.

The persistence length, $l_p$, of POG₁₀ was estimated using the worm-like chain model, $<\cos (\theta )>={\text{e}}^{-r/l_p}$, considering the center of mass of the Gly Cα of each POG-triplet as a polymeric unit, and using the vector separating the $i$ and $i+1$ Gly Cα center of mass to define the local tangent vectors used for measuring the angle $\theta$ between triplets in the triple helix separated by average distance $r$ (Figure 6.B, Table S8). CHARMM force fields with the CMAP term produced persistence lengths of approximately 170 nm, where as AMBER force fields and CHARMM36 without the CMAP term produced persistence lengths of approximately 100 nm. GROMOS54A7 produced a persistence length of 10 nm. The persistence length for human and murine wildtype collagen type I has been estimated to be 80–100 nm via analysis of AFM by Forde and coworkers(72–74), or light scattering by Wilcox et al.(75). suggesting AMBER force fields reproduce collagen mechanics slightly better than CHARMM, while GROMOS deviates substantially. However, it must be noted that the wild-type collagen sequence is significantly different from simple POG repeats which limits the quantitative comparison with the experimental persistence length.

We also tested whether the persistence length of POG-repeats was reasonably captured in POG₁₀ by simulating longer POG-repeats, POG₂₀, POG₃₀, and POG₄₀ with AMBER ff99sb with TIP3P water (Figure 6.C). We found the persistence length to be mostly insensitive to POG repeat length (107.1, 106.5, 109.9, 111.1 nm for POG₁₀₋₄₀), noting that changes in persistence length result from a slight deviation from the log-linear relation of $\cos (\theta )$ and $r$ involving the distance between the two terminal triplets that can cause for the computed persistence length to slightly change as a function of length when fit using these end-points. As such, we believe these 10-triplet long constructs may be sufficient for capturing the persistence length of longer POG-repeat triple helices, such as POG_>80 which would exceed the persistence length.

Variationally improving CHARMM36 Pro, Hyp, and Gly via tuning CMAP

Because we had observed the “over”- and “under”-shooting of backbone dihedrals in CHARMM36 when using or removing the CMAP term, we tested scaling the strength of the CMAP term by factors from 0.1 to 0.9 in intervals of 0.1 to test if the agreement with experiment could be improved. This was investigated using both the TIP3P and TIP4P/2005 water models. Scaling the CMAP term by 0.5 achieved the best agreement with backbone dihedrals (Figure 7.A). Scaling CMAP terms to 0.6 achieved optimal agreement with SAXS data (Figure 7.B) while still resulting in accurate backbone dihedrals. Scaling CMAP terms by 0.9 produces an optimal value for the Gly amide relaxation dynamics, though the accuracy of these relaxations are not systematically affected by changing the CMAP scale strength, generally remaining similar to C36 and C36-CMAP (Figure 7.C). Scaling CMAP terms to 0.6 produces the best agreement of Pro puckering with that measured by Duer and coworkers(28), though Hyp puckering maintains an overwhelming propensity for the wrong orientation, suggesting only Hyp torsional parameters may need to be reparameterized following adjustments to the CMAP term strength (Figure 7.D). The overall canonical Pro-Hyp hydrogen bond propensities become similar to those of AMBER force fields when the CMAP term is scaled by 0.5 (Figure 7.E). The persistence length is found to be linearly correlated with the CMAP scale, reaching approximately 127 nm, longer than that observed in ff99sb, at 0.5 (Figure 7.F). Overall, rescaling CMAP parameters involving Pro, Hyp, and Gly by 0.5 results in overall improvement across all of the available data. We have named this adjusted force field CHARMM36mGP, to be used in complement the other widely-used CMAP corrections of CHARMM36m. The Hyp torsional parameters require reparameterization to produce the proper ring puckering, which would also require further adjustments to CMAP or backbone parameters to compensate for resultant changes to backbone dihedrals.

Figure 7:

Simulations of POG₁₀ with CHARMM36 force field with TIP4P/2005 water scaling CMAP terms involving Pro, Hyp, and Gly by a scaling factor of 0.0 to 1.0. Evaluating (A) ${\chi }^2$ of mean backbone dihedrals for Pro, Hyp, and Gly referenced against collagen-like peptide crystal structures (Figure S1). (B) ${\chi }^2$ of SAXS form factors in $q\in (0.12,2.5)$ calculated in simulations using TIP3P referenced against Iqbal et al.(30). (C) RMSE of non-terminal Glycine amide spin relaxation rates $R_1$ (blue) and $R_2$ (red) referenced against Acevedo-Jake et al.(29). (D) Likelihood of endo-puckering state of Pro and Hyp referenced against referenced against those estimated by Duer and coworkers(28). (E) Overall likelihood of canonical Gly-Pro hydrogen bonds. (F) Persistence lengths $\left(l_p\right)$ estimated treating center of mass of glycines in each triplet trimer as a polymeric unit and measuring $<\cos (\theta )>={\text{e}}^{-r/l_p}$.

Validating CHARMM36 with tuned CMAP on GPGG peptide

In the development of CHARMM36(36), Pro and Gly parameters were validated by testing the capacity to reproduce ³J_HH-coupling parameters (Pro₂Hα-Gly₁C, Gly₃Hα-Pro₂C, Gly₄Hα-Gly₃C, Gly₄HN-Gly₄C, Gly₃HN-Gly₃Hα, Gly₄HN-Gly₄Hα) of GPGG measured by Aliev et al.(50). We performed REMD simulations using a similar scheme with ff99sb, ff14sb, and CHARMM36 with various degrees of CMAP scaling factor and compared the differences of these J-couplings against experiment. We found that, though the original CHARMM36 performed significantly better than ff99sb and ff14sb in reproducing these J-couplings, reducing the CMAP term strength to 0.4 maximized agreement (Figure 8). As such, using CHARMM36 with the CMAP terms involving Pro and Gly scaled to 0.5 may serve as a general improvement to CHARMM36.

Figure 8:

RMSE of all ³$J_{HH}$-couplings referenced against Aliev et al.(50) for REMD simulations of GPGG peptide in ff99sb and ff14sb with TIP3P water and CHARMM36 with TIP3P water tuning the CMAP terms involving Pro and Gly by a factor of 0.0 to 1.0.

Reproducing the structure of non-POG repeat triple helices

Having identified force fields that reliably reproduce structure and dynamics of POG-repeats characteristic of collagen, we can begin to explore other triple helical XYGly-repeat motifs. While there is relatively little experimental data reflecting the differences between POG and non-XYGly-repeat sequence collagen-like peptides in solution, differences in collagen triple helix structure have been observed in X-ray crystal structures. We selected two collagen-like peptide triple helices featuring functional domains in collagens and two designed collagen-like peptides.

The T3–785 peptide homotrimer, featuring the fragment ITGARGLAG from the fibrillar Collagen III, includes a metalloprotease cleavage site and is notable for featuring a change from the 7-fold face, 7/2 superhelix, which occurs in the POG-repeats, to a 10-fold face, 10/3 superhelix (PDB:1BKV)(76). Aside from this well-known example of a collagen-like peptide featuring a significant change in structure as a function of sequence, we also selected a collagen-like peptide featuring the fragment LKGHRGFTGLQG from the cartilage oligomeric matrix protein-binding domain of Collagen II (PDB:6HG7)(77). Inter-strand salt bridges and cation-π interactions can be used to design collagen-like triple helices, potentially with thermal stabilities similar to POG-repeats(78, 79). We selected two collagen-like peptide designs featuring over 10 inter-strand salt bridges. We selected one of the salt bridge-rich designs of Huang et al.(80) (PDB:8GZO) featuring competing axial and lateral interactions. We also selected the recent fast-folding design of Cole et al.(81) which also features cation-$\pi$ interactions (PDB:8TW0).

We tested three protein force field and water model combinations: AMBER99sb*-ildn with TIP3P, AMBER19sb with OPC, and our newly modified CHARMM36mGP with TIP3P, featuring the adjusted CMAP terms involving Pro, Hyp, and Gly. Initiating all simulations from the same POG-repeat-like backbone and superhelix structure, we found the triple helix structure to adjust to closely match the crystal backbone structure, producing RMSEs of backbone dihedrals comparable to that observed in force fields which most-accurately reproduce the structure of POG₁₀ (Table 4). As such, we believe any of these force fields that best-reproduce POG₁₀ structure will reasonable produce structures of other XYGly-repeat triple helices, pending further investigation that may be made possible with more detailed solution-phase data.

Table 4:

Root mean squared error of all $\varphi$ and $\psi$ angles sampled in simulations past 200-ns not including N- and C-terminal triplets of collagen-like peptides. Simulations employed AMBER99sb*-ILDN, AMBER19sb, and CHARMM36mGP in combination with TIP3P, OPC, and TIP3P (CHARMM) water models respectively. RMSEs are taken with respect to the crystal structure with exception of POG₁₀ which is taken with respect to the optimized values in Fig. S1.

Reference structure	AMBER99sb*-ILDN	AMBER19sb	CHARMM36mGP
POG10	5.90°	8.43°	5.60°
PDB:1BKV	5.86°	7.63°	6.12°
PDB:6HG7	5.43°	4.72°	4.73°
PDB:8GZO	5.96°	7.28°	5.29°
PDB:8TW0	7.27°	7.34°	10.44°

CONCLUSIONS

In this study we employed experimentally-determined crystal structure data, NMR data, and SAXS data to evaluate the capacity for AMBER, CHARMM, and GROMOS force fields to reproduce the structure and dynamics of the collagen triple helix in combination with a variety of water models. We evaluated these for the POG₁₀ homotrimer, the most well-characterized collagen-like peptide, as the POG-repeat is among the most frequent motifs in the collagen XYGly-repeat. The capacity for force fields to reproduce the structure of Proline, Hydroxyproline, and Glycine residues in the context of the collagen triple helix has not been carefully evaluated, as most force fields are validated using single-domain protein folds, where these residues typically serve as structure-breaking residues in secondary structures. We found that AMBER force fields based on ff99sb were largely able to achieve a high accuracy in reproducing the expected structure of POG₁₀ regardless of water model, and were able to capture dynamics using the TIP4P/2005 and OPC water models. We found that, while CHARMM force fields were slightly overstructured, this overstructuring can be corrected by reducing the strength of CMAP terms involving Pro, Hyp, and Gly by a factor of 1/2 in the CHARMM36 force field, a correction which we have dubbed CHARMM36mGP. However, the CHARMM36 Hyp residue torsional angles were also found to require further reparameterization to correct the puckering of the 5-member ring. This CMAP rescaling correction was also demonstrated to improve agreement of CHARMM36 with the set of J-coupling parameters originally used to validate the CHARMM36 force field. GROMOS force fields were found to significantly deviate from the expected POG₁₀ structure on the microsecond time scale, suggesting a more in-depth reparameterization of GROMOS is necessary to correct this behavior.

ff99sb, ff9sbws, ff99sb*, ff99sb-ILDNP, and ff99sb*-ILDNP were shown to be reasonable force fields for modeling collagen, among which further discrimination would require evaluation of sequences deviating from the POG-repeat, for which there is significantly less experimental data available. We also demonstrated the capacity for force fields that reasonably reproduce the structure of POG₁₀ to adopt triple helix structures that reproduce crystal structure of more complex sequences of collagen-like peptides with similar accuracy to POG₁₀. We believe that the corrections for Pro and Gly in CHARMM36 (or similar corrections based on refitting to quantum chemistry data) may provide a more general correction for Pro and Gly in CHARMM36, but testing this may require further investigation of folded and intrinsically disordered proteins in which Pro and Gly play a critical role in determining structure and function.

This investigation will enable future investigations of collagen structure, dynamics, and mechanics with greater confidence in their quantitative accuracy. Fine details of past simulations employing force fields that exhibited substantial deviations from the expected structure and dynamics of POG₁₀ may require careful reconsideration, as the triple helix structure may substantially distort from expected structure on the hundreds of nanosecond timescales which are now routine for MD simulation. Accurate all-atom force fields for collagen are expected to help directly in studies of collagen folding, misfolding and assembly in all-atom simulations that are increasingly capable of treating large systems. In addition, good all-atom force fields will be a valuable tool for “bottom-up” parameterization of coarse-grained force fields for collageneous domains – especially useful as there is not sufficient data for a “top-down” parameterization against experiment. Such coarse-grained models would allow the accurate treatment of assembly processes occurring on time- and length-scales that are currently inaccessible to all-atom simulation.

Supplementary Material

Supporting Information is complementing the manuscript is included. The CHARMM36mGP force field, simulation trajectories, input data, analysis data, analysis and plotting scripts, and scripts for preparing initial conditions are archived and available at doi:10.5281/zenodo.15354101.

An online supplement to this article can be found by visiting BJ Online at http://www.biophysj.org.

SIGNIFICANCE

Molecular Dynamics simulations have frequently been used to study the role of sequence on collagen structure and inter-protein interactions on an atomistic level, on the assumption that force fields produce reasonably accurate conformations of collagen at equilibrium. Here, we have validated equilibrium structural ensembles of the well-characterized (Proline-4(R)-Hydroxyproline-Glycine)₁₀ homotrimer produced by force fields from the AMBER, CHARMM, and GROMOS families with crystal structures, NMR data, and SAXS form factors. We suggest the use of the AMBER99sb-based force fields for current molecular dynamics simulations of collagen and propose a simple correction for CHARMM36 CMAP terms involving proline and glycine which may be generally applicable to prolines and glycines in the force field.