ORIGINAL RESEARCH article
Sec. Biological Modeling and Simulation
Coarse-Grained Modeling and Molecular Dynamics Simulations of Ca2+-Calmodulin
- 1Department of Physics, University of Houston, Houston, TX, United States
- 2Center for Theoretical Biological Physics, Rice University, Houston, TX, United States
Calmodulin (CaM) is a calcium-binding protein that transduces signals to downstream proteins through target binding upon calcium binding in a time-dependent manner. Understanding the target binding process that tunes CaM’s affinity for the calcium ions (Ca2+), or vice versa, may provide insight into how Ca2+-CaM selects its target binding proteins. However, modeling of Ca2+-CaM in molecular simulations is challenging because of the gross structural changes in its central linker regions while the two lobes are relatively rigid due to tight binding of the Ca2+ to the calcium-binding loops where the loop forms a pentagonal bipyramidal coordination geometry with Ca2+. This feature that underlies the reciprocal relation between Ca2+ binding and target binding of CaM, however, has yet to be considered in the structural modeling. Here, we presented a coarse-grained model based on the Associative memory, Water mediated, Structure, and Energy Model (AWSEM) protein force field, to investigate the salient features of CaM. Particularly, we optimized the force field of CaM and that of Ca2+ ions by using its coordination chemistry in the calcium-binding loops to match with experimental observations. We presented a “community model” of CaM that is capable of sampling various conformations of CaM, incorporating various calcium-binding states, and carrying the memory of binding with various targets, which sets the foundation of the reciprocal relation of target binding and Ca2+ binding in future studies.
Calmodulin (CaM) is a calcium-binding protein that is present in all eukaryotic cells (Berchtold and Villalobo, 2014; Villalobo et al., 2018; Chin and Means, 2000). CaM is composed of two globular domains separated by a central linker. The two domains (N- and C-domains) are constituted of two calcium-binding helix-loop-helix motifs each, namely, EF-hand motifs (Chattopadhyaya et al., 1992; Fernandes and Oliveira-Brett, 2017). Upon sufficient increase in Ca2+ concentration, Ca2+-free CaM transitions to the Ca2+-loaded CaM (Figure 1), exposing the hydrophobic target-binding surfaces of CaM to the solvent (Figure 2) (Barton et al., 2002; Vetter and Leclerc, 2003; Park et al., 2008; Gromiha and Gromiha, 2010; Wu et al., 2012; Fernandes and Oliveira-Brett, 2017). This transition is accompanied by large conformational changes mutually induced by the conformational changes in the CaM-binding target (CaMBT) peptides (Wang et al., 2013; Liu et al., 2017a; Archer et al., 2019; Bekker et al., 2020). The most unique feature of CaM is its reciprocal relation between Ca2+ binding and target binding (Meador et al., 1993; Weinstein and Mehler, 1994; Wall et al., 1997; Wriggers et al., 1998; Chin and Means, 2000; Hoeflich and Ikura, 2002; Westerlund and Delemotte, 2018), where the conformational changes in the CaM/CaMBT compound further tune CaM’s affinity for the Ca2+ ions (Hoffman et al., 2014; Zhang et al., 2017). The important feature that the net charges of Ca2+ ions vary with the conformations of a calcium-binding loop (Zhang et al., 2021), however, has not been accurately captured in molecular dynamics simulations on calcium-binding proteins.
FIGURE 1. Representative conformations of calmodulin (CaM). (A) Ca2+-free CaM, or apoCaM (PDB ID: 1CFD); (B) Ca2+-bound CaM, or holoCaM, in the extended conformation (PDB ID: 1CLL); (C) holoCaM in the collapsed conformation without a target peptide (PDB ID: 1PRW); (D) holoCaM with a target peptide (PDB ID 1CDM). We visualized the structures using the Visual Molecular Dynamics (VMD) program (Humphrey et al., 1996). Ca2+ ions are shown in yellow spheres, the N-terminal and C-terminal domains of CaM are shown in red and blue, respectively, the central linker is shown in grey, and the target peptide is in green.
FIGURE 2. Ca2+ induced conformational change. (A) apoCaM, (B) holoCaM. Ca2+ ions are shown in yellow spheres, the N-terminal and C-terminal domains of CaM are shown in red and blue, respectively, and the central linker is shown grey. Upon conformational change, the four methionine residues (shown as beads in purple), initially buried inside the EF-hands, are exposed to the solvent.
The 148-amino acid CaM is an evolutionarily conserved protein across all vertebrates (Davis and Thorner, 1989; Tripathi et al., 2015a), while it is capable of binding more than 300 variations of CaMBTs (Yamniuk and Vogel, 2004). Such structural variability permits its regulation upon the stimulation of calcium ions processes (Clapham, 2007; Carafoli, 2002; Bootman, 2012) in a wide range of biological activities (Chin and Means, 2000; Hoeflich and Ikura, 2002) including cellular motility, neurogenesis, memory formation, muscle contraction, and neuronal transmission (Bootman, 2012; Marambaud et al., 2009; Berridge, 2006). A large and growing body of literature has investigated the structures and dynamics of CaM upon calcium binding (Wriggers et al., 1998; Mehler et al., 1991; Her et al., 2018; Anthis et al., 2011). The crystal structure of the Ca2+-CaM shows a dumbbell-like structure with a central α-helical linker (Figure 1B). However, in solution, the central linker demonstrates higher flexibility (Wriggers et al., 1998; Her et al., 2018; Anthis et al., 2011; Ikura et al., 1992; Chou et al., 2001), which enables the two globular domains of CaM to orient independently from each other (Wriggers et al., 1998; Shepherd and Vogel, 2004; Qin and Squier, 2001). Moreover, this flexibility of the central linker could justify the compact structure of the Ca2+-CaM (Figure 1D) upon target binding (Barton et al., 2002; Shepherd and Vogel, 2004). Additionally, Ca2+-CaM has been shown to crystallize in the collapsed conformation in the absence of the target (Figure 1C), indeed providing more evidence of the backbone plasticity of the Ca2+-CaM (Fallon and Quiocho, 2003) and domain-domain interactions. The structural distribution between the collapsed and extended conformations is roughly 1:9 (Anthis et al., 2011).
A myriad of computational approaches, ranging from all-atom to coarse-grained (Weinstein and Mehler, 1994; Spoel et al., 1996; Wriggers et al., 1998; Vigil et al., 2001; Yang et al., 2001; Barton et al., 2002; Komeiji et al., 2002; Yang et al., 2004; Zuckerman, 2004; Monticelli et al., 2008; Nandigrami and Portman, 2016; Liu et al., 2017b; Gong and Sun, 2017; Robustelli et al., 2018; Delfino et al., 2019; Sun and Kekenes-Huskey, 2021), have been employed to model the structural dynamics of CaM. However, these models have yet to capture the reciprocal relation between Ca2+ binding and target binding. The modeling of CaM is often limited for a specific purpose to either bind the target or the calcium ions. As such, CaM is treated as a folded protein (Shepherd and Vogel, 2004; Yang et al., 2004; Zuckerman, 2004) or a folded protein with intrinsically disordered regions (Robustelli et al., 2018), where, in most cases, Ca2+ effects are ignored for simplicity (Spoel et al., 1996; Yang et al., 2001; Shepherd and Vogel, 2004; Robustelli et al., 2018). When Ca2+ is considered, it is treated as a particle with fixed charges as in an aqueous solution (Monticelli et al., 2008; Gong and Sun, 2017). When Ca2+ ions are implicitly included, their charges are often distributed to all the negatively charged residues present in the EF-hand motifs (Nandigrami and Portman, 2016) without any consideration of the coordination geometry of the Ca2+ ion, which is influenced by the conformation of a calcium-binding loop (Zhang et al., 2021). Our group has recently proposed a coarse-grained model to study the dynamics of CaM that accounts for both considerations (Wang et al., 2013; Zhang et al., 2017), but it is yet to reproduce the reciprocal relationship between calcium binding and target binding as both require intensive data-driven efforts.
One of the main challenges for developing an appropriate force field involving Ca2+ is that CaM is a structurally flexible protein about its central linker while the binding of Ca2+ to the two domains of CaM increases the rigidity of the local domains. A compromise between rigidity and softness has to be considered in order for CaM to accurately select, bind, and activate its binding targets. We, therefore, turned to the coarse-grained approach that adopts the Associative memory, Water mediated, Structure, and Energy Model (AWSEM) force field (Wang et al., 2011; Zhang et al., 2017) to fulfill these requirements. The next challenge is to properly include the Ca2+ ions in the force field of a coarse-grained model since this would allow us to understand the reciprocal relationship between calcium binding to CaM and binding of a target (Wang et al., 2013; Tripathi et al., 2015b). Although in separate studies, there have been development in AWSEM force fields on structurally flexible proteins (Wu et al., 2018) or on di-valent ions (Tsai et al., 2016), both features, however, have yet to be combined for modeling CaM. Particularly, the coordination chemistry of Ca2+ ions and the structural flexibility allowing CaM to flex according to its binding targets and surrounding environment is important in modeling the adaptive behavior of CaM (Wang et al., 2013; Liu et al., 2017a; Archer et al., 2019; Bekker et al., 2020). By taking into account the coordination chemistry of the Ca2+ ions as well as the flexible nature of the central linker of CaM, our proposed model for Ca2+-CaM elucidates the many-body effects of calcium binding on the geometrical shape of the calcium-binding loop and allows large conformational changes for binding various targets.
Materials and Methods
Coarse-Grained Modeling Using the AWSEM Force Field
We used the AWSEM force field (Davtyan et al., 2012; Tsai et al., 2016) to build the model of Ca2+-CaM. AWSEM is a transferable coarse-grained protein model, which uses three beads (
which is composed of two main terms: the physics-based terms,
The contact term
where the outer sum is over the aligned memory (from
TABLE 1. The PDB IDs of the 60 non-redundant CaM memory structures for the AWSEM model and the Rg of the CaM. In the case of CaM complexes, only the coordinates of CaM were used for memory. m is the index for the memories.
We used 60 non-redundant structures of CaM taken from our prior study (Tripathi et al., 2015c) (Table 1), either free or in complex with the target peptides, to build the memory fragments for the coarse-grained model of CaM. We used the 60 sequence homologs of Ca2+-CaM since we are interested in studying the dynamics and the folding properties of CaM. We divided each memory into three segments: N-domain of CaM, from residue 5 to residue 76; the flexible central linker, from residue 77 through residue 81; and C-domain of CaM, from residue 82 to residue 147 (as illustrated in Figure 1). The weight of each segment is controlled by a memory weight parameter
We summarized CaM models using various values of
TABLE 2. Summary of Ca2+-CaM models with different values of the global and local memory weight and the average Rg (
Modeling Ca2+ Ions in ASWEM Force Field
Calcium-binding proteins in most cases contain the EF-hand calcium-binding motif which is formed by the pentagonal bipyramidal geometry (Figure 3; Supplementary Figure S1 in the SI) (Drake et al., 1997; Yang et al., 2002). The literature on modeling those proteins, in general, does not clearly explain how Ca2+-binding effects are considered during the simulations. We developed an implicit Ca2+ model that evenly splits the Ca2+ charges to a selection of residues. Partial charges on the sidechain beads of the negatively charged residues that coordinate Ca2+ collectively in the Ca2+ binding loops (Figure 3) were adjusted to reflect the Ca2+- binding effect (Table 3). To note, charges on those acidic residues which do not coordinate (Ca2+) remain intact (−1 e). This simple approach incorporates the coordination geometry of the Ca2+ and allows us to improve the modeling of many-body effects in the local Ca2+ binding loops which furthermore controls the open/close state of the helix-loop-helix EF-hand and the global conformation of calmodulin.
FIGURE 3. Illustration of a Ca2+ binding loop at the fourth EF-hand of CaM (PDB ID: 1CLL). The pentagonal bipyramidal geometry of the Ca2+ coordination is represented with the dotted lines in the top view (A) and side view (B). The red sticks linked with the dotted lines represent oxygen atoms that participate in coordination. The water molecule, shown in pink, completes the spherical coordination through hydrogen bonding.
TABLE 3. The adjusted partial charges of the negatively charged residues participated in calcium coordination in the four calcium-binding loops of CaM. The amino acid sequences of the calcium-binding loops are provided as a reference. The subscript indices stand for the positions of the starting/ending residues in the CaM sequence. Underscored residues are the selected amino acids with negative charges as shown in the third column. We adjusted the partial charges on the sidechain beads of those residues based on the bipyramidal pentagonal coordination geometry of the calcium ion.
In this study, we compared the abovementioned approach (approach III) with two other calcium models:
I. Splitting the Ca2+ charges evenly to the neighboring negatively charged residues (Tsai et al., 2016).
II. Splitting the Ca2+ charges evenly to the residues that participate with the calcium coordination and the radius of gyration of the sidechain beads are constrained by a stiff harmonic potential with a force constant of 30 kcal/mol/Å2.
III. The same with approach II except that the harmonic constraint is removed.
Comparing to approach I of Ca2+ in AWSEM (Tsai et al., 2016), in approach III calcium charges were split according to the coordination chemistry of calcium; comparing to approach II, in approach III more degrees of freedom to the Ca2+ coordination residues allow sampling of more different conformations of CaM.
We performed the coarse-grained simulations with the open-source MD package LAMMPS, in which AWSEM code was implemented (Davtyan et al., 2012). We used the periodic boundary conditions on the cubic box of 400 Å on each side so that even unfolded CaM can fit in the box. Initial velocities were chosen randomly from a Boltzmann distribution with the average squared velocity equal to 3
Simulated annealing: firstly, we denatured the protein at 450 K using the initial structure built from the crystal structure (PDB ID: 1CLL) (Chattopadhyaya et al., 1992); then, we performed simulated annealing on Ca2+-CaM by cooling down the system to a low temperature (280 K) for 2,000,000 time steps for each value of
Production simulation: we employed the umbrella sampling (US) method (Roux, 1995) to evaluate the thermodynamic properties of Ca2+-CaM using different memory parameters. We conducted the production simulations in canonical ensemble (NVT) at the constant temperature of 300 K. Radius of gyration (Rg) of Ca2+-CaM was used as the reaction coordinate, which was restrained by a harmonic potential
We described the conformational changes of the Ca2+-CaM during the simulations by calculating the radius of gyration (
Radius of Gyration (
Rg describes the compactness of the protein, and its definition is given in Eq. 7:
In the case of PDB structures,
Definition of Collapsed and Extended Conformations of CaM
In our analyses, we used the parameter Rg to define a collapsed or extended conformation. The Rg cutoff was set according to the potential of mean force (PMF) and distribution of Rg in our simulations (Figures 4–8). A collapsed conformation is defined if Rg < 18.5Å; otherwise, an extended conformation is defined.
FIGURE 4. PMF and Rg distribution of the Ca2+-CaM models using the global memory weight of different order of magnitudes. The memory weight parameters of the Ca2+-CaM models are listed in Table 2 (model I;
FIGURE 5. PMF and Rg distribution of the Ca2+-CaM models for different values of the local memory weight
FIGURE 6. PMF and Rg distribution of the Ca2+-CaM models for different values of the local memory weight
FIGURE 7. Representative snapshots of the Ca2+-CaM model obtained from our simulations. The model that best reproduces experimental measurements was used (
FIGURE 8. PMF and Rg distribution of the Ca2+-CaM for different Ca2+ models. The optimized memory parameters for the Ca2+-CaM model were used (
Results and Discussion
The goal is to create a computational model for CaM accommodating its several key functions including divalent ion binding, conformational dynamics, and target recognition. In order to achieve this, we adopted a pool of 60 CaM or CaM complex structures from our previous study (Tripathi et al., 2015c) representing full-length CaM without mutations and its complex with 24 unique target proteins/peptides. As stated in the Materials and Methods Simulation Details, our approach is to tune the two scaling parameters
Each of the 60 memories has a specific conformation of calmodulin which could be helpful in target recognition and target selection; therefore, clustering the 60 memories may leave out important conformations that accommodate recognition of a specific target protein. Potentially, there could be as many as 181 fragment memory parameters to be determined in the most complicated scenario. However, in the general practice of AWSEM modeling, a search in the available determined structures in the database according to the match in the desired amino acid sequence is conducted to generate a library of memory structures. Therefore, to avoid excessive tuning of the parameters, the individual memory weight Wnm is kept as a constant default value. Because the unbound extended form of the Ca2+/CaM (PDB code: 1CLL) was found to be most dominant experimentally, we adjusted its local memory weight parameter correspondingly, while keeping others the default
Parameterization of our CG model was guided by the existing following experimental measures:
The Global Parameter Weight Controls the Energy Barrier Between Extended and the Collapsed States of Ca2+-CaM
Firstly, we determined the magnitude of the fragment memory interaction by investigating its effect on the folding properties of Ca2+-CaM. We carried out simulated annealing using the unfolded structure of the Ca2+-CaM (
In addition, we carried out US simulations to evaluate thermodynamic properties of Ca2+-CaM with the global scaling parameter in three orders of magnitudes
In summary, the global memory parameter
Single Memory Optimization Captures the Dynamics of Ca2+-CaM
Although the global fragment memory weight of
Since the crystal structure of Ca2+-CaM (PDB ID: 1CLL) demonstrates a value of Rg that is closest to the experimentally measured values and does not bind a target, we first examined whether variation in single memory weight of this structure (
Central Linker of the Ca2+-CaM Determines the Conformational Change of Ca2+-CaM
Although the X-ray crystallography experiment shows that the central linker that connects the two domains of Ca2+-CaM has a helical structure, numerous studies including NMR have shown its high flexibility in solution. To explore the relationship between the flexible linker and the dynamics of Ca2+-CaM in more detail, we carried out a series of US molecular simulations with the memory weight of the central linker of the Ca2+-CaM,
In order to illustrate the conformational changes of Ca2+-CaM in solution, we selected representative snapshots from the simulations using the Ca2+-CaM model with
Coordination Geometry Is Necessary for Representing Divalent Ions in Coarse-Grained Models
Although it can be tempting to use the available intrinsically disordered protein (IDP) force fields such as AWSEM-IDP (Wu et al., 2018) (due to the disordered nature of the central linker) to study the dynamics of Ca2+-CaM, the heterogeneity of CaM needs to be considered. The high rigidity of the two domains upon calcium-binding limits the use of IDP force fields, thus making the computational investigation of CaM even more complex.
We further manifest the importance of coordination chemistry by comparing the three approaches to modeling Ca2+ as described in Method Modeling Ca2+Ions in ASWEM Force Field in Figure 8. With approach I, the Ca2+ charges were evenly distributed to all the negatively charged residues (Tsai et al., 2016) and Ca2+-CaM presents an equal probability of sampling the completely collapsed conformation and the extended conformation (γc:e = 1.01).
Force field development for Ca2+ ion is mostly limited to the aqueous solution rather than in protein-bound environments (Probst et al., 1985). One of the main challenges in computer simulations of macromolecules remains the development of force fields with the appropriate implementation of the metal ion (Gifford et al., 2007; Duarte et al., 2014; Li and Merz, 2017; Liao et al., 2017; Fracchia et al., 2018; Huang and MacKerell, 2018). Due to the high sensibility of the molecules upon bivalent metal ion binding, taking the Ca2+-induced conformational changes in CaM as an example, a lack of appropriate approach to model its effects on the molecules could impede the capability of the target molecule to transduce its signals, thus, leading to the inactivation and/or malfunction of the signaling pathways (Gaertner et al., 2004; Wang et al., 2011).
Most calcium-binding proteins such as CaM contain the EF-hand (helix-loop-helix) structural domain as the calcium-binding motif (Lepšík and Field, 2007; Capozzi et al., 2006). In this motif, the calcium ion is coordinated in a pentagonal bipyramidal configuration (Figure 3). The canonical positions 1, 3, 5, 7, 9, and 12 represent the positions of the residues involved in calcium coordination (Clapham, 2007; Gifford et al., 2007). Table 3 shows simple and efficient ways to consider the effect of the Ca2+ ions in the force field, where we distributed its charges to the negatively charged residues present in the pentagonal bipyramidal configuration. In contrast to other approaches where the harmonic constraint is applied to the calcium coordinated residues in the loop, or the charges are distributed to all the negatively charged residues in the system, our approach (III) not only considers the heterogeneity of CaM but also takes into account the coordination chemistry of calcium by giving the coordinated residues the freedom to participate to the different conformations of the system, which are relevant to the target selectivity of Ca2+-CaM.
The Distribution of Ca2+-CaM Conformations Is Beyond the Extended and the Collapsed Structures
Ca2+-CaM undergoes substantial conformational changes upon binding to a target, in most cases, the Ca2+-CaM develops a collapsed form that wraps around the target peptide with the two domains coming in proximity (Meador et al., 1993; Westerlund and Delemotte, 2018; Tidow and Nissen, 2013). For various CaMBT molecules, CaM undergoes structural rearrangement to different degrees during the complex formation. Thus, the collapsed conformation of the intact Ca2+-CaM (e.g., Figure 7) assembles a vast variety of structures including a structure that resembles the compact conformation of a specific Ca2+-CaM/target complex (Figure 1D). This was also observed by X-ray crystallography (Fallon and Quiocho, 2003) and NMR studies (Anthis et al., 2011). This collapsed structure of the Ca2+-CaM (Figure 7A) confirms the earlier experiments that show multiple conformations of the Ca2+-CaM in solution, as well as the interaction between opposing domains of CaM (Johnson, 2006; Anthis et al., 2011; Her et al., 2018).
Previous studies have shown that the high flexibility of the linker in solution allows the two domains to independently undergo multiple conformations (Malmendal et al., 1999; Chou et al., 2001; Barton et al., 2002; Hoeflich and Ikura, 2002; Komeiji et al., 2002; Park et al., 2008; Wu et al., 2012). Structural differences can be inferred from crystallography, but the dynamical insights are pivotal to understand Ca2+-CaM interactions with the targets. Experimental and computational studies including NMR spectroscopy, X-ray crystallography, small-angle X-ray scattering, and molecular dynamics simulations unveil important details of the dynamics of Ca2+-CaM and paint a clear portrait of its conformational motions at the origin of the binding selectivity. The available structures of Ca2+-CaM show that it crystallizes into two major conformations: extended (Chattopadhyaya et al., 1992) and collapsed (Fallon and Quiocho, 2003), while in solution, Ca2+-CaM adopts multiple conformations (Project et al., 2006; Park et al., 2008; Wu et al., 2012; McCarthy et al., 2015; Fernandes and Oliveira-Brett, 2017; Jing et al., 2017; Her et al., 2018; Villalobo et al., 2018; Shimoyama, 2019). The conformational changes of CaM upon Ca2+ binding have been under intensive investigation (Weinstein and Mehler, 1994; Gilli et al., 1998; Project et al., 2006; Park et al., 2008; Wu et al., 2012). The goal of such studies is to understand the molecular mechanism that leads to the Ca2+-CaM target binding selectivity. How Ca2+-CaM interacts with its CaMBTs is of major interest. This presented community model of CaM allows transitions between a rich set of states beyond the two major extended or the collapsed conformations and are applicable for various Ca2+ bound conditions; this further could improve the interpretation of how target binding may tune CaM’s affinity for Ca2+ ions (Gaertner et al., 2004; Zhang et al., 2017).
Here, we developed a “community model” of CaM that samples various conformations of CaM, incorporates various calcium-binding states, and carries the memory of binding with various targets. The model would be useful for studying the reciprocal relationship interplay between target binding and calcium binding through CaM’s conformational changes as the next step. We demonstrated a workflow of the development of the AWSEM model for CaM guided by physical knowledge and experimental data. Should new structures of CaM (or CaM/CaMBT complex) structures become available, the model can be easily expanded by including these structures in the memory library.
Data Availability Statement
The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding author.
MC conceived and designed the research. JN performed the simulations and prepared the figures. MC, JN, PZ, JE, WL, and KK performed data analysis and wrote the article. PW provided critical advice. All authors contributed to the manuscript, read, and approve the submitted version.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
We thank Drs. Neal M. Waxham, Piotr Cieplak, and Qian Wang for stimulating discussions. The work was supported by a grant from the National Institutes of Health (2R01GM097553). MSC and PGW are grateful for the funding support from the National Science Foundation (PHY2019745). PGW is grateful for the support from the D. R. Bullard-Welch Chair at Rice University, Grant C-0016. The authors acknowledge the computing resources from the computing clusters uHPC and Sabine at the University of Houston.
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmolb.2021.661322/full#supplementary-material
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Keywords: calmodulin dynamics, calcium-binding protein, conformational changes, intrinsic disorder, AWSEM, community model
Citation: Nde J, Zhang P, Ezerski JC, Lu W, Knapp K, Wolynes PG and Cheung MS (2021) Coarse-Grained Modeling and Molecular Dynamics Simulations of Ca2+-Calmodulin. Front. Mol. Biosci. 8:661322. doi: 10.3389/fmolb.2021.661322
Received: 30 January 2021; Accepted: 21 July 2021;
Published: 24 August 2021.
Edited by:Vojtech Spiwok, University of Chemistry and Technology in Prague, Czechia
Reviewed by:Jianhan Chen, University of Massachusetts Amherst, United States
Manuel N. Melo,Universidade Nova de Lisboa, Portugal
Sunita Negi, GD Goenka University, India
Copyright © 2021 Nde, Zhang, Ezerski, Lu, Knapp, Wolynes and Cheung. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Margaret S. Cheung, firstname.lastname@example.org