A systematic methodology for defining coarse-grained sites in large biomolecules

Coarse-graining provides insights on the essential nature of heterogeneity in actin filaments

Experiments have shown that actin is structurally polymorphic, but knowledge of the details of molecular level heterogeneity in both the dynamics of a single subunit and the interactions between subunits is still lacking. Here, using atomistic molecular dynamics simulations of the actin filament, we identify domains of atoms that move in a correlated fashion, quantify interactions between these domains using coarse-grained (CG) analysis methods, and perform CG simulations to explore the importance of filament heterogeneity. The persistence length and torsional stiffness calculated from molecular dynamics simulation data agree with experimental values. We additionally observe that distinct actin conformations coexist in actin filaments. The filaments also exhibit random twist angles that are broadly distributed. CG analysis reveals that interactions between equivalent CG pairs vary from one subunit to another. To explore the importance of heterogeneity on filament dynamics, we perform CG simulations using different methods of parameterization to show that only by including heterogeneous interactions can we reproduce the twist angles and related properties. Free energy calculations further suggest that in general the actin filament is best represented as a set of subunits with differing CG sites and interactions, and the incorporating heterogeneity into the CG interactions is more important than including that in the CG sites. Our work therefore presents a systematic method to explore molecular level detail in this large and complex biopolymer.

Systematic methods for structurally consistent coarse-grained models

This chapter provides a primer on theories for coarse-grained (CG) modeling and, in particular, reviews several systematic methods for determining effective potentials for CG models. The chapter first reviews a statistical mechanics framework for relating atomistic and CG models. This framework naturally leads to a quantitative criterion for CG models that are "consistent" with a particular atomistic model for the same system. This consistency criterion is equivalent to minimizing the relative entropy between the two models. This criterion implies that a many-body PMF is the appropriate potential for a CG model that is consistent with a particular atomistic model. This chapter then presents a unified exposition of the theory and numerical methods for several approaches for approximating this many-body PMF. Finally, this chapter closes with a brief discussion of a few of the outstanding challenges facing the field of systematic coarse-graining.

Membrane binding and self-association of the epsin N-terminal homology domain

Epsin possesses a conserved epsin N-terminal homology (ENTH) domain that acts as a phosphatidylinositol 4,5-bisphosphate‐lipid‐targeting and membrane‐curvature‐generating element. Upon binding phosphatidylinositol 4,5‐bisphosphate, the N-terminal helix (H₀) of the ENTH domain becomes structured and aids in the aggregation of ENTH domains, which results in extensive membrane remodeling. In this article, atomistic and coarse-grained (CG) molecular dynamics (MD) simulations are used to investigate the structure and the stability of ENTH domain aggregates on lipid bilayers. EPR experiments are also reported for systems composed of different ENTH-bound membrane morphologies, including membrane vesicles as well as preformed membrane tubules. The EPR data are used to help develop a molecular model of ENTH domain aggregates on preformed lipid tubules that are then studied by CG MD simulation. The combined computational and experimental approach suggests that ENTH domains exist predominantly as monomers on vesiculated structures, while ENTH domains self-associate into dimeric structures and even higher‐order oligomers on the membrane tubes. The results emphasize that the arrangement of ENTH domain aggregates depends strongly on whether the local membrane curvature is isotropic or anisotropic. The molecular mechanism of ENTH‐domain-induced membrane vesiculation and tubulation and the implications of the epsin's role in clathrin-mediated endocytosis resulting from the interplay between ENTH domain membrane binding and ENTH domain self-association are also discussed.

A Local Rigid Body Framework for Global Optimization of Biomolecules

We present a local rigid body framework for simulations of biomolecules. In this framework, arbritrary sets of atoms may be treated as rigid bodies. Such groupings reduce the number of degrees of freedom, which can result in a significant reduction of computational time. As benchmarks, we consider global optimization for the tryptophan zipper (trpzip 1, 1LE0; using the CHARMM force field) and chignolin (1UAO; using the AMBER force field). We use a basin-hopping algorithm to find the global minima and compute the mean first encounter time from random starting configurations with and without the local rigid body framework. Minimal groupings are used, where only peptide bonds, termini, and side chain rings are considered rigid. Finding the global minimum is 4.2 and 2.5 times faster, respectively, for trpzip 1 and chignolin, within the local rigid body framework. We further compare O(10(5)) low-lying local minima to the fully relaxed unconstrained representation for trpzip 1 at different levels of rigidification. The resulting Pearson correlation coefficients, and thus the apparent intrinsic rigidity of the various groups, appear in the following order: side chain rings > termini > trigonal planar centers ≥ peptide bonds ≫ side chains. This approach is likely to be even more beneficial for structure prediction in larger biomolecules.

Structural basis of membrane bending by the N-BAR protein endophilin

Functioning as key players in cellular regulation of membrane curvature, BAR domain proteins bend bilayers and recruit interaction partners through poorly understood mechanisms. Using electron cryomicroscopy, we present reconstructions of full-length endophilin and its N-terminal N-BAR domain in their membrane-bound state. Endophilin lattices expose large areas of membrane surface and are held together by promiscuous interactions between endophilin's amphipathic N-terminal helices. Coarse-grained molecular dynamics simulations reveal that endophilin lattices are highly dynamic and that the N-terminal helices are required for formation of a stable and regular scaffold. Furthermore, endophilin accommodates different curvatures through a quantized addition or removal of endophilin dimers, which in some cases causes dimerization of endophilin's SH3 domains, suggesting that the spatial presentation of SH3 domains, rather than affinity, governs the recruitment of downstream interaction partners.

Coarse-grain Protein Models

Coarse-graining is a powerful approach for modeling biomolecules that, over the last few decades, has been extensively applied to proteins. Coarse-grain models offer access to large systems and to slow processes without becoming computationally unmanageable. In addition, they are very versatile, enabling both the protein representation and the energy function to be adapted to the biological problem in hand. This review concentrates on modeling soluble proteins and their assemblies. It presents an overview of the coarse-grain representations, of the associated interaction potentials, and of the optimization procedures used to define them. It then shows how coarse-grain models have been used to understand processes involving proteins, from their initial folding to their functional properties, their binary interactions, and the assembly of large complexes.

Optimal number of coarse-grained sites in different components of large biomolecular complexes

The computational study of large biomolecular complexes (molecular machines, cytoskeletal filaments, etc.) is a formidable challenge facing computational biophysics and biology. To achieve biologically relevant length and time scales, coarse-grained (CG) models of such complexes usually must be built and employed. One of the important early stages in this approach is to determine an optimal number of CG sites in different constituents of a complex. This work presents a systematic approach to this problem. First, a universal scaling law is derived and numerically corroborated for the intensity of the intrasite (intradomain) thermal fluctuations as a function of the number of CG sites. Second, this result is used for derivation of the criterion for the optimal number of CG sites in different parts of a large multibiomolecule complex. In the zeroth-order approximation, this approach validates the empirical rule of taking one CG site per fixed number of atoms or residues in each biomolecule, previously widely used for smaller systems (e.g., individual biomolecules). The first-order corrections to this rule are derived and numerically checked by the case studies of the Escherichia coli ribosome and Arp2/3 actin filament junction. In different ribosomal proteins, the optimal number of amino acids per CG site is shown to differ by a factor of 3.5, and an even wider spread may exist in other large biomolecular complexes. Therefore, the method proposed in this paper is valuable for the optimal construction of CG models of such complexes.

Coarse-graining of multiprotein assemblies

Multiscale models are important tools to elucidate how small changes in local subunit conformations may propagate to affect the properties of macromolecular complexes. We review recent advances in coarse-graining methods for poly-protein assemblies, systems that are composed of many copies of relatively few components, with a particular focus on viral capsids and cytoskeletal filaments. These methods are grouped into two broad categories-mapping methods, which use information from one scale of representation to parameterize a lower resolution model, and bridging methods, which repeatedly connect different scales during simulation-and we provide examples of both classes at different levels of complexity. Collectively, these models illustrate the numerous approaches to information transfer between scales and demonstrate that the complexity required of the model depends in general on the nature of the information sought.

Key intermolecular interactions in the E. coli 70S ribosome revealed by coarse-grained analysis

The ribosome is a very large complex that consists of many RNA and protein molecules and plays a central role in protein biosynthesis in all organisms. Extensive interactions between different molecules are critical to ribosomal functional dynamics. In this work, intermolecular interactions in the Escherichia coli 70S ribosome are investigated by coarse-grained (CG) analysis. CG models are defined to preserve dynamic domains in RNAs and proteins and to capture functional motions in the ribosome, and then the CG sites are connected by harmonic springs, and spring constants are obtained by matching the computed fluctuations to those of an all-atom molecular dynamics (MD) simulation. Those spring constants indicate how strong the interactions are between the ribosomal components, and they are in good agreement with various experimental data. Nearly all the bridges between the small and large ribosomal subunits are indicated by CG interactions with large spring constants. The head of the small subunit is very mobile because it has minimal CG interactions with the rest of the subunit; however, a large number of small subunit proteins bind to maintain the internal structure of the head. The results show a clear connection between the intermolecular interactions and the structural and functional properties of the ribosome because of the reduced complexity in domain-based CG models. The present approach also provides a useful strategy to map interactions between molecules within large biomolecular complexes since it is not straightforward to investigate these by either atomistic MD simulations or residue-based elastic network models.

Order parameters for macromolecules: application to multiscale simulation

Order parameters (OPs) characterizing the nanoscale features of macromolecules are presented. They are generated in a general fashion so that they do not need to be redesigned with each new application. They evolve on time scales much longer than 10(-14) s typical for individual atomic collisions/vibrations. The list of OPs can be automatically increased, and completeness can be determined via a correlation analysis. They serve as the basis of a multiscale analysis that starts with the N-atom Liouville equation and yields rigorous Smoluchowski/Langevin equations of stochastic OP dynamics. Such OPs and the multiscale analysis imply computational algorithms that we demonstrate in an application to ribonucleic acid structural dynamics for 50 ns.

Reconstructing protein remodeled membranes in molecular detail from mesoscopic models

We present a method for "inverse coarse graining," rebuilding a higher resolution model from a lower resolution one, in order to rebuild protein coats for remodeled membranes of complex topology. The specific case of membrane remodeling by N-BAR domain containing proteins is considered here, although the overall method is general and thus applicable to other membrane remodeling phenomena. Our approach begins with a previously developed, discretized mesoscopic continuum membrane model (EM2) which has been shown to capture the reticulated membrane topologies often observed for N-BAR/liposome systems by electron microscopy (EM). The information in the EM2 model-directions of the local curvatures and a low resolution sample of the membrane surface-is then used to construct a coarse-grained (CG) system with one site per lipid and 26 sites per protein. We demonstrate the approach on pieces of EM2 structures with three different topologies that have been observed by EM: A tubule, a "Y" junction, and a torus. We show that the approach leads to structures that are stable under subsequent constant temperature CG simulation, and end by considering the future application of the methodology as a hybrid approach that combines experimental information with computer modeling.

Multiscale computer simulation of the immature HIV-1 virion

Multiscale computer simulations, employing a combination of experimental data and coarse-graining methods, are used to explore the structure of the immature HIV-1 virion. A coarse-grained (CG) representation is developed for the virion membrane shell and Gag polypeptides using molecular level information. Building on the results from electron cryotomography experiments, the simulations under certain conditions reveal the existence of an incomplete p6 hexameric lattice formed from hexameric bundles of the Gag CA domains. In particular, the formation and stability of the immature Gag lattice at the CG level requires enhanced interfacial interactions of the CA protein C-terminal domains (CTDs). An exact mapping of the CG representation back to the molecular level then allows for detailed atomistic molecular dynamics studies to confirm the existence of these enhanced CA(CTD) interactions and to probe their possible origin. The multiscale simulations further provide insight into potential CA(CTD) mutations that may disrupt or modify the Gag immature lattice assembly process in the immature HIV-1 virion.

Internal Dynamics of a Coarse-Grained Protein Using Analytical Harmonic Representation

An analytical coarse-grained model (ACG) is introduced to represent individual macromolecules for simulation of dynamic processes in cells. In the ACG model, a macromolecular structure is treated as a fully coarse-grained entity with a uniform mass density without the explicit atomic details. The excluded volume and surface of the ACG macromolecular species are explicitly treated by a spherical harmonic representation in the present study (although ellipsoidal, solid, and radial augmented functions can be used), which can provide any desired accuracy and detail depending on the problem of interest. The present paper focuses on the description of the internal fluctuations of a single ACG macromolecule, modeled by the superposition of low frequency quasiharmonic modes from explicit molecular dynamics simulation. A procedure for estimating the amplitudes, time scales of the quasiharmonic motions and the corresponding phases is presented and used to synthesize the complex motion. The analytical description and numerical algorithm can provide an adequate representation of the internal protein fluctuations revealed from the corresponding atomistic simulations, although the internal motions of ACG macromolecules do not explore motions not exhibited in the dynamic simulations.

Coarse-Grained Representations of Large Biomolecular Complexes from Low-Resolution Structural Data

High-resolution atomistic structures of many large biomolecular complexes have not yet been solved by experiments, such as X-ray crystallography or NMR. Often however low-resolution information is obtained by alternative techniques, such as cryo-electron microscopy or small-angle X-ray scattering. Coarse-grained (CG) models are an appropriate choice to computationally study these complexes given the limited resolution experimental data. One of the important questions therefore is how to define CG representations from these low-resolution density maps. This work provides a space-based essential dynamics coarse-graining (ED-CG) method to define a CG representation from a density map without detailed knowledge of its underlying atomistic structure and primary sequence information. This method is demonstrated on G-actin (both the atomic structure and its density map). It is then applied to the density maps of the Escherichia coli 70S ribosome and the microtubule. The results indicate that the method can define highly CG models that still preserve functionally important dynamics of large biomolecular complexes.

Optimal identification of semi-rigid domains in macromolecules from molecular dynamics simulation

Biological function relies on the fact that biomolecules can switch between different conformations and aggregation states. Such transitions involve a rearrangement of parts of the biomolecules involved that act as dynamic domains. The reliable identification of such domains is thus a key problem in biophysics. In this work we present a method to identify semi-rigid domains based on dynamical data that can be obtained from molecular dynamics simulations or experiments. To this end the average inter-atomic distance-deviations are computed. The resulting matrix is then clustered by a constrained quadratic optimization problem. The reliability and performance of the method are demonstrated for two artificial peptides. Furthermore we correlate the mechanical properties with biological malfunction in three variants of amyloidogenic transthyretin protein, where the method reveals that a pathological mutation destabilizes the natural dimer structure of the protein. Finally the method is used to identify functional domains of the GroEL-GroES chaperone, thus illustrating the efficiency of the method for large biomolecular machines.

Multiscale network model for large protein dynamics

Protein dynamics is essential for gaining insight into biological functions of proteins. Although protein dynamics is well delineated by molecular model, the molecular model is computationally prohibited for simulating large protein structures. In this work, we provide a multiscale network model (MNM) that allows the efficient computation on low-frequency normal modes related to structural deformation of proteins as well as dynamic behavior of functional sites. Specifically, MNM consists of two regions, one of which is described as a low-resolution structure, while the other is dictated by a high-resolution structure. The high-resolution regions using all alpha carbons of the protein are mainly binding site parts, which play a critical function in molecules, while the low-resolution parts are constructed from a further coarse-grained model (not using all alpha carbons). The feasibility of MNM to observe the cooperative motion of a protein structure was validated. It was shown that the MNM enables us to understand functional motion of proteins with computational efficiency.

Role of protein interactions in defining HIV-1 viral capsid shape and stability: a coarse-grained analysis

Coarse-grained models of the HIV-1 CA dimer are constructed based on all-atom molecular dynamics simulations. Coarse-grained representations of the capsid shell, which is composed of approximately 1500 copies of CA proteins, are constructed and their stability is examined. A key interaction between carboxyl and hexameric amino terminal domains is shown to generate the curvature of the capsid shell. It is demonstrated that variation of the strength of this interaction for different subunits in the lattice can cause formation of asymmetric, conical-shaped closed capsid shells, and it is proposed that variations, in the structure of the additional carboxyl-amino terminal binding interface during self-assembly, are important aspects of capsid cone formation. These results are in agreement with recent structural studies of the capsid hexamer subunit, which suggest that variability in the binding interface is a cause of the differences in subunit environments that exist in a conical structure.

Hierarchical coarse-graining strategy for protein-membrane systems to access mesoscopic scales

An overall multiscale simulation strategy for large scale coarse-grain simulations of membrane protein systems is presented. The protein is modeled as a heterogeneous elastic network, while the lipids are modeled using the hybrid analytic-systematic (HAS) methodology, where in both cases atomistic level information obtained from molecular dynamics simulation is used to parameterize the model. A feature of this approach is that from the outset liposome length scales are employed in the simulation (i.e., on the order of 1/2 a million lipids plus protein). A route to develop highly coarse-grained models from molecular-scale information is proposed and results for N-BAR domain protein remodeling of a liposome are presented.

Defining coarse-grained representations of large biomolecules and biomolecular complexes from elastic network models

Coarse-grained (CG) models of large biomolecular complexes enable simulations of these systems over long timescales that are not accessible for atomistic molecular dynamics (MD) simulations. A systematic methodology, called essential dynamics coarse-graining (ED-CG), has been developed for defining coarse-grained sites in a large biomolecule. The method variationally determines the CG sites so that key dynamic domains in the protein are preserved in the CG representation. The original ED-CG method relies on a principal component analysis (PCA) of a MD trajectory. However, for many large proteins and multi-protein complexes such an analysis may not converge or even be possible. This work develops a new ED-CG scheme using an elastic network model (ENM) of the protein structure. In this procedure, the low-frequency normal modes obtained by ENM are used to define dynamic domains and to define the CG representation accordingly. The method is then applied to several proteins, such as the HIV-1 CA protein dimer, ATP-bound G-actin, and the Arp2/3 complex. Numerical results show that ED-CG with ENM (ENM-ED-CG) is much faster than ED-CG with PCA because no MD is necessary. The ENM-ED-CG models also capture functional essential dynamics of the proteins almost as well as those using full MD with PCA. Therefore, the ENM-ED-CG method may be better suited to coarse-grain a very large biomolecule or biomolecular complex that is too computationally expensive to be simulated by conventional MD, or when a high resolution atomic structure is not even available.

Multiscale simulation of protein mediated membrane remodeling

Proteins interacting with membranes can result in substantial membrane deformations and curvatures. This effect is known in its broadest terms as membrane remodeling. This review article will survey current multiscale simulation methodologies that have been employed to examine protein mediated membrane remodeling.

Nucleotide-dependent conformational states of actin

The influence of the state of the bound nucleotide (ATP, ADP-Pi, or ADP) on the conformational free-energy landscape of actin is investigated. Nucleotide-dependent folding of the DNase-I binding (DB) loop in monomeric actin and the actin trimer is carried out using all-atom molecular dynamics (MD) calculations accelerated with a multiscale implementation of the metadynamics algorithm. Additionally, an investigation of the opening and closing of the actin nucleotide binding cleft is performed. Nucleotide-dependent free-energy profiles for all of these conformational changes are calculated within the framework of metadynamics. We find that in ADP-bound monomer, the folded and unfolded states of the DB loop have similar relative free-energy. This result helps explain the experimental difficulty in obtaining an ordered crystal structure for this region of monomeric actin. However, we find that in the ADP-bound actin trimer, the folded DB loop is stable and in a free-energy minimum. It is also demonstrated that the nucleotide binding cleft favors a closed conformation for the bound nucleotide in the ATP and ADP-Pi states, whereas the ADP state favors an open confirmation, both in the monomer and trimer. These results suggest a mechanism of allosteric interactions between the nucleotide binding cleft and the DB loop. This behavior is confirmed by an additional simulation that shows the folding free-energy as a function of the nucleotide cleft width, which demonstrates that the barrier for folding changes significantly depending on the value of the cleft width.

Multiscale modeling of emergent materials: biological and soft matter

In this review, we focus on four current related issues in multiscale modeling of soft and biological matter. First, we discuss how to use structural information from detailed models (or experiments) to construct coarse-grained ones in a hierarchical and systematic way. This is discussed in the context of the so-called Henderson theorem and the inverse Monte Carlo method of Lyubartsev and Laaksonen. In the second part, we take a different look at coarse graining by analyzing conformations of molecules. This is done by the application of self-organizing maps, i.e., a neural network type approach. Such an approach can be used to guide the selection of the relevant degrees of freedom. Then, we discuss technical issues related to the popular dissipative particle dynamics (DPD) method. Importantly, the potentials derived using the inverse Monte Carlo method can be used together with the DPD thermostat. In the final part we focus on solvent-free modeling which offers a different route to coarse graining by integrating out the degrees of freedom associated with solvent.

Systematic multiscale parameterization of heterogeneous elastic network models of proteins

We present a method to parameterize heterogeneous elastic network models (heteroENMs) of proteins to reproduce the fluctuations observed in atomistic simulations. Because it is based on atomistic simulation, our method allows the development of elastic coarse-grained models of proteins under different conditions or in different environments. The method is simple and applicable to models at any level of coarse-graining. We validated the method in three systems. First, we computed the persistence length of ADP-bound F-actin, using a heteroENM model. The value of 6.1 +/- 1.6 microm is consistent with the experimentally measured value of 9.0 +/- 0.5 microm. We then compared our method to a uniform elastic network model and a realistic extension algorithm via covariance Hessian (REACH) model of carboxy myoglobin, and found that the heteroENM method more accurately predicted mean-square fluctuations of alpha-carbon atoms. Finally, we showed that the method captures critical differences in effective harmonic interactions for coarse-grained models of the N-terminal Bin/amphiphysin/Rvs (N-BAR) domain of amphiphysin, by building models of N-BAR both bound to a membrane and free in solution.