Quantifying RNA structures and interactions with a unified reduced chain representation model

RNA is a pivotal molecule that plays critical roles in various cellular processes. Quantifying RNA structures and interactions is essential to understanding RNA function and developing RNA-based therapeutics. Using a unified five-bead model and a non-redundant database, this paper investigates the structural features and interactions of five commonly occurring RNA motifs, i.e., double-stranded helices, hairpin loops, internal/bulge loops, multi-branched junctions, and single-stranded terminal tails. Analyzing detailed distributions of RNA local structural features and base-base interactions reveals a preference for helical structures in both local backbone structures and base orientations. The interactions between adjacent bases exhibit motif-specific and sequence-dependent characteristics, reflecting the distinct topological constraints imposed by different loop-helix connection modes and the varying pairing and stacking interactions among different sequences. These findings shed light on the stability of RNA helices, emphasizing their significance in providing dominant base pairing and stacking interactions for RNA structures and stability. The four non-helix motifs encompass unpaired nucleotide loops and exhibit diverse base-base interactions, contributing to the structural diversity observed in RNA. Overall, the complexity of RNA structure arises from the intricate interplay of base-base interactions.

Exploring the binding kinetics and behaviors of self-aggregated beta-amyloid oligomers to phase-separated lipid rafts with or without ganglioside-clusters

Lipid binding kinetics and energetics of self-aggregated and disordered beta-amyloid oligomers of various sizes, from solution to lipid raft surfaces, were investigated using MD simulations. Our systems include small (monomers to tetramers) and larger (octamers and dodecamers) oligomers. Our lipid rafts contain saturated and unsaturated phosphatidylcholine (PC), cholesterol, and with or without asymmetrically distributed monosialotetrahexosylganglioside (GM1). All rafts exhibited dynamic and structurally diversified domains including liquid-ordered (Lo), liquid-disordered (Ld), and interfacial Lod domains. For rafts without GM1, all oligomers bound to the Lod domain. For GM1-containing rafts, all small oligomers and most larger oligomers bound specifically to the GM1-clusters embedded in the Lo domain. Lipid-protein binding energies followed an order of GM1 >> unsaturated PC > saturated PC > cholesterol for all rafts. In addition, protein-induced membrane structural disruption increased progressively with the size of the oligomer for the annular lipids surrounding the membrane-bound protein in non-GM1-containing rafts. We propose that the tight binding of beta-amyloid oligomers to the GM1-clusters and the structural perturbation of lipids surrounding the membrane-bound proteins at the Lod domain are early molecular events of the beta-amyloid aggregation process on neuronal membrane surfaces that trigger the onset of Alzheimer's.

Cooperative antimicrobial action of melittin on lipid membranes: A coarse-grained molecular dynamics study

We conducted a series of coarse-grained molecular dynamics (CG-MD) simulations to investigate the complicated actions of melittin, which is an antimicrobial peptide (AMP) derived from honey bee venom, on a lipid membrane. To accurately simulate the AMP action, we developed and used a protein CG model as an extension of the pSPICA force field (FF), which was designed to reproduce several thermodynamic quantities and structural properties. At a low peptide-to-lipid (P/L) ratio (1/102), no defect was detected. At P/L = 1/51, toroidal pore formation was observed due to collective insertion of multiple melittin peptides from the N-termini. The pore formation was initiated by a local increase in membrane curvature in the vicinity of the peptide aggregate. At a higher P/L ratio (1/26), two more modes were detected, seemingly not controlled by the P/L ratio but by a local arrangement of melittin peptides: 1. Pore formation accompanied by lipid extraction by melittin peptides:a detergent-like mechanism. 2. A rapidly formed large pore in a significantly curved membrane: bursting. Thus, we observed three pore formation modes (toroidal pore formation, lipid extraction, and bursting) depending on the peptide concentration and local arrangement. These observations were consistent with experimental observations and hypothesized melittin modes. Through this study, we found that the local arrangements and population of melittin peptides and the area expansion rate by membrane deformation were key to the initiation of and competition among the multiple pore formation mechanisms.

Computational Models for the Study of Protein Aggregation

Protein aggregation has been studied by many groups around the world for many years because it can be the cause of a number of neurodegenerative diseases that have no effective treatment. Obtaining the structure of related fibrils and toxic oligomers, as well as describing the pathways and main factors that govern the self-organization process, is of paramount importance, but it is also very difficult. To solve this problem, experimental and computational methods are often combined to get the most out of each method. The effectiveness of the computational approach largely depends on the construction of a reasonable molecular model. Here we discussed different versions of the four most popular all-atom force fields AMBER, CHARMM, GROMOS, and OPLS, which have been developed for folded and intrinsically disordered proteins, or both. Continuous and discrete coarse-grained models, which were mainly used to study the kinetics of aggregation, are also summarized.

Coarse-grained MD simulations reveal beta-amyloid fibrils of various sizes bind to interfacial liquid-ordered and liquid-disordered regions in phase separated lipid rafts with diverse membrane-bound conformational states

The membrane binding behaviors of beta-amyloid fibrils, dimers to pentamers, from solution to lipid raft surfaces, were investigated using coarse-grained (CG) MD simulations. Our CG rafts contain phospholipid, cholesterol (with or without tail- or headgroup modifications), and with or without asymmetrically distributed monosialotetrahexosylganglioside (GM1). All rafts exhibited liquid-ordered (Lo), liquid-disordered (Ld), and interfacial Lo/Ld (Lod) domains, with domain sizes depending on cholesterol structure. For rafts without GM1, all fibrils bound to the Lod domains. Specifically, dimer fibrils bound exclusively via the C-terminal, while larger fibrils could bind via other protein regions. Interestingly, a membrane-inserted state was detected for a trimer fibril in a raft with tail-group modified cholesterol. For rafts containing GM1, fibrils bound either to the GM1-clusters, with numerous membrane-bound conformations, or to the non-GM1-containing-Lod domains via the C-terminal. Our results indicate beta-amyloid fibrils bind to Lod domains or GM1, with diversified membrane-bound conformations, in structurally heterogeneous lipid membranes.

Atomic-level reconstruction of biomolecules by a rigid-fragment- and local-frame-based (RF-LF) strategy

Coarse-grained (CG) model has been a powerful tool in bridging the gap between theoretical studies and experimental phenomena in biological computing field. The reconstruction from a CG model to an atomic-detail structure is especially important in CG studies of biological systems. In this work, a rigid-fragment- and local-frame-based (RF-LF) backmapping method was proposed to achieve reverse mapping from CG models to atomic-level structures. The initial atomic-level structures were further refined to yield the final backmapping ones. With the popular Martini force field, the performance of the RF-LF method was extensively examined in the CG → AA (CG to AA) backmapping of protein/DNA/RNA systems. Besides, the RF-LF method was also extended to the backmapping of the TMFF model. Numerical results illustrate that the RF-LF backmapping method is generic and parameter-free and can provide a promising way to tackle atomic-level studies in CG models.

Protocols for All-Atom Reconstruction and High-Resolution Refinement of Protein-Peptide Complex Structures

Structural characterizations of protein-peptide complexes may require further improvements. These may include reconstruction of missing atoms and/or structure optimization leading to higher accuracy models. In this work, we describe a workflow that generates accurate structural models of peptide-protein complexes starting from protein-peptide models in C-alpha representation generated using CABS-dock molecular docking. First, protein-peptide models are reconstructed from their C-alpha traces to all-atom representation using MODELLER. Next, they are refined using Rosetta FlexPepDock. The described workflow allows for reliable all-atom reconstruction of CABS-dock models and their further improvement to high-resolution models.

Electrodiffusion models of synaptic potentials in dendritic spines

The biophysical properties of dendritic spines play a critical role in neuronal integration but are still poorly understood, due to experimental difficulties in accessing them. Spine biophysics has been traditionally explored using theoretical models based on cable theory. However, cable theory generally assumes that concentration changes associated with ionic currents are negligible and, therefore, ignores electrodiffusion, i.e. the interaction between electric fields and ionic diffusion. This assumption, while true for large neuronal compartments, could be incorrect when applied to femto-liter size structures such as dendritic spines. To extend cable theory and explore electrodiffusion effects, we use here the Poisson (P) and Nernst-Planck (NP) equations, which relate electric field to charge and Fick's law of diffusion, to model ion concentration dynamics in spines receiving excitatory synaptic potentials (EPSPs). We use experimentally measured voltage transients from spines with nanoelectrodes to explore these dynamics with realistic parameters. We find that (i) passive diffusion and electrodiffusion jointly affect the dynamics of spine EPSPs; (ii) spine geometry plays a key role in shaping EPSPs; and, (iii) the spine-neck resistance dynamically decreases during EPSPs, leading to short-term synaptic facilitation. Our formulation, which complements and extends cable theory, can be easily adapted to model ionic biophysics in other nanoscale bio-compartments.

Hybrid Methods for Modeling Protein Structures Using Molecular Dynamics Simulations and Small-Angle X-Ray Scattering Data

Small-angle X-ray scattering (SAXS) is an efficient experimental tool to measure the overall shape of macromolecular structures in solution. However, due to the low resolution of SAXS data, high-resolution data obtained from X-ray crystallography or NMR and computational methods such as molecular dynamics (MD) simulations are complementary to SAXS data for understanding protein functions based on their structures at atomic resolution. Because MD simulations provide a physicochemically proper structural ensemble for flexible proteins in solution and a precise description of solvent effects, the hybrid analysis of SAXS and MD simulations is a promising method to estimate reasonable solution structures and structural ensembles in solution. Here, we review typical and useful in silico methods for modeling three dimensional protein structures, calculating theoretical SAXS profiles, and analyzing ensemble structures consistent with experimental SAXS profiles. We also review two examples of the hybrid analysis, termed MD-SAXS method in which MD simulations are carried out without any knowledge of experimental SAXS data, and the experimental SAXS data are used only to assess the consistency of the solution model from MD simulations with those observed in experiments. One example is an investigation of the intrinsic dynamics of EcoO109I using the computational method to obtain a theoretical profile from the trajectory of an MD simulation. The other example is a structural investigation of the vitamin D receptor ligand-binding domain using snapshots generated by MD simulations and assessment of the snapshots by experimental SAXS data.

Theoretical approaches for dynamical ordering of biomolecular systems

BACKGROUND

Living systems are characterized by the dynamic assembly and disassembly of biomolecules. The dynamical ordering mechanism of these biomolecules has been investigated both experimentally and theoretically. The main theoretical approaches include quantum mechanical (QM) calculation, all-atom (AA) modeling, and coarse-grained (CG) modeling. The selected approach depends on the size of the target system (which differs among electrons, atoms, molecules, and molecular assemblies). These hierarchal approaches can be combined with molecular dynamics (MD) simulation and/or integral equation theories for liquids, which cover all size hierarchies.

SCOPE OF REVIEW

We review the framework of quantum mechanical/molecular mechanical (QM/MM) calculations, AA MD simulations, CG modeling, and integral equation theories. Applications of these methods to the dynamical ordering of biomolecular systems are also exemplified.

MAJOR CONCLUSIONS

The QM/MM calculation enables the study of chemical reactions. The AA MD simulation, which omits the QM calculation, can follow longer time-scale phenomena. By reducing the number of degrees of freedom and the computational cost, CG modeling can follow much longer time-scale phenomena than AA modeling. Integral equation theories for liquids elucidate the liquid structure, for example, whether the liquid follows a radial distribution function.

GENERAL SIGNIFICANCE

These theoretical approaches can analyze the dynamic behaviors of biomolecular systems. They also provide useful tools for exploring the dynamic ordering systems of biomolecules, such as self-assembly. This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato.

Multi-scale simulations of biological systems using the OPEP coarse-grained model

Biomolecules are complex machines that are optimized by evolution to properly fulfill or contribute to a variety of biochemical tasks in the cellular environment. Computer simulations based on quantum mechanics and atomistic force fields have been proven to be a powerful microscope for obtaining valuable insights into many biological, physical, and chemical processes. Many interesting phenomena involve, however, a time scale and a number of degrees of freedom, notably if crowding is considered, that cannot be explored at an atomistic resolution. To bridge the gap between reality and simulation, many different advanced computational techniques and coarse-grained (CG) models have been developed. Here, we report some applications of the CG OPEP protein model to amyloid fibril formation, the response of catch-bond proteins to two types of fluid flow, and interactive simulations to fold peptides with well-defined 3D structures or with intrinsic disorder.

A critical assessment of finite element modeling approach for protein dynamics

Finite element (FE) modeling approach has emerged as an efficient way of calculating the dynamic properties of supramolecular protein structures and their complexes. Its efficiency mainly stems from the fact that the complexity of three-dimensional shape of a molecular surface dominates the computational cost rather than the molecular size or the number of atoms. However, no critical evaluation of the method has been made yet particularly for its sensitivity to the parameters used in model construction. Here, we make a close investigation on the effect of FE model parameters by analyzing 135 representative protein structures whose normal modes calculated using all-atom normal mode analysis are publicly accessible online. Results demonstrate that it is more beneficial to use a contour surface of electron densities as the molecular surface, in general, rather than to employ a solvent excluded surface, and that the solution accuracy is almost insensitive to the model parameters unless we avoid extreme values leading to an inaccurate depiction of the characteristic shapes.

Mechanical response and deformation mechanics of Type IV pili investigated using steered coarse-grained molecular dynamics simulation

Type IV pili are long filamentous structures on the surface of bacteria, which can be rapidly assembled or disassembled with pilin subunits by molecular motors. They can generate force during retraction and are involved in many bacterial functions. Steered molecular dynamics simulations with coarse-grained MARTINI models are carried out to investigate the mechanical behaviors of pili under tension. Our study is the first to report a Young's modulus of 0.80±0.07GPa and a spring constant of 1294.6±116.5kJmol^-1nm^-2 for pilus. Our results show the mechanical responses of pili are different from those described by the worm-like chain model and the van der Waal's interactions play a critical role in the mechanical responses. Moreover, the effects of pulling rates and virtual spring constants of pilus on Young's modulus are studied and two distinct morphological stages with the conformational changes appear during the extension of pilus are observed. This work provide insight into the mechanics and the deformation mechanism of pilus assembly.

A Discontinuous Potential Model for Protein-Protein Interactions

Protein-protein interactions play an important role in many biologic and industrial processes. In this work, we develop a two-bead-per-residue model that enables us to account for protein-protein interactions in a multi-protein system using discontinuous molecular dynamics simulations. This model deploys discontinuous potentials to describe the non-bonded interactions and virtual bonds to keep proteins in their native state. The geometric and energetic parameters are derived from the potentials of mean force between sidechain-sidechain, sidechain-backbone, and backbone-backbone pairs. The energetic parameters are scaled with the aim of matching the second virial coefficient of lysozyme reported in experiment. We also investigate the performance of several bond-building strategies.

Prediction of solution properties and dynamics of RNAs by means of Brownian dynamics simulation of coarse-grained models: Ribosomal 5S RNA and phenylalanine transfer RNA

Background

The possibility of validating biological macromolecules with locally disordered domains like RNA against solution properties is helpful to understand their function. In this work, we present a computational scheme for predicting global properties and mimicking the internal dynamics of RNA molecules in solution. A simple coarse-grained model with one bead per nucleotide and two types of intra-molecular interactions (elastic interactions and excluded volume interactions) is used to represent the RNA chain. The elastic interactions are modeled by a set of Hooke springs that form a minimalist elastic network. The Brownian dynamics technique is employed to simulate the time evolution of the RNA conformations.

Results

That scheme is applied to the 5S ribosomal RNA of E. Coli and the yeast phenylalanine transfer RNA. From the Brownian trajectory, several solution properties (radius of gyration, translational diffusion coefficient, and a rotational relaxation time) are calculated. For the case of yeast phenylalanine transfer RNA, the time evolution and the probability distribution of the inter-arm angle is also computed.

Conclusions

The general good agreement between our results and some experimental data indicates that the model is able to capture the tertiary structure of RNA in solution. Our simulation results also compare quite well with other numerical data. An advantage of the scheme described here is the possibility of visualizing the real time macromolecular dynamics.

Electronic supplementary material

The online version of this article (doi:10.1186/s13628-015-0025-7) contains supplementary material, which is available to authorized users.

Computational methods toward accurate RNA structure prediction using coarse-grained and all-atom models

Computational methods can provide significant insights into RNA structure and dynamics, bridging the gap in our understanding of the relationship between structure and biological function. Simulations enrich and enhance our understanding of data derived on the bench, as well as provide feasible alternatives to costly or technically challenging experiments. Coarse-grained computational models of RNA are especially important in this regard, as they allow analysis of events occurring in timescales relevant to RNA biological function, which are inaccessible through experimental methods alone. We have developed a three-bead coarse-grained model of RNA for discrete molecular dynamics simulations. This model is efficient in de novo prediction of short RNA tertiary structure, starting from RNA primary sequences of less than 50 nucleotides. To complement this model, we have incorporated additional base-pairing constraints and have developed a bias potential reliant on data obtained from hydroxyl probing experiments that guide RNA folding to its correct state. By introducing experimentally derived constraints to our computer simulations, we are able to make reliable predictions of RNA tertiary structures up to a few hundred nucleotides. Our refined model exemplifies a valuable benefit achieved through integration of computation and experimental methods.

High-resolution modeling of protein structures based on flexible fitting of low-resolution structural data

To circumvent the difficulty of directly solving high-resolution biomolecular structures, low-resolution structural data from Cryo-electron microscopy (EM) and small angle solution X-ray scattering (SAXS) are increasingly used to explore multiple conformational states of biomolecular assemblies. One promising venue to obtain high-resolution structural models from low-resolution data is via data-constrained flexible fitting. To this end, we have developed a new method based on a coarse-grained Cα-only protein representation, and a modified form of the elastic network model (ENM) that allows large-scale conformational changes while maintaining the integrity of local structures including pseudo-bonds and secondary structures. Our method minimizes a pseudo-energy which linearly combines various terms of the modified ENM energy with an EM/SAXS-fitting score and a collision energy that penalizes steric collisions. Unlike some previous flexible fitting efforts using the lowest few normal modes, our method effectively utilizes all normal modes so that both global and local structural changes can be fully modeled with accuracy. This method is also highly efficient in computing time. We have demonstrated our method using adenylate kinase as a test case which undergoes a large open-to-close conformational change. The EM-fitting method is available at a web server (http://enm.lobos.nih.gov), and the SAXS-fitting method is available as a pre-compiled executable upon request.

Influence of cross-link structure, density and mechanical properties in the mesoscale deformation mechanisms of collagen fibrils

Collagen is a ubiquitous protein with remarkable mechanical properties. It is highly elastic, shows large fracture strength and enables substantial energy dissipation during deformation. Most of the connective tissue in humans consists of collagen fibrils composed of a staggered array of tropocollagen molecules, which are connected by intermolecular cross-links. In this study, we report a three-dimensional coarse-grained model of collagen and analyze the influence of enzymatic cross-links on the mechanics of collagen fibrils. Two representatives immature and mature cross-links are implemented in the mesoscale model using a bottom-up approach. By varying the number, type and mechanical properties of cross-links in the fibrils and performing tensile test on the models, we systematically investigate the deformation mechanisms of cross-linked collagen fibrils. We find that cross-linked fibrils exhibit a three phase behavior, which agrees closer with experimental results than what was obtained using previous models. The fibril mechanical response is characterized by: (i) an initial elastic deformation corresponding to the collagen molecule uncoiling, (ii) a linear regime dominated by molecule sliding and (iii) the second stiffer elastic regime related to the stretching of the backbone of the tropocollagen molecules until the fibril ruptures. Our results suggest that both cross-link density and type dictate the stiffness of large deformation regime by increasing the number of interconnected molecules while cross-links mechanical properties determine the failure strain and strength of the fibril. These findings reveal that cross-links play an essential role in creating an interconnected fibrillar material of tunable toughness and strength.