The Folding of de Novo Designed Protein DS119 via Molecular Dynamics Simulations

As they are not subjected to natural selection process, de novo designed proteins usually fold in a manner different from natural proteins. Recently, a de novo designed mini-protein DS119, with a βαβ motif and 36 amino acids, has folded unusually slowly in experiments, and transient dimers have been detected in the folding process. Here, by means of all-atom replica exchange molecular dynamics (REMD) simulations, several comparably stable intermediate states were observed on the folding free-energy landscape of DS119. Conventional molecular dynamics (CMD) simulations showed that when two unfolded DS119 proteins bound together, most binding sites of dimeric aggregates were located at the N-terminal segment, especially residues 5–10, which were supposed to form β-sheet with its own C-terminal segment. Furthermore, a large percentage of individual proteins in the dimeric aggregates adopted conformations similar to those in the intermediate states observed in REMD simulations. These results indicate that, during the folding process, DS119 can easily become trapped in intermediate states. Then, with diffusion, a transient dimer would be formed and stabilized with the binding interface located at N-terminals. This means that it could not quickly fold to the native structure. The complicated folding manner of DS119 implies the important influence of natural selection on protein-folding kinetics, and more improvement should be achieved in rational protein design.     

Folding of Trp-cage Mini Protein Using Temperature and Biasing Potential Replica��Exchange Molecular Dynamics Simulations

The folding process of the 20 residue Trp-cage mini-protein was investigated using standard temperature replica exchange molecular dynamics (T-RexMD) simulation and a biasing potential RexMD (BP-RexMD) method. In contrast to several conventional molecular dynamics simulations, both RexMD methods sampled conformations close to the native structure after 10–20 ns simulation time as the dominant conformational states. In contrast, to T-RexMD involving 16 replicas the BP-RexMD method achieved very similar sampling results with only five replicas. The result indicates that the BP-RexMD method is well suited to study folding processes of proteins at a significantly smaller computational cost, compared to T-RexMD. Both RexMD methods sampled not only similar final states but also agreed on the sampling of intermediate conformations during Trp-cage folding. The analysis of the sampled potential energy contributions indicated that Trp-cage folding is favored by both van der Waals and to a lesser degree electrostatic contributions. Folding does not introduce any significant sterical strain as reflected by similar energy distributions of bonded energy terms (bond length, bond angle and dihedral angle) of folded and unfolded Trp-cage structures.     

Molecular dynamics simulations of ovalbumin adsorption at squalene/water interface

The adsorption of protein molecules to oil/water (O/W) interface is of critical importance for the product design in a wide range of technologies and industries such as biotechnology, food industry and pharmaceutical industry. In this work, with ovalbumin (OVA) as the model protein, the adsorption conformations at the O/W interface and the adsorption stability have been systematically studied via multiple simulation methods, including all-atom molecular dynamic (AAMD) simulations, coarse-grained molecular dynamic (CGMD) simulations and enhanced sampling methods. The computational results of AAMD and CGMD show that the hydrophobic tail of OVA tends to be folded under long time relaxation in aqueous phase, and multiple adsorption conformations can exist at the interface due to heterogeneous interactions raising from oil and water respectively. To further study the adsorption sites of the protein, the adsorption kinetics of OVA at the O/W interface is simulated using metadynamics method combined with CGMD simulations, and the result suggests the existence of multiple adsorption conformations of OVA at interface with the head-on conformation as the most stable one. In all, this work focuses on the adsorption behaviors of OVA at squalene/water interface, and provides a theoretical basis for further functionalization of the proteins in emulsion-based products and engineering.     

Transition Pathway and Its Free-Energy Profile: A Protocol for Protein Folding Simulations

We propose a protocol that provides a systematic definition of reaction coordinate and related free-energy profile as the function of temperature for the protein-folding simulation. First, using action-derived molecular dynamics (ADMD), we investigate the dynamic folding pathway model of a protein between a fixed extended conformation and a compact conformation. We choose the pathway model to be the reaction coordinate, and the folding and unfolding processes are characterized by the ADMD step index, in contrast to the common a priori reaction coordinate as used in conventional studies. Second, we calculate free-energy profile as the function of temperature, by employing the replica-exchange molecular dynamics (REMD) method. The current method provides efficient exploration of conformational space and proper characterization of protein folding/unfolding dynamics from/to an arbitrary extended conformation. We demonstrate that combination of the two simulation methods, ADMD and REMD, provides understanding on molecular conformational changes in proteins. The protocol is tested on a small protein, penta-peptide of met-enkephalin. For the neuropeptide met-enkephalin system, folded, extended, and intermediate sates are well-defined through the free-energy profile over the reaction coordinate. Results are consistent with those in the literature.     

Protein–Protein Docking with Large-Scale Backbone Flexibility Using Coarse-Grained Monte-Carlo Simulations

Most of the protein–protein docking methods treat proteins as almost rigid objects. Only the side-chains flexibility is usually taken into account. The few approaches enabling docking with a flexible backbone typically work in two steps, in which the search for protein–protein orientations and structure flexibility are simulated separately. In this work, we propose a new straightforward approach for docking sampling. It consists of a single simulation step during which a protein undergoes large-scale backbone rearrangements, rotations, and translations. Simultaneously, the other protein exhibits small backbone fluctuations. Such extensive sampling was possible using the CABS coarse-grained protein model and Replica Exchange Monte Carlo dynamics at a reasonable computational cost. In our proof-of-concept simulations of 62 protein–protein complexes, we obtained acceptable quality models for a significant number of cases.     

Pyranose Ring Puckering Thermodynamics for Glycan Monosaccharides Associated with Vertebrate Proteins

The conformational properties of carbohydrates can contribute to protein structure directly through covalent conjugation in the cases of glycoproteins and proteoglycans and indirectly in the case of transmembrane proteins embedded in glycolipid-containing bilayers. However, there continue to be significant challenges associated with experimental structural biology of such carbohydrate-containing systems. All-atom explicit-solvent molecular dynamics simulations provide a direct atomic resolution view of biomolecular dynamics and thermodynamics, but the accuracy of the results depends on the quality of the force field parametrization used in the simulations. A key determinant of the conformational properties of carbohydrates is ring puckering. Here, we applied extended system adaptive biasing force (eABF) all-atom explicit-solvent molecular dynamics simulations to characterize the ring puckering thermodynamics of the ten common pyranose monosaccharides found in vertebrate biology (as represented by the CHARMM carbohydrate force field). The results, along with those for idose, demonstrate that the CHARMM force field reliably models ring puckering across this diverse set of molecules, including accurately capturing the subtle balance between ⁴C₁ and ¹C₄ chair conformations in the cases of iduronate and of idose. This suggests the broad applicability of the force field for accurate modeling of carbohydrate-containing vertebrate biomolecules such as glycoproteins, proteoglycans, and glycolipids.     

Multiscale molecular modeling in nanostructured material design and process system engineering

Atomistic-based simulations such as molecular mechanics, molecular dynamics, and Monte Carlo-based methods have come into wide use for material design. Using these atomistic simulation tools, we can analyze molecular structure on the scale of 0.1–10 nm. However, difficulty arises concerning limitations of the time and length scale involved in the simulation. Although a possible molecular structure can be simulated by the atom-based simulations, it is less realistic to predict the mesoscopic structure defined on the scale of 100–1000 nm, for example the morphology of polymer blends and composites, which often dominates actual material properties. For the morphology on these scales, mesoscopic simulations such as the dynamic mean field density functional theory and dissipative particle dynamics are available as alternatives to atomistic simulations. It is therefore inevitable to adopt a mesoscopic simulation technique and bridge the gap between atomistic and mesoscopic simulations for an effective material design. Furthermore, it is possible to transfer the simulated mesoscopic structure to finite elements modeling tools for calculating macroscopic properties for the systems of interest.In this contribution, a hierarchical procedure for bridging the gap between atomistic and macroscopic modeling passing through mesoscopic simulations will be presented and discussed. The concept of multiscale (or many scale) modeling will be outlined, and examples of applications of single scale and multiscale procedures for nanostructured systems of industrial interest will be presented. In particular the following industrial applications will be considered: (i) polymer-organoclay nanocomposites of a montmorillonite–polymer–surface modifier system; (ii) mesoscale simulation for diblock copolymers with dispersion of nanoparticels; (iii) polymer–carbon nanotubes system and (iv) applications of multiscale modeling for process systems engineering.     

A Hamiltonian Replica Exchange Molecular Dynamics (MD) Method for the Study of Folding,Based on the Analysis of the Stabilization Determinants of Proteins

Herein, we present a novel Hamiltonian replica exchange protocol for classical molecular dynamics simulations of protein folding/unfolding. The scheme starts from the analysis of the energy-networks responsible for the stabilization of the folded conformation, by means of the energy-decomposition approach. In this framework, the compact energetic map of the native state is generated by a preliminary short molecular dynamics (MD) simulation of the protein in explicit solvent. This map is simplified by means of an eigenvalue decomposition. The highest components of the eigenvector associated with the lowest eigenvalue indicate which sites, named “hot spots”, are likely to be responsible for the stability and correct folding of the protein. In the Hamiltonian replica exchange protocol, we use modified force-field parameters to treat the interparticle non-bonded potentials of the hot spots within the protein and between protein and solvent atoms, leaving unperturbed those relative to all other residues, as well as solvent-solvent interactions. We show that it is possible to reversibly simulate the folding/unfolding behavior of two test proteins, namely Villin HeadPiece HP35 (35 residues) and Protein A (62 residues), using a limited number of replicas. We next discuss possible implications for the study of folding mechanisms via all atom simulations.     

Refinement of protein cores and protein-peptide interfaces using a potential scaling approach

Refinement of side chain conformations in protein model structures and at the interface of predicted protein-protein or protein-peptide complexes is an important step during protein structural modelling and docking. A common approach for side chain prediction is to assume a rigid protein main chain for both docking partners and search for an optimal set of side chain rotamers to optimize the steric fit. However, depending on the target-template similarity in the case of comparative protein modelling and on the accuracy of an initially docked complex, the main chain template structure is only an approximation of a realistic target main chain. An inaccurate rigid main chain conformation can in turn interfere with the prediction of side chain conformations. In the present study, a potential scaling approach (PS-MD) during a molecular dynamics (MD) simulation that also allows the inclusion of explicit solvent has been used to predict side chain conformations on semi-flexible protein main chains. The PS-MD method converges much faster to realistic protein-peptide interface structures or protein core structures than standard MD simulations. Depending on the accuracy of the protein main chain, it also gives significantly better results compared with the standard rotamer search method.     

Protein dynamics determined by backbone conformation and atom packing

To study the factors determining the collective motions in thermal, conformational fluctuations of a globular protein, molecular dynamics simulations were performed with a backbone model and an atomic-level model. In the backbone model, only the C alpha atoms were explicitly treated with two types of pairwise interactions assigned between the C alpha atoms; atom-packing interactions to take into account the effect of tight atom packing in the protein interior and chain-restoring interactions to maintain the backbone around the native conformation. A quasi-harmonic method was used to decompose the overall fluctuations into independent, collective modes. The modes assigned to large conformational fluctuations showed a good correlation between the backbone and atomic-level models. From this study, it was suggested that the collective modes were motions in which a protein fluctuates, keeping the tertiary structure around the native one and avoiding backbone overlap and, hence, rough aspects of the collective modes can be derived without details of the atomic interactions. The backbone model is useful in obtaining the overall backbone motions of a protein without heavy simulations, even though the simulation starts from a poorly determined conformation of experiments and in sampling main chain conformations, from which the side chain conformations may be predicted.      

Coarse-Grained and Atomistic MD Simulations of RNA and DNA Folding

Although the main features of the protein folding problem are coming into clearer focus, the microscopic viewpoint of nucleic acid folding mechanisms is only just beginning to be addressed. Experiments, theory, and simulations are pointing to complex thermodynamic and kinetic mechanisms. As is the case for proteins, molecular dynamics (MD) simulations continue to be indispensable tools for providing a molecular basis for nucleic acid folding mechanisms. In this review, we provide an overview of biomolecular folding mechanisms focusing on nucleic acids. We outline the important interactions that are likely to be the main determinants of nucleic acid folding energy landscapes. We discuss recent MD simulation studies of empirical force field and Go-type MD simulations of RNA and DNA folding mechanisms to outline recent successes and the theoretical and computational challenges that lie ahead.     

Multiscale computer simulation of polymer nanocomposites based on thermoplastics

A literature review is presented on a multiscale approach to the simulation of nanocomposites based on thermoplastic polymers that includes calculations using quantum-chemical methods and molecular dynamics simulations with the use of full-atomic and mesoscopic models. Common problems arising during the multiscale simulation of thermoplastic nanocomposites and the ways to solve them are discussed. The results of studies of the structural, thermal, and mechanical properties of thermoplastic nanocomposites obtained via the simulation with consideration for the detailed chemical structures of components are given.     

The Influences of Sulphation,Salt Type,and Salt Concentration on the Structural Heterogeneity of Glycosaminoglycans

The increasing recognition of the biochemical importance of glycosaminoglycans (GAGs) has in recent times made them the center of attention of recent research investigations. It became evident that subtle conformational factors play an important role in determining the relationship between the chemical composition of GAGs and their activity. Therefore, a thorough understanding of their structural flexibility is needed, which is addressed in this work by means of all-atom molecular dynamics (MD) simulations. Four major GAGs with different substitution patterns, namely hyaluronic acid as unsulphated GAG, heparan-6-sulphate, chondroitin-4-sulphate, and chondroitin-6-sulphate, were investigated to elucidate the influence of sulphation on the dynamical features of GAGs. Moreover, the effects of increasing NaCl and KCl concentrations were studied as well. Different structural parameters were determined from the MD simulations, in combination with a presentation of the free energy landscape of the GAG conformations, which allowed us to unravel the conformational fingerprints unique to each GAG. The largest effects on the GAG structures were found for sulphation at position 6, as well as binding of the metal ions in the absence of chloride ions to the carboxylate and sulphate groups, which both increase the GAG conformational flexibility.     

Protein folds and protein folding

The classification of protein folds is necessarily based on the structural elements that distinguish domains. Classification of protein domains consists of two problems: the partition of structures into domains and the classification of domains into sets of similar structures (or folds). Although similar topologies may arise by convergent evolution, the similarity of their respective folding pathways is unknown. The discovery and the characterization of the majority of protein folds will be followed by a similar enumeration of available protein folding pathways. Consequently, understanding the intricacies of structural domains is necessary to understanding their collective folding pathways. We review the current state of the art in the field of protein domain classification and discuss methods for the systematic and comprehensive study of protein folding across protein fold space via atomistic molecular dynamics simulation. Finally, we discuss our large-scale Dynameomics project, which includes simulations of representatives of all autonomous protein folds.     

Multiscale modeling for polymer systems of industrial interest

Atomistic-based simulations such as molecular mechanics (MM), molecular dynamics (MD), and Monte Carlo-based methods (MC) have come into wide use for materials design. Using these atomistic simulation tools, one can analyze molecular structure on the scale of 0.1–10 nm. Although molecular structures can be studied easily and extensively by these atom-based simulations, it is less realistic to predict structures defined on the scale of 100–1000 nm with these methods. For the morphology on these scales, mesoscopic modeling techniques such as the dynamic mean field density functional theory (Mesodyn) and dissipative particle dynamics (DPD) are now available as effective simulation tools. Furthermore, it is possible to transfer the simulated mesoscopic structure to finite element modeling tools (FEM) for calculating macroscopic properties for a given system of interest. In this paper, we present a hierarchical procedure for bridging the gap between atomistic and macroscopic modeling passing through mesoscopic simulations. In particular, we will discuss the concept of multiscale modeling, and present examples of applications of multiscale procedures to polymer–organoclay nanocomposites. Examples of application of multiscale modeling to immiscible polymer blends and polymer–carbon nanotubes systems will also be presented.     

Multiscale modeling of heat conduction in graphene laminates

We developed a combined atomistic-continuum hierarchical multiscale approach to explore the effective thermal conductivity of graphene laminates. To this aim, we first performed molecular dynamics simulations in order to study the heat conduction at atomistic level. Using the non-equilibrium molecular dynamics method, we evaluated the length dependent thermal conductivity of graphene as well as the thermal contact conductance between two individual graphene sheets. In the next step, based on the results provided by the molecular dynamics simulations, we constructed finite element models of graphene laminates to probe the effective thermal conductivity at macroscopic level. A similar methodology was also developed to study the thermal conductivity of laminates made from hexagonal boron-nitride (h-BN) films. In agreement with recent experimental observations, our multiscale modeling confirms that the flake size is the main factor that affects the thermal conductivity of graphene and h-BN laminates. Provided information by the proposed multiscale approach could be used to guide experimental studies to fabricate laminates with tunable thermal conduction properties.     

Effects of Model Protein Environments on the Dynamics of Proton Wires

The multiconfigurational molecular dynamics with quantum transitions (MC-MDQT) method is utilized to study the impact of model protein environments on the dynamics of proton wires. The MC-MDQT method allows the realtime nonequilibrium quantum dynamical simulation of proton transport along water chains and provides a framework for analyzing the detailed dynamical mechanisms of these multiple proton transfer reactions. In this paper, the protein environment is modeled by applying structural restraints to the oxygen atoms of the chain, by applying external electric fields, and by including solvating water molecules hydrogen-bonded to the ends of the water chain. Our simulations illustrate that the protein environment could strongly impact the dynamics of proton wires through a combination of structural restraints, fluctuating electric fields, solvation, and hydrogen bonding. Our simulations also indicate that quantum effects such as hydrogen tunneling and nonadiabatic transitions play a significant role under certain nonequilibrium conditions.     

Comparison of ras-p21 bound to GDP and GTP: differences in protein and ligand dynamics

This paper documents the first essential dynamics analysis of ras protein ligands and of the protein itself, showing important features of their dynamic properties. Essential dynamics analysis of 300 ps of full solvent molecular dynamics simulations revealed differences in structure and dynamics between GDP- and GTP-bound forms of H-ras-p21. Regions in the protein which exhibited a structural shift correspond to the switch regions described previously. Differences in dynamics between H-ras-p21 GDP and H-ras-p21 GTP may be related to interactions of ras with GAP and its receptor and effector. Molecular dynamics of free GDP (in the absence of protein) were performed in water for 2 ns and analysed using essential dynamics. The conformations of GDP and GTP when bound to the protein were compared with free GDP, revealing that the ligands bind to the protein in an energetically unfavourable conformation. GDP and GTP molecules from various other protein crystal structures were also analysed. These ligands adopt similar conformations to those seen in H-ras-p21.      

水化层影响酸酐酶内CO2扩散行为的分子动力学模拟

气相中酶分子表面的水化层对其催化行为具有显著的影响。本文采用全原子分子动力学模拟方法考察了气相体系碳酸酐酶表面的水化层对酶结构以及CO₂在酶分子中扩散行为的影响。首先展现了水分子在酶分子及其活性中心周围的分布,研究了水化层厚度对于酶结构以及CO₂扩散速率的影响;发现最有利于CO₂扩散进入酶分子的水化层厚度为0.7 nm。确认了碳酸酐酶内CO₂的吸附位点,通过对其开合状态统计,显示出碳酸酐酶中CO₂扩散通道中的瓶颈位置。上述结果对设计和优化碳酸酐酶催化气相体系中CO₂的吸附和转化提供了依据和启示。     

Liquid li structure and dynamics: A comparison between OFDFT and second nearest‐neighbor embedded‐atom method

The structure and dynamics of liquid lithium are studied using two simulation methods: orbital‐free (OF) first‐principles molecular dynamics (MD), which employs OF density functional theory (DFT), and classical MD utilizing a second nearest‐neighbor embedded‐atom method potential. The properties studied include the dynamic structure factor, the self‐diffusion coefficient, the dispersion relation, the viscosity, and the bond angle distribution function. Simulation results were compared to available experimental data when possible. Each method has distinct advantages and disadvantages. For example, OFDFT gives better agreement with experimental dynamic structure factors, yet is more computationally demanding than classical simulations. Classical simulations can access a broader temperature range and longer time scales. The combination of first‐principles and classical simulations is a powerful tool for studying properties of liquid lithium. © 2015 American Institute of Chemical Engineers AIChE J, 61: 2841–2853, 2015