Solution scattering approaches to dynamical ordering in biomolecular systems

Clarification of solution structure and its modulation in proteins and protein complexes is crucially important to understand dynamical ordering in macromolecular systems. Small-angle x-ray scattering (SAXS) and small-angle neutron scattering (SANS) are among the most powerful techniques to derive structural information. Recent progress in sample preparation, instruments and software analysis is opening up a new era for small-angle scattering. In this review, recent progress and trends of SAXS and SANS are introduced from the point of view of instrumentation and analysis, touching on general features and standard methods of small-angle scattering. This article is part of a Special Issue entitled “Biophysical Exploration of Dynamical Ordering of Biomolecular Systems” edited by Dr. Koichi Kato.     

A QM/MM study of the complexes formed by aluminum and iron with serum transferrin at neutral and acidic pH

Serum transferrin (sTf) transports iron in serum and internalizes in cells via receptor mediated endocytosis. Additionally, sTf has been identified as the predominant aluminum carrier in serum. Some questions remain unclear about the exact mechanism for the metal release or whether the aluminum and iron show the same binding mode during the entire process. In the present work, simulation techniques at quantum and atomic levels have been employed in order to gain access into a molecular level understanding of the metal-bound sTf complex, and to describe the binding of Al(III) and Fe(III) ions to sTf. First, hybrid quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations were carried out in order to analyze the dynamics of the aluminum-loaded complex, taking into account the different pH conditions in blood and into the cell. Moreover, the complexes formed by transferrin with Al(III) and Fe(III) were optimized with high level density functional theory (DFT)/MM methods. All these results indicate that the interaction mode of Al(III) and Fe(III) with sTf change upon different pH conditions, and that the coordination of Al(III) and Fe(III) is not equivalent during the metal intake, transport and release processes. Our results emphasize the importance of the pH on the metal binding and release mechanism and suggest that Al(III) can follow the iron pathway to get access into cells, although once there, it may show a different binding mode, leading to a different mechanism for its release.     

Quasi-boundary based on exchange symmetry theory for multilevel simulations

In this contribution we propose a novel method (QUEST) which enables the simulation of diffusive systems through quantum mechanical/molecular mechanical (QM/MM) molecular dynamics. The method is an evolution of boundary based on exchange symmetry theory (BEST), an approach based on imposing a bias potential to hinder exchanges between QM and MM particles. This new method corrects for the main shortcoming of BEST, namely that only static properties could be studied, as the dynamics was disrupted. With Quasi-BEST (QUEST) the dynamics is still preserved, albeit at some additional cost in the computation of energy and forces as they are needed for the exchanged configurations between QM and MM particles. Here we describe the theoretical basis of QUEST, and we present the results on a small toy system.     

Optimization of cutting schemes for the evaluation of molecular electrostatic potentials in proteins via Moving-Domain QM/MM

This work presents new developments of the moving-domain QM/MM (MoD-QM/MM) method for modeling protein electrostatic potentials. The underlying goal of the method is to map the electronic density of a specific protein configuration into a point-charge distribution. Important modifications of the general strategy of the MoD-QM/MM method involve new partitioning and fitting schemes and the incorporation of dynamic effects via a single-step free energy perturbation approach (FEP). Selection of moderately sized QM domains partitioned between and C (from C=O), with incorporation of delocalization of electrons over neighboring domains, results in a marked improvement of the calculated molecular electrostatic potential (MEP). More importantly, we show that the evaluation of the electrostatic potential can be carried out on a dynamic framework by evaluating the free energy difference between a non-polarized MEP and a polarized MEP. A simplified form of the potassium ion channel protein Gramicidin-A from Bacillus brevis is used as the model system for the calculation of MEP. Figure Schematic representation of the Moving Domain QM/MM method     

Oxygen affinity controlled by dynamical distal conformations: the soybean leghemoglobin and the Paramecium caudatum hemoglobin cases

The binding of diatomic ligands, such as O(2), NO, and CO, to heme proteins is a process intimately related with their function. In this work, we analyzed by means of a combination of classical Molecular Dynamics (MD) and Hybrid Quantum-Classical (QM/MM) techniques the existence of multiple conformations in the distal site of heme proteins and their influence on oxygen affinity regulation. We considered two representative examples: soybean leghemoglobin (Lba) and Paramecium caudatum truncated hemoglobin (PcHb). The results presented in this work provide a molecular interpretation for the kinetic, structural, and mutational data that cannot be obtained by assuming a single distal conformation.     

Native structure-based modeling and simulation of biomolecular systems per mouse click

Background

Molecular dynamics (MD) simulations provide valuable insight into biomolecular systems at the atomic level. Notwithstanding the ever-increasing power of high performance computers current MD simulations face several challenges: the fastest atomic movements require time steps of a few femtoseconds which are small compared to biomolecular relevant timescales of milliseconds or even seconds for large conformational motions. At the same time, scalability to a large number of cores is limited mostly due to long-range interactions. An appealing alternative to atomic-level simulations is coarse-graining the resolution of the system or reducing the complexity of the Hamiltonian to improve sampling while decreasing computational costs. Native structure-based models, also called Gō-type models, are based on energy landscape theory and the principle of minimal frustration. They have been tremendously successful in explaining fundamental questions of, e.g., protein folding, RNA folding or protein function. At the same time, they are computationally sufficiently inexpensive to run complex simulations on smaller computing systems or even commodity hardware. Still, their setup and evaluation is quite complex even though sophisticated software packages support their realization.

Results

Here, we establish an efficient infrastructure for native structure-based models to support the community and enable high-throughput simulations on remote computing resources via GridBeans and UNICORE middleware. This infrastructure organizes the setup of such simulations resulting in increased comparability of simulation results. At the same time, complete workflows for advanced simulation protocols can be established and managed on remote resources by a graphical interface which increases reusability of protocols and additionally lowers the entry barrier into such simulations for, e.g., experimental scientists who want to compare their results against simulations. We demonstrate the power of this approach by illustrating it for protein folding simulations for a range of proteins.

Conclusions

We present software enhancing the entire workflow for native structure-based simulations including exception-handling and evaluations. Extending the capability and improving the accessibility of existing simulation packages the software goes beyond the state of the art in the domain of biomolecular simulations. Thus we expect that it will stimulate more individuals from the community to employ more confidently modeling in their research.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-292) contains supplementary material, which is available to authorized users.     

Theoretical investigation on the diatomic ligand migration process and ligand binding properties in non‐O2‐binding H‐NOX domain

The Nostoc sp (Ns) H‐NOX (heme‐nitric oxide or OXygen‐binding) domain shares 35% sequence identity with soluble guanylate cyclase (sGC) and exhibits similar ligand binding property with the sGC. Previously, our molecular dynamic (MD) simulation work identified that there exists a Y‐shaped tunnel system hosted in the Ns H‐NOX interior, which servers for ligand migration. The tunnels were then confirmed by Winter et al. [PNAS 2011;108(43):E 881–889] recently using x‐ray crystallography with xenon pressured conditions. In this work, to further investigate how the protein matrix of Ns H‐NOX modulates the ligand migration process and how the distal residue composition affects the ligand binding prosperities, the free energy profiles for nitric oxide (NO), carbon monooxide (CO), and O₂ migration are explored using the steered MDs simulation and the ligand binding energies are calculated using QM/MM schemes. The potential of mean force profiles suggest that the longer branch of the tunnel would be the most favorable route for NO migration and a second NO trapping site other than the distal heme pocket along this route in the Ns H‐NOX was identified. On the contrary, CO and O₂ would prefer to diffuse via the shorter branch of the tunnel. The QM/MM (quantum mechanics/molecular mechanics) calculations suggest that the hydrophobic distal pocket of Ns H‐NOX would provide an approximately vacuum environment and the ligand discrimination would be determined by the intrinsic binding properties of the diatomic gas ligand to the heme group. Proteins 2013; 81:1363–1376. © 2013 Wiley Periodicals, Inc.     

All-atom simulations to studying metallodrugs/target interactions

Metallodrugs are extensively used to treat and diagnose distinct disease types. The unique physical–chemical properties of metal ions offer tantalizing opportunities to tailor effective scaffolds for selectively targeting specific biomolecules. Modern experimental techniques have collected a large body of structural data concerning the interactions of metallodrugs with their biomolecular targets, although being unable to exhaustively assess the molecular basis of their mechanism of action.In this scenario, the complementary use of accurate computational methods allows uncovering the minutiae of metallodrugs/targets interactions and their underlying mechanism of action at an atomic-level of detail. This knowledge is increasingly perceived as an invaluable requirement to rationally devise novel and selective metallodrugs. Building on literature studies, selected largely from the last 2 years, this compendium encompasses a cross-section of the current role, advances, and challenges met by computer simulations to decipher the mechanistic intricacies of prototypical metallodrugs.     

Molecular modeling of cobalt(II) hyaluronate

Structural data for complexes of hyaluronic acid and 3d metals(II) of the fourth group of the periodic table are lacking. A combined QM/MM method was used to solve the structure of the first coordination sphere around the cobalt(II) ion. Some available experimental data were compared with the results obtained via computation and were found to be in good agreement. Our results open the way for using molecular modeling to solve the structure of other metal(II) hyaluronates.     

Modeling of a propagation mechanism of infectious prion protein; a hexamer as the minimum infectious unit

To construct a new model of the propagation mechanism of infectious scrapie-type prion protein (PrP(Sc)), here we conducted a disruption simulation of a PrP(Sc) nonamer using structure-based molecular dynamics simulation method based on a hypothetical PrP(Sc) model structure. The simulation results showed that the nonamer disrupted in cooperative manners into monomers via two significant intermediate states: (1) a nonamer with a partially unfolded surface trimer and (2) a hexamer and three monomers. Dimers and trimers were rarely observed. Then, we propose a new PrP(Sc) propagation mechanism where a hexamer plays an essential role as a minimum infectious unit.     

An update view on the substrate recognition mechanism of phosphodiesterases: a computational study of PDE10 and PDE4 bound with cyclic nucleotides

Early studies strongly implied that the specificity of cyclic nucleotide phosphodiesterases (PDEs) toward its endogenous substrates can be uniquely determined by the amido orientation of the invariant glutamine locating in the binding pocket of the enzyme. However, recently solved crystal structures of PDE4 (cAMP specific) and PDE10 (dual specific) in the presence of endogenous substrates have revealed that their invariant glutamine orientations are very similar despite exhibiting different substrate specificities proven physiologically. To understand this subtle specificity issue in the PDE family, here several experimentally inaccessible PDE-substrate complex models have been studied computationally, and the results are juxtaposed and compared in detail. Modeling results show that PDE10 in fact favors cAMP energetically but still can bind to cGMP owing to the robust hydrogen-bond network in the vicinity of the invariant glutamine side chain. PDE4 fails to accommodate cGMP is correlated to the weakening of this same hydrogen-bond network but not owing to any steric strain in the binding pocket. An Asn residue in the binding pocket of PDE4 has enhanced the specificity of the binding to cAMP sideway as observed in our computer simulation. Further to the previously studied syn- versus anti-conformational specificity of cAMP in PDE10, the unexpected substrate-binding mode in PDE10 versus PDE4 as reported here strongly suggested that there are remaining uncertainties in the substrate orientation and recognition mechanism in the PDE families. The molecular details of the binding pocket observed in this study provide hints for more optimal PDE4 and PDE10 inhibitor design.     

Acetylcholinesterase: mechanisms of covalent inhibition of H447I mutant determined by computational analyses

The reaction mechanisms of two inhibitor TFK(+) and TFK(0) binding to H447I mutant mouse acetylcholinesterase (mAChE) have been investigated by using a combined ab initio quantum mechanical/molecular mechanical (QM/MM) approach and classical molecular dynamics (MD) simulations. TFK(+) binding to the H447I mutant may proceed with a different reaction mechanism from the wild-type. A water molecule takes over the role of His447 and participates in the bond breaking and forming as a "charge relayer". Unlike in the wild-type mAChE case, Glu334, a conserved residue from the catalytic triad, acts as a catalytic base in the reaction. The calculated energy barrier for this reaction is about 8kcal/mol. These predictions await experimental verification. In the case of the neutral ligand TFK(0), however, multiple MD simulations on the TFK(0)/H447I complex reveal that none of the water molecules can be retained in the active site as a "catalytic" water. Taken together our computational studies confirm that TFK(0) is almost inactive in the H447I mutant, and also provide detailed mechanistic insights into the experimental observations.     

A comparative study of trypsin specificity based on QM/MM molecular dynamics simulation and QM/MM GBSA calculation

Hydrogen bonding and polar interactions play a key role in identification of protein-inhibitor binding specificity. Quantum mechanics/molecular mechanics molecular dynamics (QM/MM MD) simulations combined with DFT and semi-empirical Hamiltonian (AM1d, RM1, PM3, and PM6) methods were performed to study the hydrogen bonding and polar interactions of two inhibitors BEN and BEN1 with trypsin. The results show that the accuracy of treating the hydrogen bonding and polar interactions using QM/MM MD simulation of PM6 can reach the one obtained by the DFT QM/MM MD simulation. Quantum mechanics/molecular mechanics generalized Born surface area (QM/MM-GBSA) method was applied to calculate binding affinities of inhibitors to trypsin and the results suggest that the accuracy of binding affinity prediction can be significantly affected by the accurate treatment of the hydrogen bonding and polar interactions. In addition, the calculated results also reveal the binding specificity of trypsin: (1) the amidinium groups of two inhibitors generate favorable salt bridge interaction with Asp189 and form hydrogen bonding interactions with Ser190 and Gly214, (2) the phenyl of inhibitors can produce favorable van der Waals interactions with the residues His58, Cys191, Gln192, Trp211, Gly212, and Cys215. This systematic and comparative study can provide guidance for the choice of QM/MM MD methods and the designs of new potent inhibitors targeting trypsin.     

Ligand‐based pharmacophore modelling and screening of DNA minor groove binders targeting Staphylococcus aureus

The recognition of DNA by small molecules is of special importance in the design of new drugs. Many natural and synthetic compounds have the ability to interact with the minor groove of DNA. In the present study, identification of minor groove binding compounds was attained by the combined approach of pharmacophore modelling, virtual screening and molecular dynamics approach. Experimentally reported 32 minor groove binding compounds were used to develop the pharmacophore model. Based on the fitness score, best three pharmacophore hypotheses were selected and used as template for screening the compounds from drug bank database. This pharmacophore‐based screening provides many compounds with the same pharmacological properties. All these compounds were subjected to four phases of docking protocols with combined Glide‐quantum‐polarized ligand docking approach. Molecular dynamics results indicated that selected compounds are more active and showed good interaction in the binding site of DNA. Based on the scoring parameters and energy values, the best compounds were selected, and antibacterial activity of these compounds was identified using in vitro antimicrobial techniques. Copyright © 2014 John Wiley & Sons, Ltd.     

Use of multistate Bennett acceptance ratio method for free-energy calculations from enhanced sampling and free-energy perturbation

Multistate Bennett acceptance ratio (MBAR) works as a method to analyze molecular dynamics (MD) simulation data after the simulations have been finished. It is widely used to estimate free-energy changes between different states and averaged properties at the states of interest. MBAR allows us to treat a wide range of states from those at different temperature/pressure to those with different model parameters. Due to the broad applicability, the MBAR equations are rather difficult to apply for free-energy calculations using different types of MD simulations including enhanced conformational sampling methods and free-energy perturbation. In this review, we first summarize the basic theory of the MBAR equations and categorize the representative usages into the following four: (i) perturbation, (ii) scaling, (iii) accumulation, and (iv) full potential energy. For each, we explain how to prepare input data using MD simulation trajectories for solving the MBAR equations. MBAR is also useful to estimate reliable free-energy differences using MD trajectories based on a semi-empirical quantum mechanics/molecular mechanics (QM/MM) model and ab initio QM/MM energy calculations on the MD snapshots. We also explain how to use the MBAR software in the GENESIS package, which we call mbar_analysis, for the four representative cases. The proposed estimations of free-energy changes and thermodynamic averages are effective and useful for various biomolecular systems.     

Computational modeling of carbohydrate processing enzymes reactions

Carbohydrate processing enzymes are of biocatalytic interest. Glycoside hydrolases and the recently discovered lytic polysaccharide monooxygenase for their use in biomass degradation to obtain biofuels or valued chemical entities. Glycosyltransferases or engineered glycosidases and phosphorylases for the synthesis of carbohydrates and glycosylated products. Quantum mechanics-molecular mechanics (QM/MM) methods are highly contributing to establish their different chemical reaction mechanisms. Other computational methods are also used to study enzyme conformational changes, ligand pathways, and processivity, e.g. for processive glycosidases like cellobiohydrolases. There is still a long road to travel to fully understand the role of conformational dynamics in enzyme activity and also to disclose the variety of reaction mechanisms these enzymes employ. Additionally, computational tools for enzyme engineering are beginning to be applied to evaluate substrate specificity or aid in the design of new biocatalysts with increased thermostability or tailored activity, a growing field where molecular modeling is finding its way.     

Emerging computational approaches for the study of protein allostery

Allosteric regulation of protein function is key in controlling cellular processes so its underlying mechanisms are of primary concern to research in areas spanning protein engineering and drug design. However, due to the complex nature of allosteric mechanisms, a clear and predictive understanding of the relationship between protein structure and allosteric function remains elusive. Well established experimental approaches are available to offer a limited degree of characterization of mechanical properties within proteins, but the analytical capabilities of computational methods are evolving rapidly in their ability to accurately define the subtle and concerted structural dynamics that comprise allostery. This review includes a brief overview of allostery in proteins and an exploration of relevant experimental methods. An explanation of the transition from experimental toward computational methods for allostery is discussed, followed by a review of existing and emerging methods.     

一类与传染病模型有关的积分方程的定性性质

证明了一类与传染病模型有关的积分方程解的唯一性,整体存在性和当t→∞时收敛到零的若干充分条件.利用Banach不动点定理证明了存在性结果,利用一个新的积分不等式证明了收敛性结果.     

QM/MM and free-energy simulations of deacylation reaction catalysed by sedolisin,a serine-carboxyl peptidase

Quantum mechanical/molecular mechanical free-energy simulations were performed to understand the deacylation reaction catalysed by sedolisin (a serine-carboxyl peptidase) and to elucidate the catalytic mechanism and the role of the active-site residues during the process. The results given here demonstrate that Asp170 may act as a general acid/base catalyst for the deacylation reaction. It is also shown that the electrostatic oxyanion hole interactions involving Asp170 may be less effective in transition state stabilisation for the deacylation step in the sedolisin-catalysed reaction compared to the general acid/base mechanism. The proton transfer processes during the enzyme-catalysed process were examined, and their role in the catalysis was discussed.