Exploring Binding Mechanisms between Curcumin and Silkworm 30Kc19 Protein Using Spectroscopic Analyses and Computational Simulations

The curry compound, curcumin exerts multiple health-promotive functions; however, its poor solubility and stability limits its biological applications. In this study, we illuminate intermolecular binding mechanisms in the nano-sized complex of curcumin with silkworm protein, 30Kc19. The intrinsic fluorescence of 30Kc19 was gradually quenched by the increase of curcumin concentrations, which demonstrates molecule-molecule complexations mediated by the fluorophore amino acid residues (Tyr, Trp) in the protein. The fluorescence quenching showed that the binding occurred at 1:1 molar ratio with binding constant of 3.28 × 10⁴ M^-1. The results from scanning electron microscopy and dynamic light scattering indicate that the complexes were formed with cubicle shapes and sizes of 200–250 nm at pH 8.0 (zeta-potential < ?20 mV). Along with Fourier transform infrared analysis, computational studies of protein-ligand docking simulation suggest a mechanism that curcumin and 30Kc19 forms complexes through specific amino acid residues (Trp174, Trp180, and Trp225) with minimum binding distance (4 Å). The complexation of curcumin with 30Kc19 protein effectively suppressed the degradation of curcumin over 10 h and improved its antioxidant activity up to 30%. These findings suggest an application of 30Kc19 for the delivery of waterinsoluble bioactive medicines.     

Computational Simulations of the Early Steps of Protein Aggregation

There is strong evidence that the oligomers of key proteins, formed during the early steps of aggregation, could be the primary toxic species associated with human neurodegenerative diseases, such as Alzheimer’s and prion diseases. Here, we review recent progress in the development of computational approaches in order to understand the structures, dynamics and free energy surfaces of oligomers. We also discuss possible research directions for the coming years.     

Computational Simulations of the Early Steps of Protein Aggregation

There is strong evidence that the oligomers of key proteins, formed during the early steps of aggregation, could be the primary toxic species associated with human neurodegenerative diseases, such as Alzheimer''s and prion diseases. Here, we review recent progress in the development of computational approaches in order to understand the structures, dynamics and free energy surfaces of oligomers. We also discuss possible research directions for the coming years.Key Words: protein aggregation, simulations, amyloid fibril, oligomers, coarse-grained model, inhibitors     

Computational Models Reveal a Passive Mechanism for Cell Migration in the Crypt

Cell migration in the intestinal crypt is essential for the regular renewal of the epithelium, and the continued upward movement of cells is a key characteristic of healthy crypt dynamics. However, the driving force behind this migration is unknown. Possibilities include mitotic pressure, active movement driven by motility cues, or negative pressure arising from cell loss at the crypt collar. It is possible that a combination of factors together coordinate migration. Here, three different computational models are used to provide insight into the mechanisms that underpin cell movement in the crypt, by examining the consequence of eliminating cell division on cell movement. Computational simulations agree with existing experimental results, confirming that migration can continue in the absence of mitosis. Importantly, however, simulations allow us to infer mechanisms that are sufficient to generate cell movement, which is not possible through experimental observation alone. The results produced by the three models agree and suggest that cell loss due to apoptosis and extrusion at the crypt collar relieves cell compression below, allowing cells to expand and move upwards. This finding suggests that future experiments should focus on the role of apoptosis and cell extrusion in controlling cell migration in the crypt.     

Computational studies of membrane proteins: Models and predictions for biological understanding

We discuss recent progresses in computational studies of membrane proteins based on physical models with parameters derived from bioinformatics analysis. We describe computational identification of membrane proteins and prediction of their topology from sequence, discovery of sequence and spatial motifs, and implications of these discoveries. The detection of evolutionary signal for understanding the substitution pattern of residues in the TM segments and for sequence alignment is also discussed. We further discuss empirical potential functions for energetics of inserting residues in the TM domain, for interactions between TM helices or strands, and their applications in predicting lipid-facing surfaces of the TM domain. Recent progresses in structure predictions of membrane proteins are also reviewed, with further discussions on calculation of ensemble properties such as melting temperature based on simplified state space model. Additional topics include prediction of oligomerization state of membrane proteins, identification of the interfaces for protein-protein interactions, and design of membrane proteins. This article is part of a Special Issue entitled: Protein Folding in Membranes.     

Developing and Optimising the Use of Logic Models in Systematic Reviews: Exploring Practice and Good Practice in the Use of Programme Theory in Reviews

Background

Logic models are becoming an increasingly common feature of systematic reviews, as is the use of programme theory more generally in systematic reviewing. Logic models offer a framework to help reviewers to ‘think’ conceptually at various points during the review, and can be a useful tool in defining study inclusion and exclusion criteria, guiding the search strategy, identifying relevant outcomes, identifying mediating and moderating factors, and communicating review findings.

Methods and Findings

In this paper we critique the use of logic models in systematic reviews and protocols drawn from two databases representing reviews of health interventions and international development interventions. Programme theory featured only in a minority of the reviews and protocols included. Despite drawing from different disciplinary traditions, reviews and protocols from both sources shared several limitations in their use of logic models and theories of change, and these were used almost unanimously to solely depict pictorially the way in which the intervention worked. Logic models and theories of change were consequently rarely used to communicate the findings of the review.

Conclusions

Logic models have the potential to be an aid integral throughout the systematic reviewing process. The absence of good practice around their use and development may be one reason for the apparent limited utility of logic models in many existing systematic reviews. These concerns are addressed in the second half of this paper, where we offer a set of principles in the use of logic models and an example of how we constructed a logic model for a review of school-based asthma interventions.     

Exploring the Use of a Guanine-Rich Catalytic DNA for Sulfoxide Preparation

A guanine-rich DNA oligonucleotide complexed with hemin was used to catalyze controlled oxygen transfer reactions to different sulfides for sulfoxide preparation in the presence of H₂O₂. Comparable activities were obtained when using fully modified L-DNA. In addition, oligonucleotide immobilization led to an active catalyst which could be successfully recovered and reused without loss of activity.     

Local Perturbation Analysis: A Computational Tool for Biophysical Reaction-Diffusion Models

Diffusion and interaction of molecular regulators in cells is often modeled using reaction-diffusion partial differential equations. Analysis of such models and exploration of their parameter space is challenging, particularly for systems of high dimensionality. Here, we present a relatively simple and straightforward analysis, the local perturbation analysis, that reveals how parameter variations affect model behavior. This computational tool, which greatly aids exploration of the behavior of a model, exploits a structural feature common to many cellular regulatory systems: regulators are typically either bound to a membrane or freely diffusing in the interior of the cell. Using well-documented, readily available bifurcation software, the local perturbation analysis tracks the approximate early evolution of an arbitrarily large perturbation of a homogeneous steady state. In doing so, it provides a bifurcation diagram that concisely describes various regimes of the model’s behavior, reducing the need for exhaustive simulations to explore parameter space. We explain the method and provide detailed step-by-step guides to its use and application.     

树鼩肝炎动物模型的研究进展

肝炎的的大范围流行已成为国内外关注的重要公共卫生问题之一。甲肝、乙肝虽已有疫苗,但不能忽视未来由于病毒变异所带来的威胁。丙肝目前尚未发现非常有效的疫苗,且丙肝的病理学机制也尚未完全清晰,主要原因是缺乏理想的动物模型。树胸属于低等灵长类动物。研究发现,他对很多人类疾病易感,所以建立肝炎树胸动物模型成为现在肝炎研究的一个热点。本文介绍了各型肝炎主要是甲、乙、丙型肝炎研究中建立树胸动物模型的自内外进展情况及存在的问题。     

High-Performance Drug Discovery: Computational Screening by Combining Docking and Molecular Dynamics Simulations

Virtual compound screening using molecular docking is widely used in the discovery of new lead compounds for drug design. However, this method is not completely reliable and therefore unsatisfactory. In this study, we used massive molecular dynamics simulations of protein-ligand conformations obtained by molecular docking in order to improve the enrichment performance of molecular docking. Our screening approach employed the molecular mechanics/Poisson-Boltzmann and surface area method to estimate the binding free energies. For the top-ranking 1,000 compounds obtained by docking to a target protein, approximately 6,000 molecular dynamics simulations were performed using multiple docking poses in about a week. As a result, the enrichment performance of the top 100 compounds by our approach was improved by 1.6–4.0 times that of the enrichment performance of molecular dockings. This result indicates that the application of molecular dynamics simulations to virtual screening for lead discovery is both effective and practical. However, further optimization of the computational protocols is required for screening various target proteins.     

The Possible Structural Models for Polyglutamine Aggregation: A Molecular Dynamics Simulations Study

Abstract

Huntington's disease is a neurodegenerative disorder caused by a polyglutamine (polyQ) expansion near the N-terminus of huntingtin. Previous studies have suggested that polyQ aggregation occurs only when the number of glutamine (Q) residues is more than 36-40, the disease threshold. However, the structural characteristics of polyQ nucleation in the very early stage of aggregation still remain elusive. In this study, we designed 18 simulation trials to determine the possible structural models for polyQ nucleation and aggregation with various shapes and sizes of initial β-helical structures, such as left-handed circular, right-handed rectangular, and left- and right-handed triangular. Our results show that the stability of these models significantly increases with increasing the number of rungs, while it is rather insensitive to the number of Qs in each rung. In particular, the 3-rung β-helical models are stable when they adopt the left-handed triangular and right-handed rectangular conformations due to the fact that they preserve high β-turn and β-sheet contents, respectively, during the simulation courses. Thus, we suggested that these two stable β-helical structures with at least 3 rungs might serve as the possible nucleation seeds for polyQ depending on how the structural elements of β-turn and β-sheet are sampled and preserved during the very early stage of aggregation.     

Using Molecular Dynamics Simulations on Crambin to Evaluate the Suitability of Different Continuum Dielectric and Hydrogen Atom Models for Protein Simulations

Abstract

Molecular dynamics simulations of enzymes with enough explicit waters of solvation to realistically account for solute-solvent interactions can burden the computational resources required to perform the simulation by more than two orders of magnitude. Since enzyme simulations even with an implicit solvation model can be imposing for a supercomputer, it is important to assess the suitability of different continuum dielectric models for protein simulations. A series of 100-picosecond molecular dynamics simulations were performed on the X-ray crystal structure of the protein crambin to examine how well computed structures, obtained using seven continuum dielectric and two hydrogen atom models, agreed with the X-ray structure. The best level of agreement between computed and experimental structures was obtained using a constant dielectric of 2 and the all-hydrogen model. Continuum dielectric models of 1,1^*r, and 2^*r also led to computed structures in reasonably good agreement with the X-ray structure. In all cases, the all-hydrogen model gave better agreement than the united atom model, although, in one case, the difference was not significant. Dielectric models of 4, 80, and 4^*r with either hydrogen model yielded significantly poorer fits. It is especially noteworthy that the observed trends did not semiquantitatively converge until about 50 picoseconds into the simulations, suggesting that validation studies for protein calculations based on energy minimizations or short simulations should be viewed with caution.     

Molecular Dynamics Simulations of a DMPC Bilayer Using Nonadditive Interaction Models

We present a polarizable force field based on the charge-equilibration formalism for molecular dynamics simulations of phospholipid bilayers. We discuss refinement of headgroup dihedral potential parameters to reproduce ab initio conformational energies of dimethylphosphate calculated at the MP2/cc-pVTZ level of theory. We also address the refinement of electrostatic and Lennard-Jones (van der Waals) parameters to reproduce ab initio polarizabilities and water interaction energies of dimethylphosphate and tetramethylammonium. We present results of molecular dynamics simulations of a solvated dimyristoylphosphatidylcholine bilayer using this polarizable force field as well as the nonpolarizable, fixed-charge CHARMM27 and CHARMM27r force fields for comparison. Calculated atomic and electron-density profiles, deuterium order parameters, and headgroup orientations are found to be consistent with previous simulations and with experiment. Polarizable interaction models for solvent and lipid exhibit greater water penetration into the lipid interior; this is due to the variation of water molecular dipole moment from a bulk value of 2.6 Debye to a value of 1.9 Debye in the membrane interior. The reduction in the electrostatic component of the desolvation free-energy penalty allows for greater water density. The surface dipole potential predicted by the polarizable model is 0.95 V compared to the value of 0.8 V based on nonpolarizable force-field calculations. Effects of inclusion of explicit polarization are discussed in relation to water dipole moment and varying charge distributions. Dielectric permittivity profiles for polarizable and nonpolarizable interactions exhibit subtle differences arising from the nature of the individual component parameterizations; for the polarizable force field, we obtain a bulk dielectric permittivity of 79, whereas the nonpolarizable force field plateaus at 97 (the value for pure TIP3P water). In the membrane interior, both models predict unit permittivities, with the polarizable models contributing from one to two more units due to the optical dielectric (high-frequency dipole fluctuations). This contribution is a step toward the continuing development of a CHARMM (Chemistry at Harvard Molecular Mechanics) polarizable force field for simulations of biomacromolecular systems.     

A Comparison of Computational Models for Eukaryotic Cell Shape and Motility

Eukaryotic cell motility involves complex interactions of signalling molecules, cytoskeleton, cell membrane, and mechanics interacting in space and time. Collectively, these components are used by the cell to interpret and respond to external stimuli, leading to polarization, protrusion, adhesion formation, and myosin-facilitated retraction. When these processes are choreographed correctly, shape change and motility results. A wealth of experimental data have identified numerous molecular constituents involved in these processes, but the complexity of their interactions and spatial organization make this a challenging problem to understand. This has motivated theoretical and computational approaches with simplified caricatures of cell structure and behaviour, each aiming to gain better understanding of certain kinds of cells and/or repertoire of behaviour. Reaction–diffusion (RD) equations as well as equations of viscoelastic flows have been used to describe the motility machinery. In this review, we describe some of the recent computational models for cell motility, concentrating on simulations of cell shape changes (mainly in two but also three dimensions). The problem is challenging not only due to the difficulty of abstracting and simplifying biological complexity but also because computing RD or fluid flow equations in deforming regions, known as a “free-boundary” problem, is an extremely challenging problem in applied mathematics. Here we describe the distinct approaches, comparing their strengths and weaknesses, and the kinds of biological questions that they have been able to address.     

Exploring the Potential Use of Seismic Waves as a Communication Channel by Elephants and Other Large Mammals

Bioseismic studies have previously documented the use of seismicstimuli as a method of communication in arthropods and smallmammals. Seismic signals are used to communicate intraspecificallyin many capacities such as mate finding, spacing, warning, resourceassessing, and in group cohesion. Seismic signals are also usedin interspecific mutualism and as a deterrent to predators.Although bioseismics is a significant mode of communicationthat is well documented for relatively small vertebrates, thepotential for seismic communication has been all but ignoredin large mammals. In this paper, we describe two modes of producingseismic waves with the potential for long distance transmission:1) locomotion by animals causing percussion on the ground and2) acoustic, seismic-evoking sounds that couple with the ground.We present recordings of several mammals, including lions, rhinoceroses,and elephants, showing that they generate similar acoustic andseismic vibrations. These large animals that produce high amplitudevocalizations are the most likely to produce seismic vibrationsthat propagate long distances. The elephant seems to be themost likely candidate to engage in long distance seismic communicationdue to its size and its high amplitude, low frequency, relativelymonotonic vocalizations that propagate in the ground and havethe potential to travel long distances. We review particularanatomical features of the elephant that would facilitate thedetection of seismic waves. We also assess low frequency soundsin the environment such as thunder and the likelihood of seismictransmission. In addition, we present the potential role ofseismic stimuli in human communication as well as the impactof modern anthropogenic effects on the seismic environment.     

Predictive Computational Models of Substrate Binding by a Nucleoside Transporter

Transporters play a vital role in both the resistance mechanisms of existing drugs and effective targeting of their replacements. Melarsoprol and diamidine compounds similar to pentamidine and furamidine are primarily taken up by trypanosomes of the genus Trypanosoma brucei through the P2 aminopurine transporter. In standardized competition experiments with [³H]adenosine, P2 transporter inhibition constants (K_i) have been determined for a diverse dataset of adenosine analogs, diamidines, Food and Drug Administration-approved compounds and analogs thereof, and custom-designed trypanocidal compounds. Computational biology has been employed to investigate compound structure diversity in relation to P2 transporter interaction. These explorations have led to models for inhibition predictions of known and novel compounds to obtain information about the molecular basis for P2 transporter inhibition. A common pharmacophore for P2 transporter inhibition has been identified along with other key structural characteristics. Our model provides insight into P2 transporter interactions with known compounds and contributes to strategies for the design of novel antiparasitic compounds. This approach offers a quantitative and predictive tool for molecular recognition by specific transporters without the need for structural or even primary sequence information of the transport protein.