Boron Uptake in Salt Cedars via Aquaporins

Salt Cedar (Tamarix) is a dicot plant highly tolerant to the chemical boron. This is interesting because for most plants boron is an essential yet toxic metalloid. Plants have a hard time excluding it. The goal of the project is to identify a potential protein sequence (order of amino acids forming a protein) for an aquaporin that allows the transport of boron, moving through a pore. In addition to selecting the sequences, a 3D model of the protein has been constructed to see how boron is entering the cells through the channels of these proteins. A dynamic model is being made to examine the structure in a cell membrane. We have assembled 3D models of these channel proteins using computer software programs that build models based on the sequences. The sequence of a protein determines how it works. Changing the sequence changes how it works. Dynamic modeling the protein’s structure has begun, to see how the structure fluctuates. The diameter of the channel/pore is a critical value being calculated. In the static model the pore was not large enough for boron to pass through. In the dynamic model the pore should have a larger size at times. The pore size will determine if boron will fit through the channel. We expect this channel to have a lower presence in the roots of this plant, thus limiting boron uptake. This research is important because plants are currently facing boron tolerance issues across the world and particularly in the southwest region in the United States

NMR-Based Computational Studies of Membrane Proteins in Explicit Membranes

Since nuclear magnetic resonance (NMR) spectroscopy data, including solution NMR from micelles and solid-state NMR from bilayers, provide valuable structural and dynamics information of membrane proteins, they are commonly used as restraints in structural determination methods for membrane proteins. However, most of these methods determine the protein structures by fitting the single-confer model into all available NMR restraints regardless of the explicit environmental effects that are determinant in the structures of membrane proteins. To develop a reliable protocol for obtaining optimal structures of membrane proteins in their native-like environments, various NMR properties were applied in the refinement approaches using explicit molecular dynamics (MD) simulations in this research. First, solution NMR NOE based-distance measurements were used as restraints in MD simulations to refine an activating immunoreceptor complex in explicit environments. Compared to the structure determined in vacuum, the resulting structures from the explicit restrained simulations yields a more favorable and realistic side-chain arrangement of a key Asp residue, which is highly consistent with mutagenesis studies on such residue. Incorporating solid-state NMR and solution NMR, MD simulations were performed in the explicit bilayers to refine the structure of membrane-bound Pf1 coat protein. Since solid-state NMR is sparse in its N-terminal periplasmic helix, the protein structure was determined by combining solid-state NMR and solution NMR. Benefiting from the sophisticated energy function and the explicit environments in MD, the orientation of Pf1's periplasmic helix can be identified in simulations restrained by solid-state NMR alone. In the simulations restrained with both solid-state NMR and solution NMR, physically irrelevant structures were frequently observed, suggesting there are conflicts between the restraints from different sample types (e.g., bilayers and micelles). As NMR data are ensemble-averaged measures, the solid-state NMR restrained explicit ensemble dynamics (ED) simulations of fd coat protein were performed in different ensemble sizes and compared to the unrestrained MD simulations. As the ensemble size increases, the violations of resulting structures from experimental NMR data decrease, while the structural variations increase to be comparable to the unrestrained MD simulations, indicating the efficacy of restrained ED in refining structures and extracting dynamics. To investigate the influence of different environments on the structures of membrane proteins, in this research, MD simulations were performed in bilayers and micelles, respectively. Since building a preassembled protein/micelle complex for MD simulation is challenging and requires considerable experience with simulation software, a web-based graphical interface Micelle Builder in CHARMM-GUI (http://www.charmm-gui.org/input/micelle) was developed to support users to build micelle systems in a automatic and simplified process. Using this interface, Pf1 coat protein was preassembled in a protein/micelle model and simulated in explicit environment. Compared to previous simulations of Pf1 coat protein in bilayers, different protein conformations were observed in these simulations due to the distinct behavior and geometry of micelles

Membrane models for molecular simulations of peripheral membrane proteins

Peripheral membrane proteins (PMPs) bind temporarily to the surface of biological membranes. They also exist in a soluble form and their tertiary structure is often known. Yet, their membrane-bound form and their interfacial-binding site with membrane lipids remain difficult to observe directly. Their binding and unbinding mechanism, the conformational changes of the PMPs and their influence on the membrane structure are notoriously challenging to study experimentally. Molecular dynamics simulations are particularly useful to fill some knowledge-gaps and provide hypothesis that can be experimentally challenged to further our understanding of PMP-membrane recognition. Because of the time-scales of PMP-membrane binding events and the computational costs associated with molecular dynamics simulations, membrane models at different levels of resolution are used and often combined in multiscale simulation strategies. We here review membrane models belonging to three classes: atomistic, coarse-grained and implicit. Differences between models are rooted in the underlying theories and the reference data they are parameterized against. The choice of membrane model should therefore not only be guided by its computational efficiency. The range of applications of each model is discussed and illustrated using examples from the literature.publishedVersio

Computational Modeling of Realistic Cell Membranes

Cell membranes contain a large variety of lipid types and are crowded with proteins, endowing them with the plasticity needed to fulfill their key roles in cell functioning. The compositional complexity of cellular membranes gives rise to a heterogeneous lateral organization, which is still poorly understood. Computational models, in particular molecular dynamics simulations and related techniques, have provided important insight into the organizational principles of cell membranes over the past decades. Now, we are witnessing a transition from simulations of simpler membrane models to multicomponent systems, culminating in realistic models of an increasing variety of cell types and organelles. Here, we review the state of the art in the field of realistic membrane simulations and discuss the current limitations and challenges ahead

Two decades of Martini:Better beads, broader scope

The Martini model, a coarse-grained force field for molecular dynamics simulations, has been around for nearly two decades. Originally developed for lipid-based systems by the groups of Marrink and Tieleman, the Martini model has over the years been extended as a community effort to the current level of a general-purpose force field. Apart from the obvious benefit of a reduction in computational cost, the popularity of the model is largely due to the systematic yet intuitive building-block approach that underlies the model, as well as the open nature of the development and its continuous validation. The easy implementation in the widely used Gromacs software suite has also been instrumental. Since its conception in 2002, the Martini model underwent a gradual refinement of the bead interactions and a widening scope of applications. In this review, we look back at this development, culminating with the release of the Martini 3 version in 2021. The power of the model is illustrated with key examples of recent important findings in biological and material sciences enabled with Martini, as well as examples from areas where coarse-grained resolution is essential, namely high-throughput applications, systems with large complexity, and simulations approaching the scale of whole cells. This article is categorized under: Software > Molecular Modeling Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods Structure and Mechanism > Computational Materials Science Structure and Mechanism > Computational Biochemistry and Biophysics

Structural Influences on the Photochemistry and Photophysical Properties of p-Phenylene Ethynylenes: Aggregation Effects and Solvent Interactions

Compounds based on the p-phenylene ethynylene backbone with pendant charged groups, known as conjugated polyelectrolytes, have been of particular interest in recent years due to their solubility in water, sensing properties, and biocidal activity against bacteria, viruses, and fungi. A series of oligomers based on these polymers were synthesized (OPEs), and several interesting questions about their photophysical and biocidal properties were raised by earlier experimental observations, which are addressed by this dissertation. The study initially focuses on the influence of the backbone length and presence of carboxyester substituents on the photophysical properties of the OPEs. Next, the photochemistry of the OPEs is explored as the products and mechanisms are elucidated through isotopic studies with mass spectrometry, revealing that photo-protonation by water and addition of oxygen across the triple bond are the two dominant initial mechanisms of all major pathways in aqueous solution. Finally, the aggregation of OPEs with is studied in two systems: surfactants and model bacterial membranes. The placement of the ionic alkyl substituents played a dominant role in determining the outcome of molecular interactions and type of aggregates which resulted between OPEs and both systems. Biophysical simulations of the interactions between OPEs and these two systems provided mechanistic insight into the mechanism of bacterial membrane disruption and the attenuation of photodegradation observed with OPE-surfactant complexes. In addition to determining the OPEs could be protected from photolysis and the structural basis for aggregate type, surfactant complexation was used to form a biocidal complex from a non-biocidal anionic OPE. The work presented will be of great use for future developments in sensors, biocides, photo-resistant materials, and drug delivery applications

Curvature as a Collective Coordinate in Enhanced Sampling Membrane Simulations

International audienceThe plasticity of membranes plays an important functional role in cells, cell components, and micelles, where bending, budding, and remodeling implement numerous recognition and communication processes. Comparatively, molecular simulation methods to induce, control, and quantitatively characterize such deformations remain scarce. This work defines a novel collective coordinate associated with membrane bending, which strives to combine realism (by preserving the notion of local atomic curvatures) and low computational cost (allowing its evaluation at every time step of a molecular dynamics simulation). Enhanced sampling simulations along this conformational coordinate provide convenient access to the underlying bending free energy landscape. To showcase its potential, the method is applied to three state-of-the-art problems: the determination of the bending free energy landscape of a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE) bilayer, the formation of a POPE liposome, and the study of the influence of the Pseudomonas quinolone signal on the budding of Gram-negative bacterial outer membranes