Self-Assembly of Phenylalanine Oligopeptides: Insights from Experiments and Simulations

Studies of peptide-based nanostructures provide general insights into biomolecular self-assembly and can lead material engineering toward technological applications. The diphenylalanine peptide (FF) self-assembles into discrete, hollow, well ordered nanotubes, and its derivatives form nanoassemblies of various morphologies. Here we demonstrate for the first time, to our knowledge, the formation of planar nanostructures with β-sheet content by the triphenylalanine peptide (FFF). We characterize these structures using various microscopy and spectroscopy techniques. We also obtain insights into the interactions and structural properties of the FF and FFF nanostructures by 0.4-μs, implicit-solvent, replica-exchange, molecular-dynamics simulations of aqueous FF and FFF solutions. In the simulations the peptides form aggregates, which often contain open or ring-like peptide networks, as well as elementary and network-containing structures with β-sheet characteristics. The networks are stabilized by polar and nonpolar interactions, and by the surrounding aggregate. In particular, the charged termini of neighbor peptides are involved in hydrogen-bonding interactions and their aromatic side chains form “T-shaped” contacts, as in three-dimensional FF crystals. These interactions may assist the FF and FFF self-assembly at the early stage, and may also stabilize the mature nanostructures. The FFF peptides have higher network propensities and increased aggregate stabilities with respect to FF, which can be interpreted energetically.     

Mechanosensitive Channels: Insights from Continuum-Based Simulations

Mechanotransduction plays an important role in regulating cell functions and it is an active topic of research in biophysics. Despite recent advances in experimental and numerical techniques, the intrinsic multiscale nature imposes tremendous challenges for revealing the working mechanisms of mechanosensitive channels. Recently, a continuum-mechanics-based hierarchical modeling and simulation framework has been established and applied to study the mechanical responses and gating behaviors of a prototypical mechanosensitive channel, the mechanosensitive channel of large conductance (MscL) in bacteria Escherichia coli (E. coli), from which several putative gating mechanisms have been tested and new insights are deduced. This article reviews these latest findings using the continuum mechanics framework and suggests possible improvements for future simulation studies. This computationally efficient and versatile continuum-mechanics-based protocol is poised to make contributions to the study of a variety of mechanobiology problems.     

Accurate PDZ/Peptide Binding Specificity with Additive and Polarizable Free Energy Simulations

PDZ domains contain 80–100 amino acids and bind short C-terminal sequences of target proteins. Their specificity is essential for cellular signaling pathways. We studied the binding of the Tiam1 PDZ domain to peptides derived from the C-termini of its Syndecan-1 and Caspr4 targets. We used free energy perturbation (FEP) to characterize the binding energetics of one wild-type and 17 mutant complexes by simulating 21 alchemical transformations between pairs of complexes. Thirteen complexes had known experimental affinities. FEP is a powerful tool to understand protein/ligand binding. It depends, however, on the accuracy of molecular dynamics force fields and conformational sampling. Both aspects require continued testing, especially for ionic mutations. For six mutations that did not modify the net charge, we obtained excellent agreement with experiment using the additive, AMBER ff99SB force field, with a root mean square deviation (RMSD) of 0.37 kcal/mol. For six ionic mutations that modified the net charge, agreement was also good, with one large error (3 kcal/mol) and an RMSD of 0.9 kcal/mol for the other five. The large error arose from the overstabilization of a protein/peptide salt bridge by the additive force field. Four of the ionic mutations were also simulated with the polarizable Drude force field, which represents the first test of this force field for protein/ligand binding free energy changes. The large error was eliminated and the RMS error for the four mutations was reduced from 1.8 to 1.2 kcal/mol. The overall accuracy of FEP indicates it can be used to understand PDZ/peptide binding. Importantly, our results show that for ionic mutations in buried regions, electronic polarization plays a significant role.     

VASP: A Volumetric Analysis of Surface Properties Yields Insights into Protein-Ligand Binding Specificity

Many algorithms that compare protein structures can reveal similarities that suggest related biological functions, even at great evolutionary distances. Proteins with related function often exhibit differences in binding specificity, but few algorithms identify structural variations that effect specificity. To address this problem, we describe the Volumetric Analysis of Surface Properties (VASP), a novel volumetric analysis tool for the comparison of binding sites in aligned protein structures. VASP uses solid volumes to represent protein shape and the shape of surface cavities, clefts and tunnels that are defined with other methods. Our approach, inspired by techniques from constructive solid geometry, enables the isolation of volumetrically conserved and variable regions within three dimensionally superposed volumes. We applied VASP to compute a comparative volumetric analysis of the ligand binding sites formed by members of the steroidogenic acute regulatory protein (StAR)-related lipid transfer (START) domains and the serine proteases. Within both families, VASP isolated individual amino acids that create structural differences between ligand binding cavities that are known to influence differences in binding specificity. Also, VASP isolated cavity subregions that differ between ligand binding cavities which are essential for differences in binding specificity. As such, VASP should prove a valuable tool in the study of protein-ligand binding specificity.     

Protein Partitioning into Ordered Membrane Domains: Insights from Simulations

Cellular membranes are laterally organized into domains of distinct structures and compositions by the differential interaction affinities between various membrane lipids and proteins. A prominent example of such structures are lipid rafts, which are ordered, tightly packed domains that have been widely implicated in cellular processes. The functionality of raft domains is driven by their selective recruitment of specific membrane proteins to regulate their interactions and functions; however, there have been few general insights into the factors that determine the partitioning of membrane proteins between coexisting liquid domains. In this work, we used extensive coarse-grained and atomistic molecular dynamics simulations, potential of mean force calculations, and conceptual models to describe the partitioning dynamics and energetics of a model transmembrane domain from the linker of activation of T cells. We find that partitioning between domains is determined by an interplay between protein-lipid interactions and differential lipid packing between raft and nonraft domains. Specifically, we show that partitioning into ordered domains is promoted by preferential interactions between peptides and ordered lipids, mediated in large part by modification of the peptides by saturated fatty acids (i.e., palmitoylation). Ordered phase affinity is also promoted by elastic effects, specifically hydrophobic matching between the membrane and the peptide. Conversely, ordered domain partitioning is disfavored by the tight molecular packing of the lipids therein. The balance of these dominant drivers determines partitioning. In the case of the wild-type linker of activation of T cells transmembrane domain, these factors combine to yield enrichment of the peptide at L_o/L_d interfaces. These results define some of the general principles governing protein partitioning between coexisting membrane domains and potentially explain previous disparities among experiments and simulations across model systems.     

The NorM MATE Transporter from N. gonorrhoeae: Insights into Drug and Ion Binding from Atomistic Molecular Dynamics Simulations

The multidrug and toxic compound extrusion transporters extrude a wide variety of substrates out of both mammalian and bacterial cells via the electrochemical gradient of protons and cations across the membrane. The substrates transported by these proteins include toxic metabolites and antimicrobial drugs. These proteins contribute to multidrug resistance in both mammalian and bacterial cells and are therefore extremely important from a biomedical perspective. Although specific residues of the protein are known to be responsible for the extrusion of solutes, mechanistic details and indeed structures of all the conformational states remain elusive. Here, we report the first, to our knowledge, simulation study of the recently resolved x-ray structure of the multidrug and toxic compound extrusion transporter, NorM from Neisseria gonorrhoeae (NorM_NG). Multiple, atomistic simulations of the unbound and bound forms of NorM in a phospholipid lipid bilayer allow us to identify the nature of the drug-protein/ion-protein interactions, and secondly determine how these interactions contribute to the conformational rearrangements of the protein. In particular, we identify the molecular rearrangements that occur to enable the Na⁺ ion to enter the cation-binding cavity even in the presence of a bound drug molecule. These include side chain flipping of a key residue, GLU-261 from pointing toward the central cavity to pointing toward the cation binding side when bound to a Na⁺ ion. Our simulations also provide support for cation binding in the drug-bound and apo states of NorM_NG.     

Methylation-independent DNA Binding Modulates Specificity of Repressor of Silencing 1 (ROS1) and Facilitates Demethylation in Long Substrates

DNA cytosine methylation is an epigenetic mark that promotes gene silencing and performs critical roles during reproduction and development in both plants and animals. The genomic distribution of DNA methylation is the dynamic outcome of opposing methylation and demethylation processes. In plants, active demethylation occurs through a base excision repair pathway initiated by 5-methycytosine (5-meC) DNA glycosylases of the REPRESSOR OF SILENCING 1 (ROS1)/DEMETER (DME) family. To gain insight into the mechanism by which Arabidopsis ROS1 recognizes and excises 5-meC, we have identified those protein regions that are required for efficient DNA binding and catalysis. We have found that a short N-terminal lysine-rich domain conserved in members of the ROS1/DME family mediates strong methylation-independent binding of ROS1 to DNA and is required for efficient activity on 5-meC·G, but not for T·G processing. Removal of this domain does not significantly affect 5-meC excision from short molecules, but strongly decreases ROS1 activity on long DNA substrates. This region is not required for product binding and is not involved in the distributive behavior of the enzyme on substrates containing multiple 5-meC residues. Altogether, our results suggest that methylation-independent DNA binding allows ROS1 to perform a highly redundant search for efficient excision of a nondamaged, correctly paired base such as 5-meC in long stretches of DNA. These findings may have implications for understanding the evolution of structure and target specificity in DNA glycosylases.     

Topographic Evolution and Climate Aridification during Continental Collision: Insights from Computer Simulations

How do the feedbacks between tectonics, sediment transport and climate work to shape the topographic evolution of the Earth? This question has been widely addressed via numerical models constrained with thermochronological and geomorphological data at scales ranging from local to orogenic. Here we present a novel numerical model that aims at reproducing the interaction between these processes at the continental scale. For this purpose, we combine in a single computer program: 1) a thin-sheet viscous model of continental deformation; 2) a stream-power surface-transport approach; 3) flexural isostasy allowing for the formation of large sedimentary foreland basins; and 4) an orographic precipitation model that reproduces basic climatic effects such as continentality and rain shadow. We quantify the feedbacks between these processes in a synthetic scenario inspired by the India-Asia collision and the growth of the Tibetan Plateau. We identify a feedback between erosion and crustal thickening leading locally to a <50% increase in deformation rates in places where orographic precipitation is concentrated. This climatically-enhanced deformation takes place preferentially at the upwind flank of the growing plateau, specially at the corners of the indenter (syntaxes). We hypothesize that this may provide clues for better understanding the mechanisms underlying the intriguing tectonic aneurisms documented in the Himalayas. At the continental scale, however, the overall distribution of topographic basins and ranges seems insensitive to climatic factors, despite these do have important, sometimes counterintuitive effects on the amount of sediments trapped within the continent. The dry climatic conditions that naturally develop in the interior of the continent, for example, trigger large intra-continental sediment trapping at basins similar to the Tarim Basin because they determine its endorheic/exorheic drainage. These complex climatic-drainage-tectonic interactions make the development of steady-state topography at the continental scale unlikely.     

Cooperativity in Binding Processes: New Insights from Phenomenological Modeling

Cooperative binding is one of the most interesting and not fully understood phenomena involved in control and regulation of biological processes. Here we analyze the simplest phenomenological model that can account for cooperativity (i.e. ligand binding to a macromolecule with two binding sites) by generating equilibrium binding isotherms from deterministically simulated binding time courses. We show that the Hill coefficients determined for cooperative binding, provide a good measure of the Gibbs free energy of interaction among binding sites, and that their values are independent of the free energy of association for empty sites. We also conclude that although negative cooperativity and different classes of binding sites cannot be distinguished at equilibrium, they can be kinetically differentiated. This feature highlights the usefulness of pre-equilibrium time-resolved strategies to explore binding models as a key complement of equilibrium experiments. Furthermore, our analysis shows that under conditions of strong negative cooperativity, the existence of some binding sites can be overlooked, and experiments at very high ligand concentrations can be a valuable tool to unmask such sites.     

Thermodynamics of Long Supercoiled Molecules: Insights from Highly Efficient Monte Carlo Simulations

Supercoiled DNA polymer models for which the torsional energy depends on the total twist of molecules (Tw) are a priori well suited for thermodynamic analysis of long molecules. So far, nevertheless, the exact determination of Tw in these models has been based on a computation of the writhe of the molecules (Wr) by exploiting the conservation of the linking number, Lk = Tw + Wr, which reflects topological constraints coming from the helical nature of DNA. Because Wr is equal to the number of times the main axis of a DNA molecule winds around itself, current Monte Carlo algorithms have a quadratic time complexity, O(L²), with respect to the contour length (L) of the molecules. Here, we present an efficient method to compute Tw exactly, leading in principle to algorithms with a linear complexity, which in practice is O(L^1.2). Specifically, we use a discrete wormlike chain that includes the explicit double-helix structure of DNA and where the linking number is conserved by continuously preventing the generation of twist between any two consecutive cylinders of the discretized chain. As an application, we show that long (up to 21 kbp) linear molecules stretched by mechanical forces akin to magnetic tweezers contain, in the buckling regime, multiple and branched plectonemes that often coexist with curls and helices, and whose length and number are in good agreement with experiments. By attaching the ends of the molecules to a reservoir of twists with which these can exchange helix turns, we also show how to compute the torques in these models. As an example, we report values that are in good agreement with experiments and that concern the longest molecules that have been studied so far (16 kbp).     

The Structural Basis of IKs Ion-Channel Activation: Mechanistic Insights from Molecular Simulations

Relating ion channel (iCh) structural dynamics to physiological function remains a challenge. Current experimental and computational techniques have limited ability to explore this relationship in atomistic detail over physiological timescales. A framework associating iCh structure to function is necessary for elucidating normal and disease mechanisms. We formulated a modeling schema that overcomes the limitations of current methods through applications of artificial intelligence machine learning. Using this approach, we studied molecular processes that underlie human IKs voltage-mediated gating. IKs malfunction underlies many debilitating and life-threatening diseases. Molecular components of IKs that underlie its electrophysiological function include KCNQ1 (a pore-forming tetramer) and KCNE1 (an auxiliary subunit). Simulations, using the IKs structure-function model, reproduced experimentally recorded saturation of gating-charge displacement at positive membrane voltages, two-step voltage sensor (VS) movement shown by fluorescence, iCh gating statistics, and current-voltage relationship. Mechanistic insights include the following: 1) pore energy profile determines iCh subconductance; 2) the entire protein structure, not limited to the pore, contributes to pore energy and channel subconductance; 3) interactions with KCNE1 result in two distinct VS movements, causing gating-charge saturation at positive membrane voltages and current activation delay; and 4) flexible coupling between VS and pore permits pore opening at lower VS positions, resulting in sequential gating. The new modeling approach is applicable to atomistic scale studies of other proteins on timescales of physiological function.     

Long-Distance Communication in the HDV Ribozyme: Insights from Molecular Dynamics and Experiments

The hepatitis delta virus ribozyme is a small, self-cleaving RNA with a compact tertiary structure and buried active site that is important in the life cycle of the virus. The ribozyme's function in nature is to cleave an internal phosphodiester bond and linearize concatemers during rolling circle replication. Crystal structures of the ribozyme have been solved in both pre-cleaved and post-cleaved (product) forms and reveal an intricate network of interactions that conspire to catalyze bond cleavage. In addition, extensive biochemical studies have been performed to work out a mechanism for bond cleavage in which C75 and a magnesium ion catalyze the reaction by general acid-base chemistry. One issue that has remained unclear in this ribozyme and in other ribozymes is the nature of long-distance communication between peripheral regions of the RNA and the buried active site. We performed molecular dynamics simulations on the hepatitis delta virus ribozyme in the product form and assessed communication between a distal structural portion of the ribozyme—the protonated C41 base triple—and the active site containing the critical C75. We varied the ionization state of C41 in both the wild type and a C41 double mutant variant and determined the impact on the active site. In all four cases, effects at the active site observed in the simulations agree with experimental studies on ribozyme activity. Overall, these studies indicate that small functional RNAs have the potential to communicate interactions over long distances and that wild-type RNAs may have evolved ways to prevent such interactions from interfering with catalysis.     

Identifying and Tracking Simulated Synaptic Inputs from Neuronal Firing: Insights from In Vitro Experiments

Accurately describing synaptic interactions between neurons and how interactions change over time are key challenges for systems neuroscience. Although intracellular electrophysiology is a powerful tool for studying synaptic integration and plasticity, it is limited by the small number of neurons that can be recorded simultaneously in vitro and by the technical difficulty of intracellular recording in vivo. One way around these difficulties may be to use large-scale extracellular recording of spike trains and apply statistical methods to model and infer functional connections between neurons. These techniques have the potential to reveal large-scale connectivity structure based on the spike timing alone. However, the interpretation of functional connectivity is often approximate, since only a small fraction of presynaptic inputs are typically observed. Here we use in vitro current injection in layer 2/3 pyramidal neurons to validate methods for inferring functional connectivity in a setting where input to the neuron is controlled. In experiments with partially-defined input, we inject a single simulated input with known amplitude on a background of fluctuating noise. In a fully-defined input paradigm, we then control the synaptic weights and timing of many simulated presynaptic neurons. By analyzing the firing of neurons in response to these artificial inputs, we ask 1) How does functional connectivity inferred from spikes relate to simulated synaptic input? and 2) What are the limitations of connectivity inference? We find that individual current-based synaptic inputs are detectable over a broad range of amplitudes and conditions. Detectability depends on input amplitude and output firing rate, and excitatory inputs are detected more readily than inhibitory. Moreover, as we model increasing numbers of presynaptic inputs, we are able to estimate connection strengths more accurately and detect the presence of connections more quickly. These results illustrate the possibilities and outline the limits of inferring synaptic input from spikes.     

Insights into Coupled Folding and Binding Mechanisms from Kinetic Studies

Intrinsically disordered proteins (IDPs) are characterized by a lack of persistent structure. Since their identification more than a decade ago, many questions regarding their functional relevance and interaction mechanisms remain unanswered. Although most experiments have taken equilibrium and structural perspectives, fewer studies have investigated the kinetics of their interactions. Here we review and highlight the type of information that can be gained from kinetic studies. In particular, we show how kinetic studies of coupled folding and binding reactions, an important class of signaling event, are needed to determine mechanisms.     

Molecular Docking Simulations Provide Insights in the Substrate Binding Sites and Possible Substrates of the ABCC6 Transporter

The human ATP-binding cassette family C member 6 (ABCC6) gene encodes an ABC transporter protein (ABCC6), primarily expressed in liver and kidney. Mutations in the ABCC6 gene cause pseudoxanthoma elasticum (PXE), an autosomal recessive connective tissue disease characterized by ectopic mineralization of the elastic fibers. The pathophysiology underlying PXE is incompletely understood, which can at least partly be explained by the undetermined nature of the ABCC6 substrates as well as the unknown substrate recognition and binding sites. Several compounds, including anionic glutathione conjugates (N-ethylmaleimide; NEM-GS) and leukotriene C4 (LTC4) were shown to be modestly transported in vitro; conversely, vitamin K3 (VK3) was demonstrated not to be transported by ABCC6. To predict the possible substrate binding pockets of the ABCC6 transporter, we generated a 3D homology model of ABCC6 in both open and closed conformation, qualified for molecular docking and virtual screening approaches. By docking 10 reported in vitro substrates in our ABCC6 3D homology models, we were able to predict the substrate binding residues of ABCC6. Further, virtual screening of 4651 metabolites from the Human Serum Metabolome Database against our open conformation model disclosed possible substrates for ABCC6, which are mostly lipid and biliary secretion compounds, some of which are found to be involved in mineralization. Docking of these possible substrates in the closed conformation model also showed high affinity. Virtual screening expands this possibility to explore more compounds that can interact with ABCC6, and may aid in understanding the mechanisms leading to PXE.