A graph-based approach identifies dynamic H-bond communication networks in spike protein S of SARS-CoV-2.

Corona virus spike protein S is a large homo-trimeric protein anchored in the membrane of the virion particle. Protein S binds to angiotensin-converting-enzyme 2, ACE2, of the host cell, followed by proteolysis of the spike protein, drastic protein conformational change with exposure of the fusion peptide of the virus, and entry of the virion into the host cell. The structural elements that govern conformational plasticity of the spike protein are largely unknown. Here, we present a methodology that relies upon graph and centrality analyses, augmented by bioinformatics, to identify and characterize large H-bond clusters in protein structures. We apply this methodology to protein S ectodomain and find that, in the closed conformation, the three protomers of protein S bring the same contribution to an extensive central network of H-bonds, and contribute symmetrically to a relatively large H-bond cluster at the receptor binding domain, and to a cluster near a protease cleavage site. Markedly different H-bonding at these three clusters in open and pre-fusion conformations suggest dynamic H-bond clusters could facilitate structural plasticity and selection of a protein S protomer for binding to the host receptor, and proteolytic cleavage. From analyses of spike protein sequences we identify patches of histidine and carboxylate groups that could be involved in transient proton binding.

Using Graphs of Dynamic Hydrogen-Bond Networks To Dissect Conformational Coupling in a Protein Motor.

DExD/H-box proteins are soluble enzymes that couple binding and hydrolysis of adenosine triphosphate (ATP) with reactions involving RNA metabolism or bind and push newly synthesized proteins across bacterial cell membranes. Knowledge of the reaction mechanism of these enzymes could help the development of new therapeutics. In order to explore the mechanism of long-distance conformational coupling in SecA, the DEAD-box motor of the Sec protein secretion in bacteria, we implemented algorithms that provide simplified graph representations of the protein's dynamic hydrogen-bond networks. We find that mutations near the nucleotide-binding site or changes of the nucleotide-binding state of SecA associate with altered dynamics at the preprotein binding domain and identify extended networks of hydrogen bonds that connect the active site of SecA to the region where SecA binds newly synthesized secretory proteins. Water molecules participate in hydrogen-bonded water chains that bridge functional domains of SecA and could contribute to long-distance conformational coupling.

Dynamic Water Hydrogen-Bond Networks at the Interface of a Lipid Membrane Containing Palmitoyl-Oleoyl Phosphatidylglycerol.

Lipid membrane interfaces are complex environments that host essential cellular processes such as binding of proteins or drug molecules. A key open question is how water molecules at the interface of membranes with anionic lipids participate in protein binding. To address this question, we studied the dynamics of water hydrogen bonding at the interface of membranes composed of phosphatidylcholine and phosphatidylglycerol, and implemented an algorithm to identify hydrogen-bonded networks at the interface of a lipid membrane, and to characterize their dynamics and linear connections. We find that the membrane interface is characterized by a rich network of hydrogen-bonded water chains that bridge lipid headgroups, some of which form transient lipid clusters. Water-mediated bridges between with lipid phosphate groups are dynamic, with residence lifetimes on the order of picoseconds. These clusters of water/lipid headgroup hydrogen bonds could provide a platform for the binding of proteins or of drug molecules with cationic groups.

Understanding Conformational Dynamics of Complex Lipid Mixtures Relevant to Biology.

This is a perspective article entitled "Frontiers in computational biophysics: understanding conformational dynamics of complex lipid mixtures relevant to biology" which is following a CECAM meeting with the same name.

NanoCrystal: A Web-Based Crystallographic Tool for the Construction of Nanoparticles Based on Their Crystal Habit.

Modeling of nanoparticles is an essential first step to assess their capacities for different uses such as energy storage and drug delivery. However, creating an initial starting conformation for modeling and simulation is tedious because every crystalline material grows with a different crystal habit. In this application note, we describe NanoCrystal, a novel web-based crystallographic tool that creates nanoparticle models from any crystal structure guided by their preferred equilibrium shape under standard conditions according to the Wulff morphology (crystal habit). Users can upload a cif file, define the Miller indices and their corresponding minimum surface energies according to the Wulff construction of a particular crystal, and specify the size of the nanocrystal. As a result, the nanoparticle is constructed and visualized, and the coordinates of the atoms are output to the user. NanoCrystal can be accessed at http://nanocrystal.vi-seem.edu/ .

DIANA-TarBase v7.0: indexing more than half a million experimentally supported miRNA:mRNA interactions.

microRNAs (miRNAs) are short non-coding RNA species, which act as potent gene expression regulators. Accurate identification of miRNA targets is crucial to understanding their function. Currently, hundreds of thousands of miRNA:gene interactions have been experimentally identified. However, this wealth of information is fragmented and hidden in thousands of manuscripts and raw next-generation sequencing data sets. DIANA-TarBase was initially released in 2006 and it was the first database aiming to catalog published experimentally validated miRNA:gene interactions. DIANA-TarBase v7.0 (http://www.microrna.gr/tarbase) aims to provide for the first time hundreds of thousands of high-quality manually curated experimentally validated miRNA:gene interactions, enhanced with detailed meta-data. DIANA-TarBase v7.0 enables users to easily identify positive or negative experimental results, the utilized experimental methodology, experimental conditions including cell/tissue type and treatment. The new interface provides also advanced information ranging from the binding site location, as identified experimentally as well as in silico, to the primer sequences used for cloning experiments. More than half a million miRNA:gene interactions have been curated from published experiments on 356 different cell types from 24 species, corresponding to 9- to 250-fold more entries than any other relevant database. DIANA-TarBase v7.0 is freely available.

Graph-Based Analyses of Dynamic Water-Mediated Hydrogen-Bond Networks in Phosphatidylserine: Cholesterol Membranes.

Phosphatidylserine lipids are anionic molecules present in eukaryotic plasma membranes, where they have essential physiological roles. The altered distribution of phosphatidylserine in cells such as apoptotic cancer cells, which, unlike healthy cells, expose phosphatidylserine, is of direct interest for the development of biomarkers. We present here applications of a recently implemented Depth-First-Search graph algorithm to dissect the dynamics of transient water-mediated lipid clusters at the interface of a model bilayer composed of 1-palmytoyl-2-oleoyl-sn-glycero-2-phosphatidylserine (POPS) and cholesterol. Relative to a reference POPS bilayer without cholesterol, in the POPS:cholesterol bilayer there is a somewhat less frequent sampling of relatively complex and extended water-mediated hydrogen-bond networks of POPS headgroups. The analysis protocol used here is more generally applicable to other lipid:cholesterol bilayers.

Algorithm to catalogue topologies of dynamic lipid hydrogen-bond networks.

Lipid membrane interfaces host reactions essential for the functioning of cells. The hydrogen-bonding environment at the membrane interface is particularly important for binding of proteins, drug molecules, and ions. We present here the implementation and applications of a depth-first search algorithm that analyzes dynamic lipid interaction networks. Lipid hydrogen-bond networks sampled transiently during simulations of lipid bilayers are clustered according to main types of topologies that characterize three-dimensional arrangements of lipids connected to each other via short water bridges. We characterize the dynamics of hydrogen-bonded lipid clusters in simulations of model POPE and POPE:POPG membranes that are often used for bacterial membrane proteins, in a model of the Escherichia coli membrane with six different lipid types, and in POPS membranes. We find that all lipids sample dynamic hydrogen-bonded networks with linear, star, or circular arrangements of the lipid headgroups, and larger networks with combinations of these three types of topologies. Overall, linear lipid-water bridges tend to be short. Water-mediated lipid clusters in all membranes with PE lipids tend to be somewhat small, with about four lipids in all membranes studied here. POPS membranes allow circular arrangements of three POPS lipids to be sampled frequently, and complex arrangements of linear, star, and circular paths may also be sampled. These findings suggest a molecular picture of the membrane interface whereby lipid molecules transiently connect in clusters with somewhat small spatial extension.

Preproteins couple the intrinsic dynamics of SecA to its ATPase cycle to translocate via a catch and release mechanism.

Protein machines undergo conformational motions to interact with and manipulate polymeric substrates. The Sec translocase promiscuously recognizes, becomes activated, and secretes >500 non-folded preprotein clients across bacterial cytoplasmic membranes. Here, we reveal that the intrinsic dynamics of the translocase ATPase, SecA, and of preproteins combine to achieve translocation. SecA possesses an intrinsically dynamic preprotein clamp attached to an equally dynamic ATPase motor. Alternating motor conformations are finely controlled by the γ-phosphate of ATP, while ADP causes motor stalling, independently of clamp motions. Functional preproteins physically bridge these independent dynamics. Their signal peptides promote clamp closing; their mature domain overcomes the rate-limiting ADP release. While repeated ATP cycles shift the motor between unique states, multiple conformationally frustrated prongs in the clamp repeatedly "catch and release" trapped preprotein segments until translocation completion. This universal mechanism allows any preprotein to promiscuously recognize the translocase, usurp its intrinsic dynamics, and become secreted.

A nexus of intrinsic dynamics underlies translocase priming.

The cytoplasmic ATPase SecA and the membrane-embedded SecYEG channel assemble to form the Sec translocase. How this interaction primes and catalytically activates the translocase remains unclear. We show that priming exploits a nexus of intrinsic dynamics in SecA. Using atomistic simulations, smFRET, and HDX-MS, we reveal multiple dynamic islands that cross-talk with domain and quaternary motions. These dynamic elements are functionally important and conserved. Central to the nexus is a slender stem through which rotation of the preprotein clamp of SecA is biased by ATPase domain motions between open and closed clamping states. An H-bonded framework covering most of SecA enables multi-tier dynamics and conformational alterations with minimal energy input. As a result, cognate ligands select preexisting conformations and alter local dynamics to regulate catalytic activity and clamp motions. These events prime the translocase for high-affinity reception of non-folded preprotein clients. Dynamics nexuses are likely universal and essential in multi-liganded proteins.

Graphs of dynamic H-bond networks: from model proteins to protein complexes in cell signaling.

Proton transfer reactions are ubiquitous in biology, as they are involved in the functioning of numerous proteins. Studies of model proteins have revealed mechanisms by which proteins use hydrogen-bond networks for proton transfers, and couple proton transfers with protein and water dynamics. In this review we focus on graph-based analyses of dynamic hydrogen-bond networks at membrane interfaces, protein H-bond networks for allosteric conformational coupling and pH sensitivity, and challenges in extrapolating from knowledge acquired from studies of model membrane proteins to computational studies of macro-molecular protein complexes that are part of cell signaling networks directly relevant to the development of new therapeutics.

Coating of magnetic nanoparticles affects their interactions with model cell membranes.

BACKGROUND: The use of functionalized iron oxide nanoparticles of various chemical properties and architectures offers a new promising direction in theranostic applications. The increasing applications of nanoparticles in medicine require that these engineered nanomaterials will contact human cells without damaging essential tissues. Thus, efficient delivery must be achieved, while minimizing cytotoxicity during passage through cell membranes to reach intracellular target compartments. METHODS: Differential Scanning Calorimetry (DSC), molecular modeling, and atomistic Molecular Dynamics (MD) simulations were performed for two magnetite nanoparticles coated with polyvinyl alcohol (PVA) and polyarabic acid (ARA) in order to assess their interactions with model DPPC membranes. RESULTS: DSC experiments showed that both nanoparticles interact strongly with DPPC lipid head groups, albeit to a different degree, which was further confirmed and quantified by MD simulations. The two systems were simulated, and dynamical and structural properties were monitored. A bimodal diffusion was observed for both nanoparticles, representing the diffusion in the water phase and in the proximity of the lipid bilayer. Nanoparticles did not enter the bilayer, but caused ordering of the head groups and reduced the area per lipid compared to the pure bilayer, with MAG-PVA interacting more strongly and being closer to the lipid bilayer. CONCLUSIONS: Results of DSC experiments and MD simulations were in excellent agreement. Our findings demonstrate that the external coating is a key factor that affects nanoparticle-membrane interactions. Magnetite nanoparticles coated with PVA and ARA did not destabilize the model membrane and can be considered promising platforms for biomedical applications. GENERAL SIGNIFICANCE: Understanding the physico-chemical interactions of different nanoparticle coatings in contact with model cell membranes is the first step for assessing toxic response and could lead to predictive models for estimating toxicity. DSC in combination with MD simulations is an effective strategy to assess physico-chemical interactions of coated nanoparticles with lipid bilayers.

Bridge: A Graph-Based Algorithm to Analyze Dynamic H-Bond Networks in Membrane Proteins.

Membrane proteins that function as transporters or receptors must communicate with both sides of the lipid bilayer in which they sit. This long distance communication enables transporters to move protons or other ions and small molecules across the bilayer and receptors to transmit an external signal to the cell. Hydrogen bonds, hydrogen-bond networks, and lipid-protein interactions are essential for the motions and functioning of the membrane protein and, consequently, of outmost interest to structural biology and numerical simulations. We present here Bridge, an algorithm tailored for efficient analyses of hydrogen-bond networks in membrane transporter and receptor proteins. For channelrhodopsin, a membrane protein whose functioning involves proton-transfer reactions, Bridge identifies extensive networks of protein-water hydrogen bonds and an unanticipated network that can bridge transiently two proton donors across a distance of ∼20 Å. Graphs of the protein hydrogen bonds reveal rapid propagation of structural changes within hydrogen-bond networks of mutant transporters and identify protein groups potentially important for the proton transfer activity. The algorithm is made available as a plugin for PyMol.

Dynamic hydrogen-bond networks in bacterial protein secretion.

The Sec protein secretion machinery includes proteins whose reaction coordinates involve large-scale conformational changes. Dynamic hydrogen-bond networks can provide structural plasticity required by the SecA protein motor and the SecY protein translocon. Here we discuss hydrogen-bond networks of these two Sec proteins from crystal structures and molecular simulations, and the usefulness of molecular simulations approaches to studying dynamic hydrogen bonds and their role in bacterial protein secretion.

Magnetic nanoparticles coated with polyarabic acid demonstrate enhanced drug delivery and imaging properties for cancer theranostic applications.

Therapeutic targeting of tumor cells with drug nanocarriers relies upon successful interaction with membranes and efficient cell internalization. A further consideration is that engineered nanomaterials should not damage healthy tissues upon contact. A critical factor in this process is the external coating of drug delivery nanodevices. Using in silico, in vitro and in vivo studies, we show for the first time that magnetic nanoparticles coated with polyarabic acid have superior imaging, therapeutic, and biocompatibility properties. We demonstrate that polyarabic acid coating allows for efficient penetration of cell membranes and internalization into breast cancer cells. Polyarabic acid also allows reversible loading of the chemotherapeutic drug Doxorubicin, which upon release suppresses tumor growth in vivo in a mouse model of breast cancer. Furthermore, these nanomaterials provide in vivo contrasting properties, which directly compare with commercial gadolinium-based contrasting agents. Finally, we report excellent biocompatibility, as these nanomaterial cause minimal, if any cytotoxicity in vitro and in vivo. We thus propose that magnetic nanodevices coated with polyarabic acid offer a new avenue for theranostics efforts as efficient drug carriers, while providing excellent contrasting properties due to their ferrous magnetic core, which can help the future design of nanomaterials for cancer imaging and therapy.