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We apply graph-based approaches to identify H-bond clusters in protein complexes. Three conformations of spike protein S have distinct H-bond clusters at key sites. Hydrogen-bond clusters could govern structural plasticity of spike protein S. Protein S binds to ACE2 receptor via H-bond clusters extending deep across interface., 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., PSI COVID19 Emergency Science Fund, Spanish Ministry of Science, Innovation and Universities RTI2018-098983-B-I00, Excellence Initiative of the German Federal and State Governments via the Freie Universitat Berlin, German Research Foundation (DFG) SFB 1078

Corona virus spike protein S is a large homo-trimeric protein embedded 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, has a relatively large H-bond cluster at the receptor binding domain, and 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.

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.

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. Fil: Friedman, Ran. Linnæus University; Argentina Fil: Khalid, Syma. University of Southampton; Reino Unido Fil: Aponte Santamaría, Camilo. Ruprecht-Karls-Universität Heidelberg; Alemania. Universidad de los Andes; Colombia Fil: Arutyunova, Elena. University of Alberta; Canadá Fil: Becker, Marlon. Westfälische Wilhelms Universität; Alemania Fil: Boyd, Kevin J.. University of Connecticut; Estados Unidos Fil: Christensen, Mikkel. University Aarhus; Dinamarca Fil: Coimbra, João T. S.. Universidad de Porto; Portugal Fil: Concilio, Simona. Universita di Salerno; Italia Fil: Daday, Csaba. Heidelberg Institute for Theoretical Studies; Alemania Fil: Eerden, Floris J. van. University of Groningen; Países Bajos Fil: Fernandes, Pedro A.. Universidad de Porto; Portugal Fil: Gräter, Frauke. Heidelberg University; Alemania. Heidelberg Institute for Theoretical Studies; Alemania Fil: Hakobyan, Davit. Westfälische Wilhelms Universität; Alemania Fil: Heuer, Andreas. Westfälische Wilhelms Universität; Alemania Fil: Karathanou, Konstantina. Freie Universität Berlin; Alemania Fil: Keller, Fabian. Westfälische Wilhelms Universität; Alemania Fil: Lemieux, M. Joanne. University of Alberta; Canadá Fil: Marrink, Siewert J.. University of Groningen; Países Bajos Fil: May, Eric R.. University of Connecticut; Estados Unidos Fil: Mazumdar, Antara. University of Groningen; Países Bajos Fil: Naftalin, Richard. Colegio Universitario de Londres; Reino Unido Fil: Pickholz, Mónica Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina Fil: Piotto, Stefano. Universita di Salerno; Italia Fil: Pohl, Peter. Johannes Kepler University; Austria Fil: Quinn, Peter. Colegio Universitario de Londres; Reino Unido Fil: Ramos, Maria J.. Universidad de Porto; Portugal Fil: Schiøtt, Birgit. University Aarhus; Dinamarca Fil: Sengupta, Durba. National Chemical Laboratory India; India Fil: Sessa, Lucia. Universita di Salerno; Italia Fil: Vanni, Stefano. University Of Fribourg; Fil: Zeppelin, Talia. University Aarhus; Dinamarca Fil: Zoni, Valeria. University of Fribourg; Suiza Fil: Bondar, Ana-Nicoleta. Freie Universität Berlin; Alemania Fil: Domene, Carmen. University of Oxford; Reino Unido. University of Bath; Reino Unido

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.

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.

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 A. 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.

SummaryThe cytoplasmic ATPase SecA and the membrane-embedded SecYEG channel assemble to form the functional Sec translocase. How this interaction primes and catalytically activates the translocase remains unclear. We now show that priming exploits a sophisticated nexus of intrinsic dynamics in SecA. Using atomistic simulations, single molecule FRET and hydrogen/deuterium exchange mass spectrometry we reveal multiple distributed dynamic islands that cross-talk with domain and quaternary motions. These dynamic elements are highly conserved and essential for function. Central to the nexus is a slender Stem through which, motions in the helicase ATPase domain of SecA biases how the preprotein binding domain rotates between open-closed clamping states. Multi-tier dynamics are enabled by an H-bonded framework covering most of the SecA structure and allowing conformational alterations with minimal energy inputs. As a result, dimerization, the channel and nucleotides select pre-existing conformations, and alter local dynamics to restrict or promote catalytic activity and clamp motions. These events prime the translocase for high affinity reception of non-folded preprotein clients. Such dynamics nexuses are likely universal and essential in multi-liganded protein machines.

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.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.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.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.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.

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.

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.