Unlocking the Power of Human Ferritin: Enhanced Drug Delivery of Aurothiomalate in A2780 Ovarian Cancer Cells.

Aurothiomalate (AuTM) is an FDA-approved antiarthritic gold drug with unique anticancer properties. To enhance its anticancer activity, we prepared a bioconjugate with human apoferritin (HuHf) by attaching some AuTM moieties to surface protein residues. The reaction of apoferritin with excess AuTM yielded a single adduct, that was characterized by ESI MS and ICP-OES analysis, using three mutant ferritins and trypsinization experiments. The adduct contains ~3 gold atoms per ferritin subunit, arranged in a small cluster bound to Cys90 and Cys102. MD simulations provide a plausible structural model for the cluster. The adduct was evaluated for its pharmacological properties and was found to be significantly more cytotoxic than free AuTM against A2780 cancer cells mainly due to higher gold uptake. NMR-metabolomics showed that AuTM bound to HuHf and free AuTM induced qualitatively similar changes in treated cancer cells, indicating that the effects on cell metabolism are approximately the same, in agreement with independent biochemical experiments. In conclusion, we have demonstrated here that a molecularly precise bioconjugate formed between AuTM and HuHf exhibits anticancer properties far superior to the free drug, while retaining its key mechanistic features. Evidence is provided that human ferritin can serve as an excellent carrier for this metallodrug.

A Comparison of Bonded and Nonbonded Zinc(II) Force Fields with NMR Data.

Classical molecular dynamics (MD) simulations are widely used to inspect the behavior of zinc(II)-proteins at the atomic level, hence the need to properly model the zinc(II) ion and the interaction with its ligands. Different approaches have been developed to represent zinc(II) sites, with the bonded and nonbonded models being the most used. In the present work, we tested the well-known zinc AMBER force field (ZAFF) and a recently developed nonbonded force field (NBFF) to assess how accurately they reproduce the dynamic behavior of zinc(II)-proteins. For this, we selected as benchmark six zinc-fingers. This superfamily is extremely heterogenous in terms of architecture, binding mode, function, and reactivity. From repeated MD simulations, we computed the order parameter (S2) of all backbone N-H bond vectors in each system. These data were superimposed to heteronuclear Overhauser effect measurements taken by NMR spectroscopy. This provides a quantitative estimate of the accuracy of the FFs in reproducing protein dynamics, leveraging the information about the protein backbone mobility contained in the NMR data. The correlation between the MD-computed S2 and the experimental data indicated that both tested FFs reproduce well the dynamic behavior of zinc(II)-proteins, with comparable accuracy. Thus, along with ZAFF, NBFF represents a useful tool to simulate metalloproteins with the advantage of being extensible to diverse systems such as those bearing dinuclear metal sites.

Molecular Structure of Cu(II)-Bound Amyloid-ß Monomer Implicated in Inhibition of Peptide Self-Assembly in Alzheimer's Disease.

Metal ions, such as copper and zinc ions, have been shown to strongly modulate the self-assembly of the amyloid-ß (Aß) peptide into insoluble fibrils, and elevated concentrations of metal ions have been found in amyloid plaques of Alzheimer's patients. Among the physiological transition metal ions, Cu(II) ions play an outstanding role since they can trigger production of neurotoxic reactive oxygen species. In contrast, structural insights into Cu(II) coordination of Aß have been challenging due to the paramagnetic nature of Cu(II). Here, we employed specifically tailored paramagnetic NMR experiments to determine NMR structures of Cu(II) bound to monomeric Aß. We found that monomeric Aß binds Cu(II) in the N-terminus and combined with molecular dynamics simulations, we could identify two prevalent coordination modes of Cu(II). For these, we report here the NMR structures of the Cu(II)-bound Aß complex, exhibiting heavy backbone RMSD values of 1.9 and 2.1 Å, respectively. Further, applying aggregation kinetics assays, we identified the specific effect of Cu(II) binding on the Aß nucleation process. Our results show that Cu(II) efficiently retards Aß fibrillization by predominately reducing the rate of fibril-end elongation at substoichiometric ratios. A detailed kinetic analysis suggests that this specific effect results in enhanced Aß oligomer generation promoted by Cu(II). These results can quantitatively be understood by Cu(II) interaction with the Aß monomer, forming an aggregation inert complex. In fact, this mechanism is strikingly similar to other transition metal ions, suggesting a common mechanism of action of retarding Aß self-assembly, where the metal ion binding to monomeric Aß is a key determinant.

Learning to Identify Physiological and Adventitious Metal-Binding Sites in the Three-Dimensional Structures of Proteins by Following the Hints of a Deep Neural Network.

Thirty-eight percent of protein structures in the Protein Data Bank contain at least one metal ion. However, not all these metal sites are biologically relevant. Cations present as impurities during sample preparation or in the crystallization buffer can cause the formation of protein-metal complexes that do not exist in vivo. We implemented a deep learning approach to build a classifier able to distinguish between physiological and adventitious zinc-binding sites in the 3D structures of metalloproteins. We trained the classifier using manually annotated sites extracted from the MetalPDB database. Using a 10-fold cross validation procedure, the classifier achieved an accuracy of about 90%. The same neural classifier could predict the physiological relevance of non-heme mononuclear iron sites with an accuracy of nearly 80%, suggesting that the rules learned on zinc sites have general relevance. By quantifying the relative importance of the features describing the input zinc sites from the network perspective and by analyzing the characteristics of the MetalPDB datasets, we inferred some common principles. Physiological sites present a low solvent accessibility of the aminoacids forming coordination bonds with the metal ion (the metal ligands), a relatively large number of residues in the metal environment (≥20), and a distinct pattern of conservation of Cys and His residues in the site. Adventitious sites, on the other hand, tend to have a low number of donor atoms from the polypeptide chain (often one or two). These observations support the evaluation of the physiological relevance of novel metal-binding sites in protein structures.

Automated Determination of Nuclear Magnetic Resonance Chemical Shift Perturbations in Ligand Screening Experiments: The PICASSO Web Server.

Nuclear magnetic resonance (NMR) is an effective, commonly used experimental approach to screen small organic molecules against a protein target. A very popular method consists of monitoring the changes of the NMR chemical shifts of the protein nuclei upon addition of the small molecule to the free protein. Multidimensional NMR experiments allow the interacting residues to be mapped along the protein sequence. A significant amount of human effort goes into manually tracking the chemical shift variations, especially when many signals exhibit chemical shift changes and when many ligands are tested. Some computational approaches to automate the procedure are available, but none of them as a web server. Furthermore, some methods require the adoption of a fairly specific experimental setup, such as recording a series of spectra at increasing small molecule:protein ratios. In this work, we developed a tool requesting a minimal amount of experimental data from the user, implemented it as an open-source program, and made it available as a web application. Our tool compares two spectra, one of the free protein and one of the small molecule:protein mixture, based on the corresponding peak lists. The performance of the tool in terms of correct identification of the protein-binding regions has been evaluated on different protein targets, using experimental data from interaction studies already available in the literature. For a total of 16 systems, our tool achieved between 79% and 100% correct assignments, properly identifying the protein regions involved in the interaction.

Structural Biology in the Clouds: The WeNMR-EOSC Ecosystem.

Structural biology aims at characterizing the structural and dynamic properties of biological macromolecules at atomic details. Gaining insight into three dimensional structures of biomolecules and their interactions is critical for understanding the vast majority of cellular processes, with direct applications in health and food sciences. Since 2010, the WeNMR project (www.wenmr.eu) has implemented numerous web-based services to facilitate the use of advanced computational tools by researchers in the field, using the high throughput computing infrastructure provided by EGI. These services have been further developed in subsequent initiatives under H2020 projects and are now operating as Thematic Services in the European Open Science Cloud portal (www.eosc-portal.eu), sending >12 millions of jobs and using around 4,000 CPU-years per year. Here we review 10 years of successful e-infrastructure solutions serving a large worldwide community of over 23,000 users to date, providing them with user-friendly, web-based solutions that run complex workflows in structural biology. The current set of active WeNMR portals are described, together with the complex backend machinery that allows distributed computing resources to be harvested efficiently.

Insights into the Dynamics of the Human Zinc Transporter ZnT8 by MD Simulations.

ZnT8 is a human zinc(II) transporter expressed at the membrane of secretory granules where it contributes to insulin storage importing zinc ions from the cytosol. In the human population, the two most common ZnT8 variants carry an arginine (R325) or a tryptophan (W325) in position 325. The former variant has the most efficient kinetics in zinc transport and has been correlated to a higher risk of developing insulin resistance. On the contrary, the W325 variant is less active and protects against type-2-diabetes. Here, we used molecular dynamics (MD) simulations to investigate the main differences between the R325 and W325 variants in the interaction with zinc(II) ions. Our simulations suggested that the position of the metal ion within the transport site was not the same for the two variants, underlying a different rearrangement of the transmembrane (TM) helices in the channel. The W325 variant featured a peculiar zinc environment not detected in the experimental structures. With respect to conformational dynamics, we observed that the R325 variant was significantly more flexible than W325, with the main role played by the transmembrane domain (TMD) and the C-terminal domain (CTD). This dynamics affected the packing of the TM helices and thus the channel accessibility from the cytosol. The dimer interface that keeps the two TM channels in contact became looser in both variants upon zinc binding to the transport site, suggesting that this may be an important step toward the switch from the inward- to the outward-facing state of the protein.

A protocol to automatically calculate homo-oligomeric protein structures through the integration of evolutionary constraints and NMR ambiguous contacts.

Protein assemblies are involved in many important biological processes. Solid-state NMR (SSNMR) spectroscopy is a technique suitable for the structural characterization of samples with high molecular weight and thus can be applied to such assemblies. A significant bottleneck in terms of both effort and time required is the manual identification of unambiguous intermolecular contacts. This is particularly challenging for homo-oligomeric complexes, where simple uniform labeling may not be effective. We tackled this challenge by exploiting coevolution analysis to extract information on homo-oligomeric interfaces from NMR-derived ambiguous contacts. After removing the evolutionary couplings (ECs) that are already satisfied by the 3D structure of the monomer, the predicted ECs are matched with the automatically generated list of experimental contacts. This approach provides a selection of potential interface residues that is used directly in monomer-monomer docking calculations. We validated the protocol on tetrameric L-asparaginase II and dimeric Sod1.

Conformational characterization of full-length X-chromosome-linked inhibitor of apoptosis protein (XIAP) through an integrated approach.

The X-chromosome-linked inhibitor of apoptosis protein (XIAP) is a multidomain protein whose main function is to block apoptosis by caspase inhibition. XIAP is also involved in other signalling pathways, including NF-κB activation and copper homeostasis. XIAP is overexpressed in tumours, potentiating cell survival and resistance to chemotherapeutics, and has therefore become an important target for the treatment of malignancy. Despite the fact that the structure of each single domain is known, the conformation of the full-length protein has never been determined. Here, the first structural model of the full-length XIAP dimer, determined by an integrated approach using nuclear magnetic resonance, small-angle X-ray scattering and electron paramagnetic resonance data, is presented. It is shown that XIAP adopts a compact and relatively rigid conformation, implying that the spatial arrangement of its domains must be taken into account when studying the interactions with its physiological partners and in developing effective inhibitors.

An atomistic view of the YiiP structural changes upon zinc(II) binding.

BACKGROUND: YiiP is a bacterial zinc-for-proton antiporter belonging to the cation diffusion facilitator family. The zinc(II) ions are transported across the cell membrane, from the cytosol to the extracellular space. METHODS: We performed atomistic molecular dynamics simulations of the YiiP dimer with zinc(II) ions in solution to elucidate how the metal ions interact with the protein while moving from the cytosol to the transport site. RESULTS: We observed that of the two cavities of the dimer, only one was accessible from the cytosol during transport. Zinc(II) binding to D49 of the transport site triggered a rearrangement of the transmembrane domain that closed the accessible cavity. Finally, we analyzed the free-energy profiles of metal transit in the channel and observed the existence of a high barrier preventing release from the transport site. CONCLUSIONS: The observed dynamics is consistent with the dimer-dimer interface forming a stable scaffold against which the rest of the trans-membrane rearranges. GENERAL SIGNIFICANCE: Zinc(II) transporters are present in all kingdoms of life. The present study highlights structural features that might be of general relevance.

West-Life: A Virtual Research Environment for structural biology.

The West-Life project (https://about.west-life.eu/) is a Horizon 2020 project funded by the European Commission to provide data processing and data management services for the international community of structural biologists, and in particular to support integrative experimental approaches within the field of structural biology. It has developed enhancements to existing web services for structure solution and analysis, created new pipelines to link these services into more complex higher-level workflows, and added new data management facilities. Through this work it has striven to make the benefits of European e-Infrastructures more accessible to life-science researchers in general and structural biologists in particular.

Investigation of the Iron(II) Release Mechanism of Human H-Ferritin as a Function of pH.

We investigated the kinetics of the release of iron(II) ions from the internal cavity of human H-ferritin as a function of pH. Extensive molecular dynamics simulations of the entire 24-mer ferritin provided atomic-level information on the release mechanism. Double protonation of His residues at pH 4 facilitates the removal of the iron ligands within the C3 channel through the formation of salt bridges, resulting in a significantly lower release energy barrier than pH 9.

Structural insights into the molecular function of human [2Fe-2S] BOLA1-GRX5 and [2Fe-2S] BOLA3-GRX5 complexes.

Members of the monothiol glutaredoxin family and members of the BolA-like protein family have recently emerged as specific interacting partners involved in iron-sulfur protein maturation and redox regulation pathways. It is known that human mitochondrial BOLA1 and BOLA3 form [2Fe-2S] cluster-bridged dimeric heterocomplexes with the monothiol glutaredoxin GRX5. The structure and cluster coordination of the two [2Fe-2S] heterocomplexes as well as their molecular function are, however, not defined yet. Experimentally-driven structural models of the two [2Fe-2S] cluster-bridged dimeric heterocomplexes, the relative stability of the two complexes and the redox properties of the [2Fe-2S] cluster bound to these complexes are here presented on the basis of UV/vis, CD, EPR and NMR spectroscopies and computational protein-protein docking. While the BOLA1-GRX5 complex coordinates a reduced, Rieske-type [2Fe-2S]1+ cluster, an oxidized, ferredoxin-like [2Fe-2S]2+ cluster is present in the BOLA3-GRX5 complex. The [2Fe-2S] BOLA1-GRX5 complex is preferentially formed over the [2Fe-2S] BOLA3-GRX5 complex, as a result of a higher cluster binding affinity. All these observed differences provide the first indications discriminating the molecular function of the two [2Fe-2S] heterocomplexes.

A protocol for the refinement of NMR structures using simultaneously pseudocontact shift restraints from multiple lanthanide ions.

The binding of paramagnetic metal ions to proteins produces a number of different effects on the NMR spectra of the system. In particular, when the magnetic susceptibility of the metal ion is anisotropic, pseudocontact shifts (PCSs) arise and can be easily measured. They constitute very useful restraints for the solution structure determination of metal-binding proteins. In this context, there has been great interest in the use of lanthanide(III) ions to induce PCSs in diamagnetic proteins, e.g. through the replacement native calcium(II) ions. By preparing multiple samples in each of which a different ion of the lanthanide series is introduced, it is possible to obtain multiple independent PCS datasets that can be used synergistically to generate protein structure ensembles (typically called bundles). For typical NMR-based determination of protein structure, it is necessary to perform an energetic refinement of such initial bundles to obtain final structures whose geometric quality is suitable for deposition in the PDB. This can be conveniently done by using restrained molecular dynamics simulations (rMD) in explicit solvent. However, there are no available protocols for rMD using multiple PCS datasets as part of the restraints. In this work, we extended the PCS module of the AMBER MD package to handle multiple datasets and tuned a previously developed protocol for NMR structure refinement to achieve consistent convergence with PCS restraints. Test calculations with real experimental data show that this new implementation delivers the expected improvement of protein geometry, resulting in final structures that are of suitable quality for deposition. Furthermore, we observe that also initial structures generated only with traditional restraints can be successfully refined using traditional and PCS restraints simultaneously.

Scale Space Graph Representation and Kernel Matching for Non Rigid and Textured 3D Shape Retrieval.

In this paper we introduce a novel framework for 3D object retrieval that relies on tree-based shape representations (TreeSha) derived from the analysis of the scale-space of the Auto Diffusion Function (ADF) and on specialized graph kernels designed for their comparison. By coupling maxima of the Auto Diffusion Function with the related basins of attraction, we can link the information at different scales encoding spatial relationships in a graph description that is isometry invariant and can easily incorporate texture and additional geometrical information as node and edge features. Using custom graph kernels it is then possible to estimate shape dissimilarities adapted to different specific tasks and on different categories of models, making the procedure a powerful and flexible tool for shape recognition and retrieval. Experimental results demonstrate that the method can provide retrieval scores similar or better than state-of-the-art on textured and non textured shape retrieval benchmarks and give interesting insights on effectiveness of different shape descriptors and graph kernels.

Robust automatic measurement of 3D scanned models for the human body fat estimation.

In this paper, we present an automatic tool for estimating geometrical parameters from 3-D human scans independent on pose and robustly against the topological noise. It is based on an automatic segmentation of body parts exploiting curve skeleton processing and ad hoc heuristics able to remove problems due to different acquisition poses and body types. The software is able to locate body trunk and limbs, detect their directions, and compute parameters like volumes, areas, girths, and lengths. Experimental results demonstrate that measurements provided by our system on 3-D body scans of normal and overweight subjects acquired in different poses are highly correlated with the body fat estimates obtained on the same subjects with dual-energy X-rays absorptiometry (DXA) scanning. In particular, maximal lengths and girths, not requiring precise localization of anatomical landmarks, demonstrate a good correlation (up to 96%) with the body fat and trunk fat. Regression models based on our automatic measurements can be used to predict body fat values reasonably well.

G-triplex structure and formation propensity.

The occurrence of a G-triplex folding intermediate of thrombin binding aptamer (TBA) has been recently predicted by metadynamics calculations, and experimentally supported by Nuclear Magnetic Resonance (NMR), Circular Dichroism (CD) and Differential Scanning Calorimetry (DSC) data collected on a 3' end TBA-truncated 11-mer oligonucleotide (11-mer-3'-t-TBA). Here we present the solution structure of 11-mer-3'-t-TBA in the presence of potassium ions. This structure is the first experimental example of a G-triplex folding, where a network of Hoogsteen-like hydrogen bonds stabilizes six guanines to form two G:G:G triad planes. The G-triplex folding of 11-mer-3'-t-TBA is stabilized by the potassium ion and destabilized by increasing the temperature. The superimposition of the experimental structure with that predicted by metadynamics shows a great similarity, with only significant differences involving two loops. These new structural data show that 11-mer-3'-t-TBA assumes a G-triplex DNA conformation as its stable form, reinforcing the idea that G-triplex folding intermediates may occur in vivo in human guanine-rich sequences. NMR and CD screening of eight different constructs obtained by removing from one to four bases at either the 3' and the 5' ends show that only the 11-mer-3'-t-TBA yields a relatively stable G-triplex.

Long-range correlated dynamics in intrinsically disordered proteins.

Intrinsically disordered proteins (IDPs) are involved in a wide variety of physiological and pathological processes and are best described by ensembles of rapidly interconverting conformers. Using fast field cycling relaxation measurements we here show that the IDP α-synuclein as well as a variety of other IDPs undergoes slow reorientations at time scales comparable to folded proteins. The slow motions are not perturbed by mutations in α-synuclein, which are related to genetic forms of Parkinson's disease, and do not depend on secondary and tertiary structural propensities. Ensemble-based hydrodynamic calculations suggest that the time scale of the underlying correlated motion is largely determined by hydrodynamic coupling between locally rigid segments. Our study indicates that long-range correlated dynamics are an intrinsic property of IDPs and offers a general physical mechanism of correlated motions in highly flexible biomolecular systems.

Accurate and reliable segmentation of the optic disc in digital fundus images.

We describe a complete pipeline for the detection and accurate automatic segmentation of the optic disc in digital fundus images. This procedure provides separation of vascular information and accurate inpainting of vessel-removed images, symmetry-based optic disc localization, and fitting of incrementally complex contour models at increasing resolutions using information related to inpainted images and vessel masks. Validation experiments, performed on a large dataset of images of healthy and pathological eyes, annotated by experts and partially graded with a quality label, demonstrate the good performances of the proposed approach. The method is able to detect the optic disc and trace its contours better than the other systems presented in the literature and tested on the same data. The average error in the obtained contour masks is reasonably close to the interoperator errors and suitable for practical applications. The optic disc segmentation pipeline is currently integrated in a complete software suite for the semiautomatic quantification of retinal vessel properties from fundus camera images (VAMPIRE).

Cytochrome c and superoxide: a reply.

In his comments, W.H. Koppenol criticizes our article with respect to our conclusions and procedures. In this answer, we respond in detail to his objections, demonstrating that the approaches used are commonly accepted in the literature and that he makes a number of assumptions regarding our proposed mechanism that are not justified. Our study is thus a contribution to the ongoing investigation of the behavior of cytochrome c.