Atomic Force Microscopy beyond Topography: Chemical Sensing of 2D Material Surfaces through Adhesion Measurements.

Developing new functionalities of two-dimensional materials (2Dms) can be achieved by their chemical modification with a broad spectrum of molecules. This functionalization is commonly studied by using spectroscopies such as Raman, IR, or XPS, but the detection limit is a common problem. In addition, these methods lack detailed spatial resolution and cannot provide information about the homogeneity of the coating. Atomic force microscopy (AFM), on the other hand, allows the study of 2Dms on the nanoscale with excellent lateral resolution. AFM has been extensively used for topographic analysis; however, it is also a powerful tool for evaluating other properties far beyond topography such as mechanical ones. Therefore, herein, we show how AFM adhesion mapping of transition metal chalcogenide 2Dms (i.e., MnPS3 and MoS2) permits a close inspection of the surface chemical properties. Moreover, the analysis of adhesion as relative values allows a simple and robust strategy to distinguish between bare and functionalized layers and significantly improves the reproducibility between measurements. Remarkably, it is also confirmed by statistical analysis that adhesion values do not depend on the thickness of the layers, proving that they are related only to the most superficial part of the materials. In addition, we have implemented an unsupervised classification method using k-means clustering, an artificial intelligence-based algorithm, to automatically classify samples based on adhesion values. These results demonstrate the potential of simple adhesion AFM measurements to inspect the chemical nature of 2Dms and may have implications for the broad scientific community working in the field.

A binary interaction map between turnip mosaic virus and Arabidopsis thaliana proteomes.

Viruses are obligate intracellular parasites that have co-evolved with their hosts to establish an intricate network of protein-protein interactions. Here, we followed a high-throughput yeast two-hybrid screening to identify 378 novel protein-protein interactions between turnip mosaic virus (TuMV) and its natural host Arabidopsis thaliana. We identified the RNA-dependent RNA polymerase NIb as the viral protein with the largest number of contacts, including key salicylic acid-dependent transcription regulators. We verified a subset of 25 interactions in planta by bimolecular fluorescence complementation assays. We then constructed and analyzed a network comprising 399 TuMV-A. thaliana interactions together with intravirus and intrahost connections. In particular, we found that the host proteins targeted by TuMV are enriched in different aspects of plant responses to infections, are more connected and have an increased capacity to spread information throughout the cell proteome, display higher expression levels, and have been subject to stronger purifying selection than expected by chance. The proviral or antiviral role of ten host proteins was validated by characterizing the infection dynamics in the corresponding mutant plants, supporting a proviral role for the transcriptional regulator TGA1. Comparison with similar studies with animal viruses, highlights shared fundamental features in their mode of action.

Data-driven design of molecular nanomagnets.

Three decades of research in molecular nanomagnets have raised their magnetic memories from liquid helium to liquid nitrogen temperature thanks to a wise choice of the magnetic ion and coordination environment. Still, serendipity and chemical intuition played a main role. In order to establish a powerful framework for statistically driven chemical design, here we collected chemical and physical data for lanthanide-based nanomagnets, catalogued over 1400 published experiments, developed an interactive dashboard (SIMDAVIS) to visualise the dataset, and applied inferential statistical analysis. Our analysis shows that the Arrhenius energy barrier correlates unexpectedly well with the magnetic memory. Furthermore, as both Orbach and Raman processes can be affected by vibronic coupling, chemical design of the coordination scheme may be used to reduce the relaxation rates. Indeed, only bis-phthalocyaninato sandwiches and metallocenes, with rigid ligands, consistently present magnetic memory up to high temperature. Analysing magnetostructural correlations, we offer promising strategies for improvement, in particular for the preparation of pentagonal bipyramids, where even softer complexes are protected against molecular vibrations.

pyDockDNA: A new web server for energy-based protein-DNA docking and scoring.

Proteins and nucleic acids are essential biological macromolecules for cell life. Indeed, interactions between proteins and DNA regulate many biological processes such as protein synthesis, signal transduction, DNA storage, or DNA replication and repair. Despite their importance, less than 4% of total structures deposited in the Protein Data Bank (PDB) correspond to protein-DNA complexes, and very few computational methods are available to model their structure. We present here the pyDockDNA web server, which can successfully model a protein-DNA complex with a reasonable predictive success rate (as benchmarked on a standard dataset of protein-DNA complex structures, where DNA is in B-DNA conformation). The server implements the pyDockDNA program, as a module of pyDock suite, thus including third-party programs, modules, and previously developed tools, as well as new modules and parameters to handle the DNA properly. The user is asked to enter Protein Data Bank files for protein and DNA input structures (or suitable models) and select the chains to be docked. The server calculations are mainly divided into three steps: sampling by FTDOCK, scoring with new energy-based parameters and the possibility of applying external restraints. The user can select different options for these steps. The final output screen shows a 3D representation of the top 10 models and a table sorting the model according to the scoring function selected previously. All these output files can be downloaded, including the top 100 models predicted by pyDockDNA. The server can be freely accessed for academic use (https://model3dbio.csic.es/pydockdna).

Molecular signatures of silencing suppression degeneracy from a complex RNA virus.

As genomic architectures become more complex, they begin to accumulate degenerate and redundant elements. However, analyses of the molecular mechanisms underlying these genetic architecture features remain scarce, especially in compact but sufficiently complex genomes. In the present study, we followed a proteomic approach together with a computational network analysis to reveal molecular signatures of protein function degeneracy from a plant virus (as virus-host protein-protein interactions). We employed affinity purification coupled to mass spectrometry to detect several host factors interacting with two proteins of Citrus tristeza virus (p20 and p25) that are known to function as RNA silencing suppressors, using an experimental system of transient expression in a model plant. The study was expanded by considering two different isolates of the virus, and some key interactions were confirmed by bimolecular fluorescence complementation assays. We found that p20 and p25 target a common set of plant proteins including chloroplastic proteins and translation factors. Moreover, we noted that even specific targets of each viral protein overlap in function. Notably, we identified argonaute proteins (key players in RNA silencing) as reliable targets of p20. Furthermore, we found that these viral proteins preferentially do not target hubs in the host protein interactome, but elements that can transfer information by bridging different parts of the interactome. Overall, our results demonstrate that two distinct proteins encoded in the same viral genome that overlap in function also overlap in their interactions with the cell proteome, thereby highlighting an overlooked connection from a degenerate viral system.

Towards peptide-based tunable multistate memristive materials.

Development of new memristive hardware is a technological requirement towards widespread neuromorphic computing. Molecular spintronics seems to be a fertile field for the design and preparation of this hardware. Within molecular spintronics, recent results on metallopeptides demonstrating the interaction between paramagnetic ions and the chirality induced spin selectivity effect hold particular promise for developing fast (ns-µs) operation times. [R. Torres-Cavanillas et al., J. Am. Chem. Soc., 2020, DOI: 10.1021/jacs.0c07531]. Among the challenges in the field, a major highlight is the difficulty in modelling the spin dynamics in these complex systems, but at the same time the use of inexpensive methods has already allowed progress in that direction. Finally, we discuss the unique potential of biomolecules for the design of multistate memristors with a controlled- and indeed, programmable-nanostructure, allowing going beyond anything that is conceivable by employing conventional coordination chemistry.

Reinforced Room-Temperature Spin Filtering in Chiral Paramagnetic Metallopeptides.

Chirality-induced spin selectivity (CISS), whereby helical molecules polarize the spin of electrical current, is an intriguing effect with potential applications in nanospintronics. In this nascent field, the study of the CISS effect using paramagnetic chiral molecules, which could introduce another degree of freedom in controlling the spin transport, remains so far unexplored. To address this challenge, herein we propose the use of self-assembled monolayers (SAMs) of helical lanthanide-binding peptides. To elucidate the effect of the paramagnetic nuclei, monolayers of the peptide coordinating paramagnetic or diamagnetic ions are prepared. By means of spin-dependent electrochemistry, the CISS effect is demonstrated by cyclic voltammetry and electrochemical impedance measurements for both samples. Additionally, an implementation of the standard liquid-metal drop electron transport setup has been carried out, and this process helped to demonstrate the peptides' suitability for solid-state devices. Remarkably, the inclusion of a paramagnetic center in the peptide increases the spin polarization as was independently proved by different techniques. These findings permit the inclusion of magnetic biomolecules in the CISS field and pave the way to their implementation in a new generation of (bio)spintronic nanodevices.

Exploiting clock transitions for the chemical design of resilient molecular spin qubits.

Molecular spin qubits are chemical nanoobjects with promising applications that are so far hampered by the rapid loss of quantum information, a process known as decoherence. A strategy to improve this situation involves employing so-called Clock Transitions (CTs), which arise at anticrossings between spin energy levels. At CTs, the spin states are protected from magnetic noise and present an enhanced quantum coherence. Unfortunately, these optimal points are intrinsically hard to control since their transition energy cannot be tuned by an external magnetic field; moreover, their resilience towards geometric distortions has not yet been analyzed. Here we employ a python-based computational tool for the systematic theoretical analysis and chemical optimization of CTs. We compare three relevant case studies with increasingly complex ground states. First, we start with vanadium(iv)-based spin qubits, where the avoided crossings are controlled by hyperfine interaction and find that these S = 1/2 systems are very promising, in particular in the case of vanadyl complexes in an L-band pulsed EPR setup. Second, we proceed with a study of the effect of symmetry distortions in a holmium polyoxotungstate of formula [Ho(W5O18)2]9- where CTs had already been experimentally demonstrated. Here we determine the relative importance of the different structural distortions that causes the anticrossings. Third, we study the most complicated case, a polyoxopalladate cube [HoPd12(AsPh)8O32]5- which presents an unusually rich ground spin multiplet. This system allows us to find uniquely favorable CTs that could nevertheless be accessible with standard pulsed EPR equipment (X-band or Q-band) after a suitable chemical distortion to break the perfect cubic symmetry. Since anticrossings and CTs constitute a rich source of physical phenomena in very different kinds of quantum systems, the generalization of this study is expected to have impact not only in molecular spin science but also in other related fields such as molecular photophysics and photochemistry.