Nanoparticles have been making their way in biomedical applications and personalized medicine, allowing for the coupling of diagnostics and therapeutics into a single nanomaterial—nanotheranostics. Gold nanoparticles, in particular, have unique features that make them excellent nanomaterials for theranostics, enabling the integration of targeting, imaging and therapeutics in a single platform, with proven applicability in the management of heterogeneous diseases, such as cancer. In this review, we focus on gold nanoparticle-based theranostics at the lab bench, through pre-clinical and clinical stages. With few products facing clinical trials, much remains to be done to effectively assess the real benefits of nanotheranostics at the clinical level. Hence, we also discuss the efforts currently being made to translate nanotheranostics into the market, as well as their commercial impact.

AbstractVanadium is an element ubiquitously present in our planet's crust and thus there are several organisms that use vanadium for activity or function of proteins. Examples are the vanadium-dependent haloperoxidases and the vanadium-containing nitrogenases. Some organisms that use vanadium have extremely efficient and selective protein-dependent systems for uptake and transport of vanadium and are able to accumulate high levels of vanadium from seawater, vanabins being a unique family of vanadium binding proteins found in ascidians involved in this process. For all of the systems a discussion regarding the role of the V-containing proteins is provided, mostly centered on structural aspects of the vanadium site and, when possible or relevant, relating this to the mechanisms operating. Phosphate is very important in biological systems and is involved in an extensive number of biological recognition and bio-catalytic systems. Vanadate(V) is able to inhibit many of the enzymes involved in these processes, such as ATPases, phosphatases, ribonucleases, phosphodiesterases, phosphoglucomutase and glucose-6-phosphatase, and it appears clear that this is closely related to the analogous physicochemical properties of vanadate and phosphate. The ability of vanadium to interfere with the metabolic processes involving Ca2+ and Mg2+, connected with its versatility to undergo changes in coordination geometry, allow V to influence the function of a large variety of phosphate-metabolizing enzymes and vanadate(V) salts and compounds have been frequently used either as inhibitors of these enzymes, or as probes to study the mechanisms of their reactions and catalytic cycle. In this review we give an overview of the many examples so far reported, also disclosing that vanadate(IV) may also have an equally efficient inhibiting effect. The prospective application of vanadium compounds as therapeutics has also been an important topic of research. How vanadium may be transported in blood and up-taken by cells are particularly relevant issues, this being mainly dependent on transferrin (and albumin) present in blood plasma. The thousands of studies reported on the effects of vanadium compounds reflect the complexity of the interactions occurring. Although it is not easy to anticipate/determine if a particular effect observed in a test tube or in vitro is also going to take place in vivo, it is clear that vanadium ions may interfere with many metabolic processes at many distinct levels. Emphasis is given on structural and functional aspects of vanadium–protein interactions relevant for vanadium binding and/or for clarification of role of the metal center in the reaction mechanisms. The additional knowledge that the presence of vanadium can change the action of a protein, other than simply inhibiting it, may also be important to understand how vanadium affects biological systems. This possibility, together with the vanadate–phosphate analogy further potentiates the belief that vanadium probably has relevant functions in living beings, which may involve interaction or incorporation of the metal ion and/or its compounds with several proteins.

Metalloproteases have evolved in a vast number of biological systems, being one of the most diverse types of proteases and presenting a wide range of folds and catalytic metal ions. Given the increasing understanding of protein internal dynamics and its role in enzyme function, we are interested in assessing how the structural heterogeneity of metalloproteases translates into their dynamics. Therefore, the dynamical profile of the clan MA type protein thermolysin, derived from an Elastic Network Model of protein structure, was evaluated against those obtained from a set of experimental structures and molecular dynamics simulation trajectories. A close correspondence was obtained between modes derived from the coarse-grained model and the subspace of functionally-relevant motions observed experimentally, the later being shown to be encoded in the internal dynamics of the protein. This prompted the use of dynamics-based comparison methods that employ such coarse-grained models in a representative set of clan members, allowing for its quantitative description in terms of structural and dynamical variability. Although members show structural similarity, they nonetheless present distinct dynamical profiles, with no apparent correlation between structural and dynamical relatedness. However, previously unnoticed dynamical similarity was found between the relevant members Carboxypeptidase Pfu, Leishmanolysin, and Botulinum Neurotoxin Type A, despite sharing no structural similarity. Inspection of the respective alignments shows that dynamical similarity has a functional basis, namely the need for maintaining proper intermolecular interactions with the respective substrates. These results suggest that distinct selective pressure mechanisms act on metalloproteases at structural and dynamical levels through the course of their evolution. This work shows how new insights on metalloprotease function and evolution can be assessed with comparison schemes that incorporate information on protein dynamics. The integration of these newly developed tools, if applied to other protein families, can lead to more accurate and descriptive protein classification systems.