Large scale genome sequencing allowed the identification of a massive number of genetic variations, whose impact on human health is still unknown. In this review we analyze, by an in silico-based strategy, the impact of missense variants on cancer-related genes, whose effect on protein stability and function was experimentally determined. We collected a set of 164 variants from 11 proteins to analyze the impact of missense mutations at structural and functional levels, and to assess the performance of state-of-the-art methods (FoldX and Meta-SNP) for predicting protein stability change and pathogenicity. The result of our analysis shows that a combination of experimental data on protein stability and in silico pathogenicity predictions allowed the identification of a subset of variants with a high probability of having a deleterious phenotypic effect, as confirmed by the significant enrichment of the subset in variants annotated in the COSMIC database as putative cancer-driving variants. Our analysis suggests that the integration of experimental and computational approaches may contribute to evaluate the risk for complex disorders and develop more effective treatment strategies.

Serine hydroxymethyltransferase from the psychrophilic microorganism Psychromonas ingrahamii was expressed in Escherichia coli and purified as a His-tag fusion protein. The enzyme was characterized with respect to its spectroscopic, catalytic, and thermodynamic properties. The properties of the psychrophilic enzyme have been contrasted with the characteristics of the homologous counterpart from E. coli, which has been structurally and functionally characterized in depth and with which it shares 75% sequence identity. Spectroscopic measures confirmed that the psychrophilic enzyme displays structural properties almost identical to those of the mesophilic counterpart. At variance, the P. ingrahamii enzyme showed decreased thermostability and high specific activity at low temperature, both of which are typical features of cold adapted enzymes. Furthermore, it was a more efficient biocatalyst compared to E. coli serine hydroxymethyltransferase (SHMT) particularly for side reactions. Many β-hydroxy-α-amino acids are SHMT substrates and represent important compounds in the synthesis of pharmaceuticals, agrochemicals and food additives. Thanks to these attractive properties, this enzyme could have a significant potential for biotechnological applications.

We present in this work a first X‐ray Absorption Spectroscopy study of the interactions of Zn with human BST2/tetherin and SARS‐CoV‐2 orf7a proteins as well as with some of their complexes. The analysis of the XANES region of the measured spectra shows that Zn binds to BST2, as well as to orf7a, thus resulting in the formation of BST2‐orf7a complexes. This structural information confirms the the conjecture, recently put forward by some of the present Authors, according to which the accessory orf7a (and possibly also orf8) viral protein are capable of interfering with the BST2 antiviral activity. Our explanation for this behavior is that, when BST2 gets in contact with Zn bound to the orf7a Cys₁₅ ligand, it has the ability of displacing the metal owing to the creation of a new disulfide bridge across the two proteins. The formation of this BST2‐orf7a complex destabilizes BST2 dimerization, thus impairing the antiviral activity of the latter.

Frataxin (FXN) is a highly conserved protein found in prokaryotes and eukaryotes that is required for efficient regulation of cellular iron homeostasis. Experimental evidence associates amino acid substitutions of the FXN to Friedreich Ataxia, a neurodegenerative disorder. Recently, new thermodynamic experiments have been performed to study the impact of somatic variations identified in cancer tissues on protein stability. The Critical Assessment of Genome Interpretation (CAGI) data provider at the University of Rome measured the unfolding free energy of a set of variants (FXN challenge data set) with far‐UV circular dichroism and intrinsic fluorescence spectra. These values have been used to calculate the change in unfolding free energy between the variant and wild‐type proteins at zero concentration of denaturant . The FXN challenge data set, composed of eight amino acid substitutions, was used to evaluate the performance of the current computational methods for predicting the value associated with the variants and to classify them as destabilizing and not destabilizing. For the fifth edition of CAGI, six independent research groups from Asia, Australia, Europe, and North America submitted 12 sets of predictions from different approaches. In this paper, we report the results of our assessment and discuss the limitations of the tested algorithms.

In this paper we prove in the exemplary case of the amyloid-β peptide in complex with Cu(ii) that at the current low temperatures employed in XAS experiments, the time needed for collecting a good quality XAS spectrum is significantly shorter than the time after which structural damage becomes appreciable. Our method takes advantage of the well-known circumstance that the transition of Cu from the oxidized to the reduced form under ionizing radiation can be quantified by monitoring a characteristic peak in the pre-edge region. We show that there exists a sufficiently large time window in which good XAS spectra can be acquired before the structure around the oxidized Cu(ii) ion reorganizes itself into the reduced Cu(i) “resting” structure. We suggest that similar considerations apply to other cases of biological interest, especially when dealing with macromolecules in complex with transition metal ions.