Computationally driven engineering of proteins aims to allow them to withstand an extended range of conditions and to mediate modified or novel functions. Therefore, it is crucial to the biotechnological industry, to biomedicine and to afford new challenges in environmental sciences, such as biocatalysis for green chemistry and bioremediation. In order to achieve these goals, it is important to clarify molecular mechanisms underlying proteins stability and modulating their interactions. So far, much attention has been given to hydrophobic and polar packing interactions and stability of the protein core. In contrast, the role of electrostatics and, in particular, of surface interactions has received less attention. However, electrostatics plays a pivotal role along the whole life cycle of a protein, since early folding steps to maturation, and it is involved in the regulation of protein localization and interactions with other cellular or artificial molecules. Short- and long-range electrostatic interactions, together with other forces, provide essential guidance cues in molecular and macromolecular assembly. We report here on methods for computing protein electrostatics and for individual or comparative analysis able to sort proteins by electrostatic similarity. Then, we provide examples of electrostatic analysis and fingerprints in natural protein evolution and in biotechnological design, in fields as diverse as biocatalysis, antibody and nanobody engineering, drug design and delivery, molecular virology, nanotechnology and regenerative medicine.

Genome variation is very high in influenza A viruses. However, viral evolution and spreading is strongly influenced by immunogenic features and capacity to bind host cells, depending in turn on the two major capsidic proteins. Therefore, such viruses are classified based on haemagglutinin and neuraminidase types, e.g. H5N1. Current analyses of viral evolution are based on serological and primary sequence comparison; however, comparative structural analysis of capsidic proteins can provide functional insights on surface regions possibly crucial to antigenicity and cell binding. We performed extensive structural comparison of influenza virus haemagglutinins and of their domains and subregions to investigate type- and/or domain-specific variation. We found that structural closeness and primary sequence similarity are not always tightly related; moreover, type-specific features could be inferred when comparing surface properties of haemagglutinin subregions, monomers and trimers, in terms of electrostatics and hydropathy. Focusing on H5N1, we found that variation at the receptor binding domain surface intriguingly relates to branching of still circulating clades from those ones that are no longer circulating. Evidence from this work suggests that integrating phylogenetic and serological analyses by extensive structural comparison can help in understanding the `functional evolution’ of viral surface determinants. In particular, variation in electrostatic and hydropathy patches can provide molecular evolution markers: intriguing surface charge redistribution characterizing the haemagglutinin receptor binding domains from circulating H5N1 clades 2 and 7 might have contributed to antigenic escape hence to their evolutionary success and spreading.

Avian influenza virus is a zoonotic agent that significantly impacts public health and the poultry industry. Monitoring viral evolution and spread is crucial for surveillance and tracing programmes, which are currently based on serological or DNA sequencing-phylogenetics analysis. However, virus-host interactions, antigenic drift and spreading of viral clades strongly depend on variation in the surface features of capsid proteins. We report here that in silico comparative structural analysis of haemagglutinin can reveal relevant evolutionary fingerprints, particularly when integrated with sequence-based analyses. Phylogenetic analyses of H9 viral strains from wild birds and poultry, performed with different methods, reliably led to clustering of viruses into five main groups. Subsequent comparison of structural features showed congruence between such clustering and surface electrostatic fingerprints. These latter fingerprints relate group-specific variations in electrostatic charges and isocontours to well-known haemagglutinin sites involved in the modulation of immune escape and host specificity. This work suggests that the integration of structural and sequence comparisons may enhance investigations of trends and relevant mechanisms in viral evolution.

Billions of years of co-evolution has made mitochondria central to the eukaryotic cell and organism life playing the role of cellular power plants, as indeed they are involved in most, if not all, important regulatory pathways. Neurological disorders depending on impaired mitochondrial function or homeostasis can be caused by the misregulation of “endogenous players”, such as nuclear or cytoplasmic regulators, which have been treated elsewhere. In this review, we focus on how exogenous agents, i.e., viral pathogens, or unbalanced microbiota in the gut-brain axis can also endanger mitochondrial dynamics in the central nervous system (CNS). Neurotropic viruses such as Herpes, Rabies, West-Nile, and Polioviruses seem to hijack neuronal transport networks, commandeering the proteins that mitochondria typically use to move along neurites. However, several neurological complications are also associated to infections by pandemic viruses, such as Influenza A virus and SARS-CoV-2 coronavirus, representing a relevant risk associated to seasonal flu, coronavirus disease-19 (COVID-19) and “Long-COVID”. Emerging evidence is depicting the gut microbiota as a source of signals, transmitted via sensory neurons innervating the gut, able to influence brain structure and function, including cognitive functions. Therefore, the direct connection between intestinal microbiota and mitochondrial functions might concur with the onset, progression, and severity of CNS diseases.

BackgroundType A influenza viruses circulate and spread among wild birds and mostly consist of low pathogenic strains. However, fast genome variation timely results in the insurgence of high pathogenic strains, which when infecting poultry birds may cause a million deaths and strong commercial damage. More importantly, the host shift may concern these viruses and sustained human-to-human transmission may result in a dangerous pandemic outbreak. Therefore, fingerprints specific to either low or high pathogenic strains may represent a very important tool for global surveillance.ResultsWe combined Normal Modes Analysis and surface electrostatic analysis of a mixed strain dataset of influenza A virus haemagglutinins from high and low pathogenic strains in order to infer specific fingerprints. Normal Modes Analysis sorted the strains in two different, homogeneous clusters; sorting was independent of clades and specific instead to high vs low pathogenicity. A deeper analysis of fluctuations and flexibility regions unveiled a special role for the 110-helix region. Specific sorting was confirmed by surface electrostatics analysis, which further allowed to focus on regions and mechanisms possibly crucial to the low-to-high transition.ConclusionsEvidence from previous work demonstrated that changes in surface electrostatics are associated with the evolution and spreading of avian influenza A virus clades, and seemingly involved also in the avian to mammalian host shift. This work shows that a combination of electrostatics and Normal Modes Analysis can also identify fingerprints specific to high and low pathogenicity. The possibility to predict which specific mutations may result in a shift to high pathogenicity may help in surveillance and vaccine development.

Computer-aided analysis of proteins or nucleic acids seems like a matter of course nowadays; however, the history of Bioinformatics and Computational Biology is quite recent. The advent of high-throughput sequencing has led to the production of “big data”, which has also affected the field of virology. The collaboration between the communities of bioinformaticians and virologists already started a few decades ago and it was strongly enhanced by the recent SARS-CoV-2 pandemics. In this article, which is the first in a series on how bioinformatics can enhance virus research, we show that highly useful information is retrievable from selected general and dedicated databases. Indeed, an enormous amount of information—both in terms of nucleotide/protein sequences and their annotation—is deposited in the general databases of international organisations participating in the International Nucleotide Sequence Database Collaboration (INSDC). However, more and more virus-specific databases have been established and are progressively enriched with the contents and features reported in this article. Since viruses are intracellular obligate parasites, a special focus is given to host-pathogen protein-protein interaction databases. Finally, we illustrate several phylogenetic and phylodynamic tools, combining information on algorithms and features with practical information on how to use them and case studies that validate their usefulness. Databases and tools for functional inference will be covered in the next article of this series: Bioinformatics goes viral: II. Sequence-based and structure-based functional analyses for boosting virus research.