Recent advances in human viruses imaging studies

Protein Folding Interdiction Strategy for Therapeutic Drug Development in Viral Diseases: Ebola VP40 and Influenza A M1

In a recent paper, we proposed the folding interdiction target region (FITR) strategy for therapeutic drug design in SARS-CoV-2. This paper expands the application of the FITR strategy by proposing therapeutic drug design approaches against Ebola virus disease and influenza A. We predict target regions for folding interdicting drugs on correspondingly relevant structural proteins of both pathogenic viruses: VP40 of Ebola, and matrix protein M1 of influenza A. Identification of the protein targets employs the sequential collapse model (SCM) for protein folding. It is explained that the model predicts natural peptide candidates in each case from which to start the search for therapeutic drugs. The paper also discusses how these predictions could be tested, as well as some challenges likely to be found when designing effective therapeutic drugs from the proposed peptide candidates. The FITR strategy opens a potential new avenue for the design of therapeutic drugs that promises to be effective against infectious diseases.

How Computational Models Enable Mechanistic Insights into Virus Infection

An implicit aim in cellular infection biology is to understand the mechanisms how viruses, microbes, eukaryotic parasites, and fungi usurp the functions of host cells and cause disease. Mechanistic insight is a deep understanding of the biophysical and biochemical processes that give rise to an observable phenomenon. It is typically subject to falsification, that is, it is accessible to experimentation and empirical data acquisition. This is different from logic and mathematics, which are not empirical, but built on systems of inherently consistent axioms. Here, we argue that modeling and computer simulation, combined with mechanistic insights, yields unprecedented deep understanding of phenomena in biology and especially in virus infections by providing a way of showing sufficiency of a hypothetical mechanism. This ideally complements the necessity statements accessible to empirical falsification by additional positive evidence. We discuss how computational implementations of mathematical models can assist and enhance the quantitative measurements of infection dynamics of enveloped and non-enveloped viruses and thereby help generating causal insights into virus infection biology.

Single-Molecule Localization Microscopy in Eukaryotes

Super-resolution fluorescence imaging by photoactivation or photoswitching of single fluorophores and position determination (single-molecule localization microscopy, SMLM) provides microscopic images with subdiffraction spatial resolution. This technology has enabled new insights into how proteins are organized in a cellular context, with a spatial resolution approaching virtually the molecular level. A unique strength of SMLM is that it delivers molecule-resolved information, along with super-resolved images of cellular structures. This allows quantitative access to cellular structures, for example, how proteins are distributed and organized and how they interact with other biomolecules. Ultimately, it is even possible to determine protein numbers in cells and the number of subunits in a protein complex. SMLM thus has the potential to pave the way toward a better understanding of how cells function at the molecular level. In this review, we describe how SMLM has contributed new knowledge in eukaryotic biology, and we specifically focus on quantitative biological data extracted from SMLM images.