Thrombocytopenia, characterized by reduced platelet count, increases mortality in COVID-19 patients. We performed a computational investigation of antibody-induced cross-reactivity due to molecular mimicry between SARS-CoV-2 Spike protein and human thrombopoietin, the regulator of platelet production, as a mechanism for thrombocytopenia in COVID-19 infections. The presence of a common sequence motif with similar structure and antibody-binding properties for these proteins strongly indicate shared molecular mimicry. Recent reports of antibodies in COVID-19 patients and pre-pandemic samples against epitopes containing the motif offer additional support for the cross-reactivity. Altogether, this suggests cross-reactivity between an antibody with affinity for Spike protein and a human protein. Consideration of cross-reactivity for SARS-CoV-2 is important for therapeutic intervention and when designing the next generation of COVID-19 vaccines to avoid potential autoimmune interference.

The mammalian high mobility group protein AT-hook 2 (HMGA2) houses three motifs that preferentially bind short stretches of AT-rich DNA regions. These DNA binding motifs, known as ‘AT-hooks’, are traditionally characterized as being unstructured. Upon binding to AT-rich DNA, they form ordered assemblies. It is this disordered-to-ordered transition that has implicated HMGA2 as a protein actively involved in many biological processes, with abnormal HMGA expression linked to a variety of health problems including diabetes, obesity, and oncogenesis. In the current work, the solution binding dynamics of the three ‘AT-hook’ peptides (ATHPs) with AT-rich DNA hairpin substrates were studied using DNA UV melting studies, fluorescence spectroscopy, native ion mobility spectrometry-mass spectrometry (IMS-MS), solution isothermal titration calorimetry (ITC) and molecular modeling. Results showed that the ATHPs bind to the DNA to form a single, 1:1 and 2:1, ‘key-locked’ conformational ensemble. The molecular models showed that 1:1 and 2:1 complex formation is driven by the capacity of the ATHPs to bind to the minor and major grooves of the AT-rich DNA oligomers. Complementary solution ITC results confirmed that the 2:1 stoichiometry of ATHP: DNA is originated under native conditions in solution.

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There has been an alarming rise in antibacterial resistant infections in recent years due to the widespread use of antibiotics, and there is a dire need for the development of new antibiotics utilizing novel modes of action. Lantibiotics are promising candidates to engage in the fight against resistant strains of bacteria due to their unique modes of action, including interference with cell wall synthesis by binding to lipid II and creating pores in bacterial membranes. In this study, we use atomic-scale molecular dynamics computational studies to compare both the lipid II binding ability and the membrane interactions of five lanthipeptides that are commonly used in antimicrobial research: nisin, Mutacin 1140 (MU1140), gallidermin, NVB302, and NAI107. Among the five peptides investigated, nisin is found to be the most efficient at forming water channels through a membrane, whereas gallidermin and MU1140 are found to be better at binding the lipid II molecules. Nisin’s effectiveness in facilitating water transport across the membrane is due to the creation of several different water trajectories along with no significant water delay points along the paths. The shorter peptide deoxyactagardine B (NVB302) was found to not form a water channel. These detailed observations provide insights into the dual mechanisms of the action of lantibiotic peptides and can facilitate the design and development of novel lanthipeptides by strategic placement of different residues.

the phenotypic classification of the compounds. Dimensional reduction and clustering of behaviors based on image analysis successfully recapitulates the phenomenological differences between the compounds, suggesting that bioinformatic approaches may be able to successfully pick out interesting compounds from large behavioral screens without extensive manual analysis of the behavioral data.