The nuclear export protein (NEP) (NS2) of the highly pathogenic human-derived H5N1 strain A/Thailand/1(KAN-1)/2004 with the adaptive mutation M16I greatly enhances the polymerase activity in human cells in a concentration-dependent manner. While low NEP levels enhance the polymerase activity, high levels are inhibitory. To gain insights into the underlying mechanism, we analyzed the effect of NEP deletion mutants on polymerase activity after reconstitution in human cells. This revealed that the polymerase-enhancing function of NEP resides in the C-terminal moiety and that removal of the last three amino acids completely abrogates this activity. Moreover, compared to full-length NEP, the C-terminal moiety alone exhibited significantly higher activity and seemed to be deregulated, since even the highest concentration did not result in an inhibition of polymerase activity. To determine transient interactions between the N- and C-terminal domains in cis , we fused both ends of NEP to a split click beetle luciferase and performed fragment complementation assays. With decreasing temperature, increased luciferase activity was observed, suggesting that intramolecular binding between the C- and N-terminal domains is preferentially stabilized at low temperatures. This stabilizing effect was significantly reduced with the adaptive mutation M16I or a combination of adaptive mutations (M16I, Y41C, and E75G), which further increased polymerase activity also at 34°C. We therefore propose a model in which the N-terminal moiety of NEP exerts an inhibitory function by back-folding to the C-terminal domain. In this model, adaptive mutations in NEP decrease binding between the C- and N-terminal domains, thereby allowing the protein to “open up” and become active already at a low temperature.

This system allows the high-throughput protein interaction analysis on microarrays. We apply the interference technology 1λ–imaging reflectometric interferometry (iRIf) as a label-free detection method and create microfluidic flow cells in microscope slide format for low reagent consumption and lab work compatibility. By now, most prominent for imaging label-free interaction analyses on microarrays are imaging surface plasmon resonance (SPR) methods, quartz crystal microbalance, or biolayer interferometry. SPR is sensitive against temperature drifts and suffers from plasmon crosstalk, and all systems lack array size (maximum 96 spots). Our detection system is robust against temperature drifts. Microarrays are analyzed with a spatial resolution of 7 µm and time resolution of ≤50 fps. System sensitivity is competitive, with random noise of <5 × 10⁻⁵ and baseline drift of <3 × 10⁻⁶. Currently available spotting technologies limit array sizes to ~4 spots/mm² (1080 spots/array); our detection system would allow ~40 spots/mm² (10,800 spots/array). The microfluidic flow cells consist of structured PDMS inlays sealed by versatilely coated glass slides immobilizing the microarray. The injection protocol determines reagent volumes, priming rates, and flow cell temperatures for up to 44 reagents; volumes of ≤300 µL are validated. The system is validated physically by the biotinylated bovine serum albumin streptavidin assay and biochemically by thrombin aptamer interaction analysis, resulting in a KD of ~100 nM.

Today, whole genomes are analyzed by Next‐Generation Sequencing systems, or displayed by DNA microarray in situ synthesis. However, genomic data are mainly static and do not exactly reveal the complexity of protein interaction networks of any organism or cell. To investigate protein interactions, the generation of protein microarrays, displaying whole proteomes is a prerequisite. But traditional protein microarray generation is time consuming, costly, and is restricted by a wide range of technical difficulties concerning cell culturing, protein purification, and transfer onto microarray. Some of these obstacles can be bypassed by application of cell‐free expression systems, enabling fast in situ synthesis of protein microarrays without need for cell culturing. This review provides a historical timeline of the different methods to generate protein microarrays by cell‐free expression, highlights differences and similarities, and reports the current state of the different approaches.

In the rapidly expanding field of peptide therapeutics, the short in vivo half-life of peptides represents a considerable limitation for drug action. D-peptides, consisting entirely of the dextrorotatory enantiomers of naturally occurring levorotatory amino acids (AAs), do not suffer from these shortcomings as they are intrinsically resistant to proteolytic degradation, resulting in a favourable pharmacokinetic profile. To experimentally identify D-peptide binders to interesting therapeutic targets, so-called mirror-image phage display is typically performed, whereby the target is synthesized in D-form and L-peptide binders are screened as in conventional phage display. This technique is extremely powerful, but it requires the synthesis of the target in D-form, which is challenging for large proteins. Here we present finDr, a novel web server for the computational identification and optimization of D-peptide ligands to any protein structure (https://findr.biologie.uni-freiburg.de/). finDr performs molecular docking to virtually screen a library of helical 12-mer peptides extracted from the RCSB Protein Data Bank (PDB) for their ability to bind to the target. In a separate, heuristic approach to search the chemical space of 12-mer peptides, finDr executes a customizable evolutionary algorithm (EA) for the de novo identification or optimization of D-peptide ligands. As a proof of principle, we demonstrate the validity of our approach to predict optimal binders to the pharmacologically relevant target phenol soluble modulin alpha 3 (PSMα3), a toxin of methicillin-resistant Staphylococcus aureus (MRSA). We validate the predictions using in vitro binding assays, supporting the success of this approach. Compared to conventional methods, finDr provides a low cost and easy-to-use alternative for the identification of D-peptide ligands against protein targets of choice without size limitation. We believe finDr will facilitate D-peptide discovery with implications in biotechnology and biomedicine.

COVID-19 is a severe acute respiratory disease caused by SARS-CoV-2, a novel betacoronavirus discovered in December 2019 and closely related to the SARS coronavirus (CoV). Both viruses use the human ACE2 receptor for cell entry, recognizing it with the Receptor Binding Domain (RBD) of the S1 subunit of the viral spike (S) protein. The S2 domain mediates viral fusion with the host cell membrane. Experience with SARS and MERS coronaviruses has shown that potent monoclonal neutralizing antibodies against the RBD can inhibit the interaction with the virus cellular receptor (ACE2 for SARS) and block the virus cell entry. Assuming that a similar strategy would be successful against SARS-CoV-2, we used phage display to select from the human naïve universal antibody gene libraries HAL9/10 anti-SARS-CoV-2 spike antibodies capable of inhibiting interaction with ACE2. 309 unique fully human antibodies against S1 were identified. 17 showed more than 75% inhibition of spike binding to cells expressing ACE2 in the scFv-Fc format, assessed by flow cytometry and several antibodies showed even an 50% inhibition at a molar ratio of the antibody to spike protein or RBD of 1:1. All 17 scFv-Fc were able to bind the isolated RBD, four of them with sub-nanomolar EC50. Furthermore, these scFv-Fc neutralized active SARS-CoV-2 virus infection of VeroE6 cells. In a final step, the antibodies neutralizing best as scFv-Fc were converted into the IgG format. The antibody STE73-2E9 showed neutralization of active SARS-CoV-2 with an IC50 0.43 nM and is binding to the ACE2-RBD interface. Universal libraries from healthy human donors offer the advantage that antibodies can be generated quickly and independent from the availability of material from recovered patients in a pandemic situation.