Spermine and spermidine bind CXCR4 and inhibit CXCR4- but not CCR5-tropic HIV-1 infection

Semen is an important vector for sexual HIV-1 transmission. Although CXCR4-tropic (X4) HIV-1 may be present in semen, almost exclusively CCR5-tropic (R5) HIV-1 causes systemic infection after sexual intercourse. To identify factors that may limit sexual X4-HIV-1 transmission, we generated a seminal fluid-derived compound library and screened it for antiviral agents. We identified four adjacent fractions that blocked X4-HIV-1 but not R5-HIV-1 and found that they all contained spermine and spermidine, abundant polyamines in semen. We showed that spermine, which is present in semen at concentrations up to 14 mM, binds CXCR4 and selectively inhibits cell-free and cell-associated X4-HIV-1 infection of cell lines and primary target cells at micromolar concentrations. Our findings suggest that seminal spermine restricts sexual X4-HIV-1 transmission.

PPI-Affinity: A Web Tool for the Prediction and Optimization of Protein-Peptide and Protein-Protein Binding Affinity

Virtual screening of protein–protein and protein–peptide interactions is a challenging task that directly impacts the processes of hit identification and hit-to-lead optimization in drug design projects involving peptide-based pharmaceuticals. Although several screening tools designed to predict the binding affinity of protein–protein complexes have been proposed, methods specifically developed to predict protein–peptide binding affinity are comparatively scarce. Frequently, predictors trained to score the affinity of small molecules are used for peptides indistinctively, despite the larger complexity and heterogeneity of interactions rendered by peptide binders. To address this issue, we introduce PPI-Affinity, a tool that leverages support vector machine (SVM) predictors of binding affinity to screen datasets of protein–protein and protein–peptide complexes, as well as to generate and rank mutants of a given structure. The performance of the SVM models was assessed on four benchmark datasets, which include protein–protein and protein–peptide binding affinity data. In addition, we evaluated our model on a set of mutants of EPI-X4, an endogenous peptide inhibitor of the chemokine receptor CXCR4, and on complexes of the serine proteases HTRA1 and HTRA3 with peptides. PPI-Affinity is freely accessible at https://protdcal.zmb.uni-due.de/PPIAffinity.

The role of DNA nanostructures in the catalytic properties of an allosterically regulated protease

DNA-scaffolded enzymes typically show altered kinetic properties; however, the mechanism behind this phenomenon is still poorly understood. We address this question using thrombin, a model of allosterically regulated serine proteases, encaged into DNA origami cavities with distinct structural and electrostatic features. We compare the hydrolysis of substrates that differ only in their net charge due to a terminal residue far from the cleavage site and presumably involved in the allosteric activation of thrombin. Our data show that the reaction rate is affected by DNA/substrate electrostatic interactions, proportionally to the degree of DNA/enzyme tethering. For substrates of opposite net charge, this leads to an inversion of the catalytic response of the DNA-scaffolded thrombin when compared to its freely diffusing counterpart. Hence, by altering the electrostatic environment nearby the encaged enzyme, DNA nanostructures interfere with charge-dependent mechanisms of enzyme-substrate recognition and may offer an alternative tool to regulate allosteric processes through spatial confinement.

Effect of Organic Solvents on the Structure and Activity of a Minimal Lipase

Lipases are ubiquitously used in chemo-enzymatic synthesis and industrial applications. Nevertheless, the modulation of the activity of lipases by organic solvents still is not fully understood at the molecular level. We systematically investigated the activity and structure of lipase A from Bacillus subtilis in binary water-organic solvent mixtures of dimethyl sulfoxide (DMSO), acetonitrile (ACN), and isopropyl alcohol (IPA) using activity assays, fluorescence spectroscopy, molecular dynamics (MD) simulations, and FRET/MD analysis. The enzymatic activity strongly depended on the type and amount of organic solvent in the reaction media. Whereas IPA and ACN reduced the activity of the enzyme, small concentrations of DMSO led to lipase activation via an uncompetitive mechanism. DMSO molecules did not directly interfere with the binding of the substrate in the active site, contrary to what is known for other solvents and enzymes. We propose that the His156-Asp133 interaction, the binding of organic molecules to the active site, and the water accessibility of the substrate are key factors modulating the catalytic activity. Furthermore, we rationalized the role of solvent descriptors on the regulation of enzymatic activity in mixtures with low concentrations of the organic molecule, with prospective implications for the optimization of biocatalytic processes via solvent tuning.

Respiratory ß-2-Microglobulin exerts pH dependent antimicrobial activity

The respiratory tract is a major entry site for microbial pathogens. To combat bacterial infections, the immune system has various defense mechanisms at its disposal, including antimicrobial peptides (AMPs). To search for novel AMPs from the respiratory tract, a peptide library from human broncho-alveolar-lavage (BAL) fluid was screened for antimicrobial activity by radial diffusion assays allowing the efficient detection of antibacterial activity within a small sample size. After repeated testing-cycles and subsequent purification, we identified ß-2-microglobulin (B2M) in antibacterially active fractions. B2M belongs to the MHC-1 receptor complex present at the surface of nucleated cells. It is known to inhibit the growth of Listeria monocytogenes and Escherichia coli and to facilitate phagocytosis of Staphylococcus aureus. Using commercially available B2M we confirmed a dose-dependent inhibition of Pseudomonas aeruginosa and L. monocytogenes. To characterize AMP activity within the B2M sequence, peptide fragments of the molecule were tested for antimicrobial activity. Activity could be localized to the C-terminal part of B2M. Investigating pH dependency of the antimicrobial activity of B2M demonstrated an increased activity at pH values of 5.5 and below, a hallmark of infection and inflammation. Sytox green uptake into bacterial cells following the exposure to B2M was determined and revealed a pH-dependent loss of bacterial membrane integrity. TEM analysis showed areas of disrupted bacterial membranes in L. monocytogenes incubated with B2M and high amounts of lysed bacterial cells. In conclusion, B2M as part of a ubiquitous cell surface complex may represent a potent antimicrobial agent by interfering with bacterial membrane integrity.

Inhibition of Staphylococcus aureus biofilm-forming functional amyloid by molecular tweezers

Biofilms are rigid and largely impenetrable three-dimensional matrices constituting virulence determinants of various pathogenic bacteria. Here, we demonstrate that molecular tweezers, unique supramolecular artificial receptors, modulate biofilm formation of Staphylococcus aureus. In particular, the tweezers affect the structural and assembly properties of phenol-soluble modulin α1 (PSMα1), a biofilm-scaffolding functional amyloid peptide secreted by S. aureus. The data reveal that CLR01, a diphosphate tweezer, exhibits significant S. aureus biofilm inhibition and disrupts PSMα1 self-assembly and fibrillation, likely through inclusion of lysine side chains of the peptide. In comparison, different peptide binding occurs in the case of CLR05, a tweezer containing methylenecarboxylate units, which exhibits lower affinity for the lysine residues yet disrupts S. aureus biofilm more strongly than CLR01. Our study points to a possible role for molecular tweezers as potent biofilm inhibitors and antibacterial agents, particularly against untreatable biofilm-forming and PSM-producing bacteria, such as methicillin-resistant S. aureus.

Specific inhibition of the Survivin-CRM1 interaction by peptide-modified molecular tweezers

Survivin's dual function as apoptosis inhibitor and regulator of cell proliferation is mediated via its interaction with the export receptor CRM1. This protein-protein interaction represents an attractive target in cancer research and therapy. Here, we report a sophisticated strategy addressing Survivin's nuclear export signal (NES), the binding site of CRM1, with advanced supramolecular tweezers for lysine and arginine. These were covalently connected to small peptides resembling the natural, self-complementary dimer interface which largely overlaps with the NES. Several biochemical methods demonstrated sequence-selective NES recognition and interference with the critical receptor interaction. These data were strongly supported by molecular dynamics simulations and multiscale computational studies. Rational design of lysine tweezers equipped with a peptidic recognition element thus allowed to address a previously unapproachable protein surface area. As an experimental proof-of-principle for specific transport signal interference, this concept should be transferable to any protein epitope with a flanking well-accessible lysine.

Peptide and peptide-based inhibitors of SARS-CoV-2 entry

To date, no effective vaccines or therapies are available against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pandemic agent of the coronavirus disease 2019 (COVID-19). Due to their safety, efficacy and specificity, peptide inhibitors hold great promise for the treatment of newly emerging viral pathogens. Based on the known structures of viral proteins and their cellular targets, antiviral peptides can be rationally designed and optimized. The resulting peptides may be highly specific for their respective targets and particular viral pathogens or exert broad antiviral activity. Here, we summarize the current status of peptides inhibiting SARS-CoV-2 entry and outline the strategies used to design peptides targeting the ACE2 receptor or the viral spike protein and its activating proteases furin, transmembrane serine protease 2 (TMPRSS2), or cathepsin L. In addition, we present approaches used against related viruses such as SARS-CoV-1 that might be implemented for inhibition of SARS-CoV-2 infection.

Engineering protein fragments via evolutionary and protein-protein interaction algorithms: de novo design of peptide inhibitors for FO F1 -ATP synthase

Enzyme subunit interfaces have remarkable potential in drug design as both target and scaffold for their own inhibitors. We show an evolution-driven strategy for the de novo design of peptide inhibitors targeting interfaces of the Escherichia coli FoF1-ATP synthase as a case study. The evolutionary algorithm ROSE was applied to generate diversity-oriented peptide libraries by engineering peptide fragments from ATP synthase interfaces. The resulting peptides were scored with PPI-Detect, a sequence-based predictor of protein-protein interactions. Two selected peptides were confirmed by in vitro inhibition and binding tests. The proposed methodology can be widely applied to design peptides targeting relevant interfaces of enzymatic complexes.

Supramolecular Mechanism of Viral Envelope Disruption by Molecular Tweezers

Broad-spectrum antivirals are powerful weapons against dangerous viruses where no specific therapy exists, as in the case of the ongoing SARS-CoV-2 pandemic. We discovered that a lysine- and arginine-specific supramolecular ligand (CLR01) destroys enveloped viruses, including HIV, Ebola, and Zika virus, and remodels amyloid fibrils in semen that promote viral infection. Yet, it is unknown how CLR01 exerts these two distinct therapeutic activities. Here, we delineate a novel mechanism of antiviral activity by studying the activity of tweezer variants: the “phosphate tweezer” CLR01, a “carboxylate tweezer” CLR05, and a “phosphate clip” PC. Lysine complexation inside the tweezer cavity is needed to antagonize amyloidogenesis and is only achieved by CLR01. Importantly, CLR01 and CLR05 but not PC form closed inclusion complexes with lipid head groups of viral membranes, thereby altering lipid orientation and increasing surface tension. This process disrupts viral envelopes and diminishes infectivity but leaves cellular membranes intact. Consequently, CLR01 and CLR05 display broad antiviral activity against all enveloped viruses tested, including herpesviruses, Measles virus, influenza, and SARS-CoV-2. Based on our mechanistic insights, we potentiated the antiviral, membrane-disrupting activity of CLR01 by introducing aliphatic ester arms into each phosphate group to act as lipid anchors that promote membrane targeting. The most potent ester modifications harbored unbranched C4 units, which engendered tweezers that were approximately one order of magnitude more effective than CLR01 and nontoxic. Thus, we establish the mechanistic basis of viral envelope disruption by specific tweezers and establish a new class of potential broad-spectrum antivirals with enhanced activity.

ProtDCal-Suite: A web server for the numerical codification and functional analysis of proteins

Computational tools for the analysis of protein data and the prediction of biological properties are essential in life sciences and biomedical research. Here, we introduce ProtDCal-Suite, a web server comprising a set of machine learning-based methods for studying proteins. The main module of ProtDCal-Suite is the ProtDCal software. ProtDCal translates the structural information of proteins into numerical descriptors that serve as input to machine-learning techniques. The ProtDCal-Suite server also incorporates a post-processing optional stage that allows ranking and filtering the obtained descriptors by computing their Shannon entropy values across the input set of proteins. ProtDCal's codification was used in the development of models for the prediction of specific protein properties. Thus, the other modules of ProtDCal-Suite are protein analysis tools implemented using ProtDCal's descriptors. Among them are PPI-Detect, for predicting the interaction likelihood of protein-protein and protein-peptide pairs, Enzyme Identifier, for identifying enzymes from amino acid sequences or 3D structures, and Pred-NGlyco, for predicting N-glycosylation sites. ProtDCal-Suite is freely accessible at https://protdcal.zmb.uni-due.de.

A Placenta Derived C-Terminal Fragment of β-Hemoglobin With Combined Antibacterial and Antiviral Activity

The placenta acts as physical and immunological barrier against the transmission of viruses and bacteria from mother to fetus. However, the specific mechanisms by which the placenta protects the developing fetus from viral and bacterial pathogens are poorly understood. To identify placental peptides and small proteins protecting from viral and bacterial infections, we generated a peptide library from 10 kg placenta by chromatographic means. Screening the resulting 250 fractions against Herpes-Simplex-Virus 2 (HSV-2), which is rarely transmitted through the placenta, in a cell-based system identified two adjacent fractions with significant antiviral activity. Further rounds of chromatographic purification and anti-HSV-2 testing allowed to purify the bioactive peptide. Mass spectrometry revealed the presence of a 36-mer derived from the C-terminal region of the hemoglobin β subunit. The purified and corresponding chemically synthesized peptide, termed HBB(112–147), inhibited HSV-2 infection in a dose-dependent manner, with a mean IC₅₀ in the median μg/ml range. Full-length hemoglobin tetramer had no antiviral activity. HBB(112–147) did not impair infectivity by direct targeting of the virions but prevented HSV-2 infection at the cell entry level. The peptide was inactive against Human Immunodeficiency Virus Type 1, Rubella and Zika virus infection, suggesting a specific anti-HSV-2 mechanism. Notably, HBB(112–147) has previously been identified as broad-spectrum antibacterial agent. It is abundant in placenta, reaching concentrations between 280 and 740 μg/ml, that are well sufficient to inhibit HSV-2 and prototype Gram-positive and -negative bacteria. We here additionally show, that HBB(112–147) also acts potently against Pseudomonas aeruginosa strains (including a multi-drug resistant strain) in a dose dependent manner, while full-length hemoglobin is inactive. Interestingly, the antibacterial activity of HBB(112–147) was increased under acidic conditions, a hallmark of infection and inflammatory conditions. Indeed, we found that HBB(112–147) is released from the hemoglobin precursor by Cathepsin D and Napsin A, acidic proteases highly expressed in placental and other tissues. We propose that upon viral or bacterial infection, the abundant hemoglobin precursor is proteolytically processed to release HBB(112–147), a broadly active antimicrobial innate immune defense peptide.

Adoption of a Turn Conformation Drives the Binding Affinity of p53 C-Terminal Domain Peptides to 14-3-3σ

The interaction between the adapter protein 14-3-3σ and transcription factor p53 is important for preserving the tumor-suppressor functions of p53 in the cell. A phosphorylated motif within the C-terminal domain (CTD) of p53 is key for binding to the amphipathic groove of 14-3-3. This motif is unique among 14-3-3 binding partners, and the precise dynamics of the interaction is not yet fully understood. Here, we investigate this interaction at the molecular level by analyzing the binding of different length p53 CTD peptides to 14-3-3σ using ITC, SPR, NMR, and MD simulations. We observed that the propensity of the p53 peptide to adopt turn-like conformation plays an important role in the binding to the 14-3-3σ protein. Our study contributes to elucidate the molecular mechanism of the 14-3-3-p53 binding and provides useful insight into how conformation properties of a ligand influence protein binding.

Multivalent Ligands with Tailor-Made Anion Binding Motif as Stabilizers of Protein-Protein Interactions

Modulation of protein-protein interactions (PPIs) is essential for understanding and tuning biologically relevant processes. Although inhibitors for PPIs are widely used, the field still lacks the targeted design of stabilizers. Here, we report unnatural stabilizers based on the combination of multivalency effects and the artificial building block guanidiniocarbonylpyrrol (GCP), an arginine mimetic. Unlike other GCP-based ligands that modulate PPIs in different protein targets, only a tetrameric design shows potent activity as stabilizer of the 14-3-3ζ/C-Raf and 14-3-3ζ/Tau complexes in the low-micromolar range. This evidences the role of multivalency for achieving higher specificity in the modulation of PPIs.

Control of TLR7-mediated type I IFN signaling in pDCs through CXCR4 engagement-A new target for lupus treatment

Type I interferons are highly potent cytokines essential for self-protection against tumors and infections. Deregulations of type I interferon signaling are associated with multiple diseases that require novel therapeutic options. Here, we identified the small molecule, IT1t, a previously described CXCR4 ligand, as a highly potent inhibitor of Toll-like receptor 7 (TLR7)-mediated inflammation. IT1t inhibits chemical (R848) and natural (HIV) TLR7-mediated inflammation in purified human plasmacytoid dendritic cells from blood and human tonsils. In a TLR7-dependent lupus-like model, in vivo treatment of mice with IT1t drives drastic reduction of both systemic inflammation and anti-double-stranded DNA autoantibodies and prevents glomerulonephritis. Furthermore, IT1t controls inflammation, including interferon α secretion, in resting and stimulated cells from patients with systemic lupus erythematosus. Our findings highlight a groundbreaking immunoregulatory property of CXCR4 signaling that opens new therapeutic perspectives in inflammatory settings and autoimmune diseases.

PPI-Detect: A support vector machine model for sequence-based prediction of protein-protein interactions

The prediction of peptide-protein or protein-protein interactions (PPI) is a challenging task, especially if amino acid sequences are the only information available. Machine learning methods allow us to exploit the information content in PPI datasets. However, the numerical codification of these datasets often influences the performance of data mining approaches. Here, we introduce a procedure for the general-purpose numerical codification of polypeptides. This procedure transforms pairs of amino acid sequences into a machine learning-friendly vector, whose elements represent numerical descriptors of residues in proteins. We used this numerical encoding procedure for the development of a support vector machine model (PPI-Detect), which allows predicting whether two proteins will interact or not. PPI-Detect (https://ppi-detect.zmb.uni-due.de/) outperforms state of the art sequence-based predictors of PPI. We employed PPI-Detect for the analysis of derivatives of EPI-X4, an endogenous peptide inhibitor of CXCR4, a G-protein-coupled receptor. There, we identified with high accuracy those peptides which bind better than EPI-X4 to the receptor. Also using PPI-Detect, we designed a novel peptide and then experimentally established its anti-CXCR4 activity. © 2019 Wiley Periodicals, Inc.

Mono- and Bivalent 14-3-3 Inhibitors for Characterizing Supramolecular "Lysine Wrapping" of Oligoethylene Glycol (OEG) Moieties in Proteins

Previous studies have indicated the presence of defined interactions between oligo or poly(ethylene glycol) (OEG or PEG) and lysine residues. In these interactions, the OEG or PEG residues "wrap around" the lysine amino group, thereby enabling complexation of the amino group by the ether oxygen residues. The resulting biochemical binding affinity and thus biological relevance of this supramolecular interaction however remains unclear so far. Here, we report that OEG-containing phosphophenol ether inhibitors of 14-3-3 proteins also display such a "lysine-wrapping" binding mode. For better investigating the biochemical relevance of this binding mode, we made use of the dimeric nature of 14-3-3 proteins and designed as well as synthesized a set of bivalent 14-3-3 inhibitors for biochemical and X-ray crystallography-based structural studies. We found that all synthesized derivatives adapted the "lysine-wrapping" binding mode in the crystal structures; in solution, a different binding mode is however observed, most probably as the "lysine-wrapping" binding mode turned out to be a rather weak interaction. Accordingly, our studies demonstrate that structural studies of OEG-lysine interactions are difficult to interpret and their presence in structural studies may not automatically be correlated with a relevant interaction also in solution but requires further biochemical studies.

Orthotropic Piezoelectricity in 2D Nanocellulose

The control of electromechanical responses within bonding regions is essential to face frontier challenges in nanotechnologies, such as molecular electronics and biotechnology. Here, we present Iβ-nanocellulose as a potentially new orthotropic 2D piezoelectric crystal. The predicted in-layer piezoelectricity is originated on a sui-generis hydrogen bonds pattern. Upon this fact and by using a combination of ab-initio and ad-hoc models, we introduce a description of electrical profiles along chemical bonds. Such developments lead to obtain a rationale for modelling the extended piezoelectric effect originated within bond scales. The order of magnitude estimated for the 2D Iβ-nanocellulose piezoelectric response, ~pm V-1, ranks this material at the level of currently used piezoelectric energy generators and new artificial 2D designs. Such finding would be crucial for developing alternative materials to drive emerging nanotechnologies.

ProtDCal: A program to compute general-purpose-numerical descriptors for sequences and 3D-structures of proteins

BACKGROUND

The exponential growth of protein structural and sequence databases is enabling multifaceted approaches to understanding the long sought sequence-structure-function relationship. Advances in computation now make it possible to apply well-established data mining and pattern recognition techniques to these data to learn models that effectively relate structure and function. However, extracting meaningful numerical descriptors of protein sequence and structure is a key issue that requires an efficient and widely available solution.

RESULTS

We here introduce ProtDCal, a new computational software suite capable of generating tens of thousands of features considering both sequence-based and 3D-structural descriptors. We demonstrate, by means of principle component analysis and Shannon entropy tests, how ProtDCal's sequence-based descriptors provide new and more relevant information not encoded by currently available servers for sequence-based protein feature generation. The wide diversity of the 3D-structure-based features generated by ProtDCal is shown to provide additional complementary information and effectively completes its general protein encoding capability. As demonstration of the utility of ProtDCal's features, prediction models of N-linked glycosylation sites are trained and evaluated. Classification performance compares favourably with that of contemporary predictors of N-linked glycosylation sites, in spite of not using domain-specific features as input information.

CONCLUSIONS

ProtDCal provides a friendly and cross-platform graphical user interface, developed in the Java programming language and is freely available at: http://bioinf.sce.carleton.ca/ProtDCal/ . ProtDCal introduces local and group-based encoding which enhances the diversity of the information captured by the computed features. Furthermore, we have shown that adding structure-based descriptors contributes non-redundant additional information to the features-based characterization of polypeptide systems. This software is intended to provide a useful tool for general-purpose encoding of protein sequences and structures for applications is protein classification, similarity analyses and function prediction.