Interfacial Interactions between Nanoplastics and Biological Systems: toward an Atomic and Molecular Understanding of Plastics-Driven Biological Dyshomeostasis.

Micro- and nano-plastics (NPs) are found in human milk, blood, tissues, and organs and associate with aberrant health outcomes including inflammation, genotoxicity, developmental disorders, onset of chronic diseases, and autoimmune disorders. Yet, interfacial interactions between plastics and biomolecular systems remain underexplored. Here, we have examined experimentally, in vitro, in vivo, and by computation, the impact of polystyrene (PS) NPs on a host of biomolecular systems and assemblies. Our results reveal that PS NPs essentially abolished the helix-content of the milk protein ß-lactoglobulin (BLG) in a dose-dependent manner. Helix loss is corelated with the near stoichiometric formation of ß-sheet elements in the protein. Structural alterations in BLG are also likely responsible for the nanoparticle-dependent attrition in binding affinity and weaker on-rate constant of retinol, its physiological ligand (compromising its nutritional role). PS NP-driven helix-to-sheet conversion was also observed in the amyloid-forming trajectory of hen egg-white lysozyme (accelerated fibril formation and reduced helical content in fibrils). Caenorhabditis elegans exposed to PS NPs exhibited a decrease in the fluorescence of green fluorescent protein-tagged dopaminergic neurons and locomotory deficits (akin to the neurotoxin paraquat exposure). Finally, in silico analyses revealed that the most favorable PS/BLG docking score and binding energies corresponded to a pose near the hydrophobic ligand binding pocket (calyx) of the protein where the NP fragment was found to make nonpolar contacts with side-chain residues via the hydrophobic effect and van der Waals forces, compromising side chain/retinol contacts. Binding energetics indicate that PS/BLG interactions destabilize the binding of retinol to the protein and can potentially displace retinol from the calyx region of BLG, thereby impairing its biological function. Collectively, the experimental and high-resolution in silico data provide new insights into the mechanism(s) by which PS NPs corrupt the bimolecular structure and function, induce amyloidosis and onset neuronal injury, and drive aberrant physiological and behavioral outcomes.

Predicting Serotonin Detection with DNA-Carbon Nanotube Sensors across Multiple Spectral Wavelengths.

Owing to the value of DNA-wrapped single-walled carbon nanotube (SWNT)-based sensors for chemically specific imaging in biology, we explore machine learning (ML) predictions DNA-SWNT serotonin sensor responsivity as a function of DNA sequence based on the whole SWNT fluorescence spectra. Our analysis reveals the crucial role of DNA sequence in the binding modes of DNA-SWNTs to serotonin, with a smaller influence of SWNT chirality. Regression ML models trained on existing data sets predict the change in the fluorescence emission in response to serotonin, ΔF/F, at over a hundred wavelengths for new DNA-SWNT conjugates, successfully identifying some high- and low-response DNA sequences. Despite successful predictions, we also show that the finite size of the training data set leads to limitations on prediction accuracy. Nevertheless, incorporating entire spectra into ML models enhances prediction robustness and facilitates the discovery of novel DNA-SWNT sensors. Our approaches show promise for identifying new chemical systems with specific sensing response characteristics, marking a valuable advancement in DNA-based system discovery.

An Atomic and Molecular Insight into How PFOA Reduces α-Helicity, Compromises Substrate Binding, and Creates Binding Pockets in a Model Globular Protein.

Per- and polyfluoroalkyl substances (PFAS) pose significant health risks due to their widespread presence in various environmental and biological matrices. However, the molecular-level mechanisms underlying the interactions between PFAS and biological constituents, including proteins, carbohydrates, lipids, and DNA, remain poorly understood. Here, we investigate the interactions between a legacy PFAS, viz. perfluorooctanoic acid (PFOA), and the milk protein ß-lactoglobulin (BLG) obtained using a combination of experimental and computational techniques. Circular dichroism studies reveal that PFOA perturbs the secondary structure of BLG, by driving a dose-dependent loss of α-helicity and alterations in its ß-sheet content. Furthermore, exposure of the protein to PFOA attenuates the on-rate constant for the binding of the hydrophobic probe 8-anilino-1-naphthalene sulfonic acid (ANS), suggesting potential functional impairment of BLG by PFOA. Steered molecular dynamics and umbrella sampling calculations reveal that PFOA binding leads to the formation of an energetically favorable novel binding pocket within the protein, when residues 129-142 are steered to unfold from their initial α-helical structure, wherein a host of intermolecular interactions between PFOA and BLG's residues serve to insert the PFOA into the region between the unfolded helix and beta-sheets. Together, the data provide a novel understanding of the atomic and molecular mechanism(s) by which PFAS modulates structure and function in a globular protein, leading to a beginning of our understanding of altered biological outcomes.

Directed Evolution of Near-Infrared Serotonin Nanosensors with Machine Learning-Based Screening.

In this study, we employed a novel approach to improve the serotonin-responsive ssDNA-wrapped single-walled carbon nanotube (ssDNA-SWCNT) nanosensors, combining directed evolution and machine learning-based prediction. Our iterative optimization process is aimed at the sensitivity and selectivity of ssDNA-SWCNT nanosensors. In the three rounds for higher serotonin sensitivity, we substantially improved sensitivity, achieving a remarkable 2.5-fold enhancement in fluorescence response compared to the original sequence. Following this, we directed our efforts towards selectivity for serotonin over dopamine in the two rounds. Despite the structural similarity between these neurotransmitters, we achieved a 1.6-fold increase in selectivity. This innovative methodology, offering high-throughput screening of mutated sequences, marks a significant advancement in biosensor development. The top-performing nanosensors, N2-1 (sensitivity) and L1-14 (selectivity) present promising reference sequences for future studies involving serotonin detection.

Fusion Position-Dependent Aromatic Transitions of Ligand Backbone Rings for Controlling the Redox Energetics of Photoredox Catalysts.

To reveal, quantify, and rationalize the effect of backbone π-extension on ligand redox activity, we studied the ground- and excited-state reduction potentials of eight ruthenium photoredox catalysts with the formula Ru(ppy)2L (L is the redox-active ligand of the bipyridine family) using density functional theory. Our research underlines the profound importance of the fusion position of backbone aromatic C6 rings on the redox activity of ligands in transition metal photoredox catalysts. Namely, certain fusion positions lead to the dearomatization of C6 rings in ligand-centered electron transfer events, resulting in a thermodynamic penalty equivalent to a half-volt negative shift in the reduction potential. Contrarily, the extent of backbone delocalization shows a minimal impact on redox energetics, which can be explained by the charge concentration at the nitrogen contact atoms in ligand-centered reductions. Grounded in Caulton's conceptual framework, we reaffirm the predictive potency of Lewis structures in ligand-centered redox energetics with qualitative and quantitative data. Our hypothesis regarding the effect of backbone ring dearomatization on redox energetics is further corroborated using magnetic and structure-based aromaticity indicators. Highlighting fusion-dependent dearomatization as a determining factor of ligand-centered electron transfer energetics, our findings hold implications for molecular-level design in advanced electroactive materials and catalysts.

Triepoxide formation by a flavin-dependent monooxygenase in monensin biosynthesis.

Monensin A is a prototypical natural polyether polyketide antibiotic. It acts by binding a metal cation and facilitating its transport across the cell membrane. Biosynthesis of monensin A involves construction of a polyene polyketide backbone, subsequent epoxidation of the alkenes, and, lastly, formation of cyclic ethers via epoxide-opening cyclization. MonCI, a flavin-dependent monooxygenase, is thought to transform all three alkenes in the intermediate polyketide premonensin A into epoxides. Our crystallographic study has revealed that MonCI's exquisite stereocontrol is due to the preorganization of the active site residues which allows only one specific face of the alkene to approach the reactive C(4a)-hydroperoxyflavin moiety. Furthermore, MonCI has an unusually large substrate-binding cavity that can accommodate premonensin A in an extended or folded conformation which allows any of the three alkenes to be placed next to C(4a)-hydroperoxyflavin. MonCI, with its ability to perform multiple epoxidations on the same substrate in a stereospecific manner, demonstrates the extraordinary versatility of the flavin-dependent monooxygenase family of enzymes.

Genetically encoded discovery of perfluoroaryl macrocycles that bind to albumin and exhibit extended circulation in vivo.

Peptide-based therapeutics have gained attention as promising therapeutic modalities, however, their prevalent drawback is poor circulation half-life in vivo. In this paper, we report the selection of albumin-binding macrocyclic peptides from genetically encoded libraries of peptides modified by perfluoroaryl-cysteine SNAr chemistry, with decafluoro-diphenylsulfone (DFS). Testing of the binding of the selected peptides to albumin identified SICRFFC as the lead sequence. We replaced DFS with isosteric pentafluorophenyl sulfide (PFS) and the PFS-SICRFFCGG exhibited KD = 4-6 µM towards human serum albumin. When injected in mice, the concentration of the PFS-SICRFFCGG in plasma was indistinguishable from the reference peptide, SA-21. More importantly, a conjugate of PFS-SICRFFCGG and peptide apelin-17 analogue (N3-PEG6-NMe17A2) showed retention in circulation similar to SA-21; in contrast, apelin-17 analogue was cleared from the circulation after 2 min. The PFS-SICRFFC is the smallest known peptide macrocycle with a significant affinity for human albumin and substantial in vivo circulation half-life. It is a productive starting point for future development of compact macrocycles with extended half-life in vivo.

Characterizing the Interactions of Cell-Membrane-Disrupting Peptides with Lipid-Functionalized Single-Walled Carbon Nanotubes.

Lipid-functionalized single-walled carbon nanotubes (SWNTs) have garnered significant interest for their potential use in a wide range of biomedical applications. In this work, we used molecular dynamics simulations to study the equilibrium properties of SWNTs surrounded by the phosphatidylcholine (POPC) corona phase and their interactions with three cell membrane disruptor peptides: colistin, TAT peptide, and crotamine-derived peptide. Our results show that SWNTs favor asymmetrical positioning within the POPC corona, so that one side of the SWNT, covered by the thinnest part of the corona, comes in contact with charged and polar functional groups of POPC and water. We also observed that colistin and TAT insert deeply into the POPC corona, while crotamine-derived peptide only adsorbs to the corona surface. In separate simulations, we show that three examined peptides exhibit similar insertion and adsorption behaviors when interacting with POPC bilayers, confirming that peptide-induced perturbations to POPC in conjugates and bilayers are similar in nature and magnitude. Furthermore, we observed correlations between the peptide-induced structural perturbations and the near-infrared emission of the lipid-functionalized SWNTs, which suggest that the optical signal of the conjugates transduces the morphological changes in the lipid corona. Overall, our findings indicate that lipid-functionalized SWNTs could serve as simplified cell membrane model systems for prescreening of new antimicrobial compounds that disrupt cell membranes.

BinderSpace: A package for sequence space analyses for datasets of affinity-selected oligonucleotides and peptide-based molecules.

Discovery of target-binding molecules, such as aptamers and peptides, is usually performed with the use of high-throughput experimental screening methods. These methods typically generate large datasets of sequences of target-binding molecules, which can be enriched with high affinity binders. However, the identification of the highest affinity binders from these large datasets often requires additional low-throughput experiments or other approaches. Bioinformatics-based analyses could be helpful to better understand these large datasets and identify the parts of the sequence space enriched with high affinity binders. BinderSpace is an open-source Python package that performs motif analysis, sequence space visualization, clustering analyses, and sequence extraction from clusters of interest. The motif analysis, resulting in text-based and visual output of motifs, can also provide heat maps of previously measured user-defined functional properties for all the motif-containing molecules. Users can also run principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) analyses on whole datasets and on motif-related subsets of the data. Functionally important sequences can also be highlighted in the resulting PCA and t-SNE maps. If points (sequences) in two-dimensional maps in PCA or t-SNE space form clusters, users can perform clustering analyses on their data, and extract sequences from clusters of interest. We demonstrate the use of BinderSpace on a dataset of oligonucleotides binding to single-wall carbon nanotubes in the presence and absence of a bioanalyte, and on a dataset of cyclic peptidomimetics binding to bovine carbonic anhydrase protein. BinderSpace is openly accessible to the public via the GitHub website: https://github.com/vukoviclab/BinderSpace.

Mechanistic Understanding of DNA Denaturation in Nanoscale Thermal Gradients Created by Femtosecond Excitation of Gold Nanoparticles.

There is significant interest in developing photothermal systems that can precisely control the structure and function of biomolecules through local temperature modulation. One specific application is the denaturation of double-stranded (ds) DNA through femtosecond (fs) laser pulse optical heating of gold nanoparticles (AuNPs); however, the mechanism of DNA melting in these systems is not fully understood. Here, we utilize 55 nm AuNPs with surface-tethered dsDNA, which are locally heated using fs laser pulses to induce DNA melting. By varying the dsDNA distance from the AuNP surface and the laser pulse energy fluence, this system is used to study how the nanosecond duration temperature increase and the steep temperature gradient around the AuNP affect dsDNA dehybridization. Through modifying the distance between the dsDNA and AuNP surface by 3.8 nm in total and the pulse energy fluence from 7.1 to 14.1 J/m2, the dehybridization rates ranged from 0.002 to 0.05 DNA per pulse, and the total amount of DNA released into solution was controlled over a range of 26-93% in only 100 s of irradiation. By shifting the dsDNA position as little as ∼1.1 nm, the average dsDNA dehybridization rate is altered up to 30 ± 2%, providing a high level of control over DNA melting and release. By comparing the theoretical temperature around the dsDNA to the experimentally derived temperature, we find that maximum or peak temperatures have a greater influence on the dehybridization rate when the dsDNA is closer to the AuNP surface and when lower laser pulse fluences are used. Furthermore, molecular dynamics simulations mimicking the photothermal heat pulse around a AuNP provide mechanistic insight into the stochastic nature of dehybridization and demonstrate increased base pair separation near the AuNP surface during laser pulse heating when compared to steady-state heating. Understanding how biological materials respond to the short-lived and non-uniform temperature increases innate to fs laser pulse optical heating of AuNPs is critical to improving the functionality and precision of this technique so that it may be implemented into more complex biological systems.

Discovery of DNA-Carbon Nanotube Sensors for Serotonin with Machine Learning and Near-infrared Fluorescence Spectroscopy.

DNA-wrapped single walled carbon nanotube (SWNT) conjugates have distinct optical properties leading to their use in biosensing and imaging applications. A critical limitation in the development of DNA-SWNT sensors is the current inability to predict unique DNA sequences that confer a strong analyte-specific optical response to these sensors. Here, near-infrared (nIR) fluorescence response data sets for ∼100 DNA-SWNT conjugates, narrowed down by a selective evolution protocol starting from a pool of ∼1010 unique DNA-SWNT candidates, are used to train machine learning (ML) models to predict DNA sequences with strong optical response to neurotransmitter serotonin. First, classifier models based on convolutional neural networks (CNN) are trained on sequence features to classify DNA ligands as either high response or low response to serotonin. Second, support vector machine (SVM) regression models are trained to predict relative optical response values for DNA sequences. Finally, we demonstrate with validation experiments that integrating the predictions of ensembles of the highest quality neural network classifiers (convolutional or artificial) and SVM regression models leads to the best predictions of both high and low response sequences. With our ML approaches, we discovered five DNA-SWNT sensors with higher fluorescence intensity response to serotonin than obtained previously. Overall, the explored ML approaches, shown to predict useful DNA sequences, can be used for discovery of DNA-based sensors and nanobiotechnologies.

Computational Modeling of the Virucidal Inhibition Mechanism for Broad-Spectrum Antiviral Nanoparticles and HPV16 Capsid Segments.

Solid core nanoparticles (NPs) coated with sulfonated ligands that mimic heparan sulfate proteoglycans (HSPGs) can exhibit virucidal activity against many viruses that utilize HSPG interactions with host cells for the initial stages of infection. How the interactions of these NPs with large capsid segments of HSPG-interacting viruses lead to their virucidal activity has been unclear. Here, we describe the interactions between sulfonated NPs and segments of the human papilloma virus type 16 (HPV16) capsids using atomistic molecular dynamics simulations. The simulations demonstrate that the NPs primarily bind at the interfaces of two HPV16 capsid proteins. After equilibration, the distances and angles between capsid proteins in the capsid segments are larger for the systems in which the NPs bind at the interfaces of capsid proteins. Over time, NP binding can lead to breaking of contacts between two neighboring proteins. The revealed mechanism of NPs targeting the interfaces between pairs of capsid proteins can be utilized for designing new generations of virucidal materials and contribute to the development of new broad-spectrum non-toxic virucidal materials.

Photochemical control of bacterial gene expression based on trans encoded genetic switches.

Controlling gene expression by light with fine spatiotemporal resolution not only allows understanding and manipulating fundamental biological processes but also fuels the development of novel therapeutic strategies. In complement to exploiting optogenetic tools, photochemical strategies mostly rely on the incorporation of photo-responsive small molecules into the corresponding biomacromolecular scaffolds. Therefore, generally large synthetic effort is required and the switching of gene expression in both directions within a single system remains a challenge. Here, we report a trans encoded ribo-switch, which consists of an engineered tRNA mimicking structure (TMS), under control of small photo-switchable signalling molecules. The signalling molecules consist of two amino glycoside molecules that are connected via an azobenzene unit. The light responsiveness of our system originates from the photo-switchable noncovalent interactions between the signalling molecule and the TMS switch, leading to the demonstration of photochemically controlled expression of two different genes. We believe that this modular design will provide a powerful platform for controlling the expression of other functional proteins with high spatiotemporal resolution employing light as a stimulus.

Genetically Encoded Fragment-Based Discovery from Phage-Displayed Macrocyclic Libraries with Genetically Encoded Unnatural Pharmacophores.

Genetically encoded macrocyclic peptide libraries with unnatural pharmacophores are valuable sources for the discovery of ligands for many targets of interest. Traditionally, generation of such libraries employs "early stage" incorporation of unnatural building blocks into the chemically or translationally produced macrocycles. Here, we describe a divergent late-stage approach to such libraries starting from readily available starting material: genetically encoded libraries of peptides. A diketone linchpin 1,5-dichloropentane-2,4-dione converts peptide libraries displayed on phage to 1,3-diketone bearing macrocyclic peptides (DKMP): shelf-stable precursors for Knorr pyrazole synthesis. Ligation of diverse hydrazine derivatives onto DKMP libraries displayed on phage that carries silent DNA-barcodes yields macrocyclic libraries in which the amino acid sequence and the pharmacophore are encoded by DNA. Selection of this library against carbonic anhydrase enriched macrocycles with benzenesulfonamide pharmacophore and nanomolar Kd. The methodology described in this manuscript can graft diverse pharmacophores into many existing genetically encoded phage libraries and significantly increase the value of such libraries in molecular discoveries.

Adaptive Evolution of Peptide Inhibitors for Mutating SARS-CoV-2.

The SARS-CoV-2 virus is currently causing a worldwide pandemic with dramatic societal consequences for the humankind. In the past decades, disease outbreaks due to such zoonotic pathogens have appeared with an accelerated rate, which calls for an urgent development of adaptive (smart) therapeutics. Here, a computational strategy is developed to adaptively evolve peptides that could selectively inhibit mutating S protein receptor binding domains (RBDs) of different SARS-CoV-2 viral strains from binding to their human host receptor, angiotensin-converting enzyme 2 (ACE2). Starting from suitable peptide templates, based on selected ACE2 segments (natural RBD binder), the templates are gradually modified by random mutations, while retaining those mutations that maximize their RBD-binding free energies. In this adaptive evolution, atomistic molecular dynamics simulations of the template-RBD complexes are iteratively perturbed by the peptide mutations, which are retained under favorable Monte Carlo decisions. The computational search will provide libraries of optimized therapeutics capable of reducing the SARS-CoV-2 infection on a global scale.

Surfactant-Controlled Mobility of Oil Droplets in Mineral Nanopores.

Polymer flooding is one of the widely used enhanced oil recovery (EOR) methods. However, tuning polymer properties to achieve improved performance in porous mineral rocks of diverse oil reservoirs remains one of the challenges of EOR processes. Here, we use molecular dynamics (MD) simulations to examine decane/water mixtures with surfactant additives in calcite and kaolinite mineral nanopores and characterize surfactant properties associated with increased fluid mobility and improved wettability in planar and constricted nanopore geometries. Cetyltrimethylammonium chloride (CTAC) and sodium dodecyl sulfate (SDS) surfactants are found to modulate the contact angles of decane droplets and reduce the decane density on mineral surfaces. CTAC can enhance and unblock the flow of decane droplets through narrowing nanopores with constricted geometries while aiding in decane droplet shape deformation, whereas SDS leads to decane droplets stalling in front of constrictions in nanopores. We hypothesize that the inability of the cationic CTAC headgroup to form hydrogen bonds is one of the key factors leading to enhanced CTAC-coated decane flow through constricted nanopores. The obtained molecular view of equilibrium and dynamic properties of complex fluids typical of oil reservoirs can provide a basis for the future design of new molecules for EOR processes.

Adaptive Evolution of Peptide Inhibitors for Mutating SARS-CoV-2.

The SARS-CoV-2 virus is currently causing a worldwide pandemic with dramatic societal consequences for the humankind. In the last decades, disease outbreaks due to such zoonotic pathogens have appeared with an accelerated rate, which calls for an urgent development of
adaptive (smart) therapeutics. Here, we develop a computational strategy to adaptively evolve peptides that could selectively inhibit mutating S protein receptor binding domains (RBDs) of different SARS-CoV-2 viral strains from binding to their human host receptor, angiotensin-converting enzyme 2 (ACE2). Starting from suitable peptide templates, based on selected ACE2 segments (natural RBD binder), we gradually modify the templates by random mutations, while retaining those mutations that maximize their RBD-binding free energies. In this adaptive evolution, atomistic molecular dynamics simulations of the template-RBD complexes are iteratively perturbed by the peptide mutations, which are retained under favorable Monte Carlo decisions. The computational search will provide libraries
of optimized therapeutics capable of reducing the SARS-CoV-2 infection on a global scale.
.

Modified cyclodextrins as broad-spectrum antivirals.

Viral infections kill millions of people and new antivirals are needed. Nontoxic drugs that irreversibly inhibit viruses (virucidal) are postulated to be ideal. Unfortunately, all virucidal molecules described to date are cytotoxic. We recently developed nontoxic, broad-spectrum virucidal gold nanoparticles. Here, we develop further the concept and describe cyclodextrins, modified with mercaptoundecane sulfonic acids, to mimic heparan sulfates and to provide the key nontoxic virucidal action. We show that the resulting macromolecules are broad-spectrum, biocompatible, and virucidal at micromolar concentrations in vitro against many viruses [including herpes simplex virus (HSV), respiratory syncytial virus (RSV), dengue virus, and Zika virus]. They are effective ex vivo against both laboratory and clinical strains of RSV and HSV-2 in respiratory and vaginal tissue culture models, respectively. Additionally, they are effective when administrated in mice before intravaginal HSV-2 inoculation. Lastly, they pass a mutation resistance test that the currently available anti-HSV drug (acyclovir) fails.

Collecting duct carcinoma and endemic nephropathy - case reportS and literature review.

Although collecting duct carcinoma is a subtype of renal cell carcinoma, several studies implicate association with urothelial carcinoma. The coexistence of collecting duct carcinoma and another renal neoplasm is rare. Endemic nephropathy is a renal disease causing chronic renal failure. It is highly associated with urothelial neoplasm and occurs in endemic villages in Bosnia, Croatia, Bulgaria, Romania and Serbia. Recent studies have confirmed the important role of exposure to aristolochic acid as an etiologic factor. We present three cases of collecting duct carcinoma with literature overview. In one case, we describe collecting duct carcinoma with metachronous urothelial carcinoma of the pyelon and urinary bladder in an endemic nephropathy patient. To our knowledge, this is the first case report describing this coexistence. Certain similarities between collecting duct carcinoma and urothelial carcinoma were found, e.g., higher incidence in female compared to male, higher mean age, and multifocal and multicentric occurrence of the tumor. Our observations support the hypothesis that collecting duct carcinoma and urothelial carcinoma could be connected.