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.

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.

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.

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.

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.

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.

High-resolution imaging of cellular dopamine efflux using a fluorescent nanosensor array.

Intercellular communication via chemical signaling proceeds with both spatial and temporal components, but analytical tools, such as microfabricated electrodes, have been limited to just a few probes per cell. In this work, we use a nonphotobleaching fluorescent nanosensor array based on single-walled carbon nanotubes (SWCNTs) rendered selective to dopamine to study its release from PC12 neuroprogenitor cells at a resolution exceeding 20,000 sensors per cell. This allows the spatial and temporal dynamics of dopamine release, following K+ stimulation, to be measured at exceedingly high resolution. We observe localized, unlabeled release sites of dopamine spanning 100 ms to seconds that correlate with protrusions but not predominately the positive curvature associated with the tips of cellular protrusions as intuitively expected. The results illustrate how directionality of chemical signaling is shaped by membrane morphology, and highlight the advantages of nanosensor arrays that can provide high spatial and temporal resolution of chemical signaling.

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.

Transition of Metastable Cross-α Crystals into Cross-ß Fibrils by ß-Turn Flipping.

The ensemble of native, folded state was once considered to represent the global energy minimum of a given protein sequence. More recently, the discovery of the cross-ß amyloid state revealed that deeper energy minima exist, often associated with pathogenic, fibrillar deposits, when the concentration of proteins reaches a critical value. Fortunately, a sizable energy barrier impedes the conversion from native to pathogenic states. However, little is known about the structure of the related transition state. In addition, there are indications of polymorphism in the amyloidogenic process. Here, we report the first evidence of the conversion of metastable cross-α-helical crystals to thermodynamically stable cross-ß-sheet-like fibrils by a de novo designed heptapeptide. Furthermore, for the first time, we demonstrate at atomic resolution that the flip of a peptide plane from a type I to a type II' turn facilitates transformation to cross-ß structure and assembly of a dry steric zipper. This study establishes the potential of a peptide turn, a common protein secondary structure, to serve as a principal gatekeeper between a native metastable folded state and the amyloid state.

Broad-spectrum non-toxic antiviral nanoparticles with a virucidal inhibition mechanism.

Viral infections kill millions yearly. Available antiviral drugs are virus-specific and active against a limited panel of human pathogens. There are broad-spectrum substances that prevent the first step of virus-cell interaction by mimicking heparan sulfate proteoglycans (HSPG), the highly conserved target of viral attachment ligands (VALs). The reversible binding mechanism prevents their use as a drug, because, upon dilution, the inhibition is lost. Known VALs are made of closely packed repeating units, but the aforementioned substances are able to bind only a few of them. We designed antiviral nanoparticles with long and flexible linkers mimicking HSPG, allowing for effective viral association with a binding that we simulate to be strong and multivalent to the VAL repeating units, generating forces (∼190 pN) that eventually lead to irreversible viral deformation. Virucidal assays, electron microscopy images, and molecular dynamics simulations support the proposed mechanism.  These particles show no cytotoxicity, and in vitro nanomolar irreversible activity against herpes simplex virus (HSV), human papilloma virus, respiratory syncytial virus (RSV), dengue and lenti virus. They are active ex vivo in human cervicovaginal histocultures infected by HSV-2 and in vivo in mice infected with RSV.

Computational studies of micellar and nanoparticle nanomedicines.

Nanomedicines are typically formed by nanocarriers which can deliver in a targeted manner drugs poorly soluble in blood, increase their therapeutic activities, and reduce their side effects. Many tested nanomedicines are formed by lipids, polymers, and other amphiphilic molecules isolated or self-assembled into various complexes and micelles, functionalized nanoparticles, and other bio-compatible composite materials. Here, we show how atomistic molecular dynamics simulations can be used to characterize and optimize the structure, stability, and activity of selected nanomedicines. We discuss modeling of nanomedicines based on micelles, which can deliver selected therapeutic agents, and nanoparticles designed to act like large drugs. We show how to model nanomedicines interacting with lipid membranes, viruses, and amyloid fibrils.

Ultralarge Modulation of Fluorescence by Neuromodulators in Carbon Nanotubes Functionalized with Self-Assembled Oligonucleotide Rings.

Noncovalent interactions between single-stranded DNA (ssDNA) oligonucleotides and single wall carbon nanotubes (SWNTs) have provided a unique class of tunable chemistries for a variety of applications. However, mechanistic insight into both the photophysical and intermolecular phenomena underlying their utility is lacking, which results in obligate heuristic approaches for producing ssDNA-SWNT based technologies. In this work, we present an ultrasensitive "turn-on" nanosensor for neuromodulators dopamine and norepinephrine with strong relative change in fluorescence intensity (Δ F/ F0) of up to 3500%, a signal appropriate for in vivo neuroimaging, and uncover the photophysical principles and intermolecular interactions that govern the molecular recognition and fluorescence modulation of this nanosensor synthesized from the spontaneous self-assembly of (GT)6 ssDNA rings on SWNTs. The fluorescence modulation of the ssDNA-SWNT conjugate is shown to exhibit remarkable sensitivity to the ssDNA sequence chemistry, length, and surface density, providing a set of parameters with which to tune nanosensor dynamic range, analyte selectivity and strength of fluorescence turn-on. We employ classical and quantum mechanical molecular dynamics simulations to rationalize our experimental findings. Calculations show that (GT)6 ssDNA form ordered rings around (9,4) SWNTs, inducing periodic surface potentials that modulate exciton recombination lifetimes. Further evidence is presented to elucidate how dopamine analyte binding modulates SWNT fluorescence. We discuss the implications of our findings for SWNT-based molecular imaging applications.

Dynamic profiling of double-stranded RNA binding proteins.

Double-stranded (ds) RNA is a key player in numerous biological activities in cells, including RNA interference, anti-viral immunity and mRNA transport. The class of proteins responsible for recognizing dsRNA is termed double-stranded RNA binding proteins (dsRBP). However, little is known about the molecular mechanisms underlying the interaction between dsRBPs and dsRNA. Here we examined four human dsRBPs, ADAD2, TRBP, Staufen 1 and ADAR1 on six dsRNA substrates that vary in length and secondary structure. We combined single molecule pull-down (SiMPull), single molecule protein-induced fluorescence enhancement (smPIFE) and molecular dynamics (MD) simulations to investigate the dsRNA-dsRBP interactions. Our results demonstrate that despite the highly conserved dsRNA binding domains, the dsRBPs exhibit diverse substrate specificities and dynamic properties when in contact with different RNA substrates. While TRBP and ADAR1 have a preference for binding simple duplex RNA, ADAD2 and Staufen1 display higher affinity to highly structured RNA substrates. Upon interaction with RNA substrates, TRBP and Staufen1 exhibit dynamic sliding whereas two deaminases ADAR1 and ADAD2 mostly remain immobile when bound. MD simulations provide a detailed atomic interaction map that is largely consistent with the affinity differences observed experimentally. Collectively, our study highlights the diverse nature of substrate specificity and mobility exhibited by dsRBPs that may be critical for their cellular function.

Molecular Mechanism of Processive 3' to 5' RNA Translocation in the Active Subunit of the RNA Exosome Complex.

Recent experimental studies revealed structural details of 3' to 5' degradation of RNA molecules, performed by the exosome complex. ssRNA is channeled through its multisubunit ring-like core into the active site tunnel of its key exonuclease subunit Rrp44, which acts both as an enzyme and a motor. Even in isolation, Rrp44 can pull and sequentially cleave RNA nucleotides, one at a time, without any external energy input and release a final 3-5 nucleotide long product. Using molecular dynamics simulations, we identify the main factors that control these processes. Our free energy calculations reveal that RNA transfer from solution into the active site of Rrp44 is highly favorable, but dependent on the length of the RNA strand. While RNA strands formed by 5 nucleotides or more correspond to a decreasing free energy along the translocation coordinate toward the cleavage site, a 4-nucleotide RNA experiences a free energy barrier along the same direction, potentially leading to incomplete cleavage of ssRNA and the release of short (3-5) nucleotide products. We provide new insight into how Rrp44 catalyzes a localized enzymatic reaction and performs an action distributed over several RNA nucleotides, leading eventually to the translocation of whole RNA segments into the position suitable for cleavage.

Substrate recognition and specificity of double-stranded RNA binding proteins.

Recognition of double-stranded (ds) RNA is an important part of many cellular pathways, including RNA silencing, viral recognition, RNA editing, processing, and transport. dsRNA recognition is often achieved by dsRNA binding domains (dsRBDs). We use atomistic molecular dynamics simulations to examine the binding interface of the transactivation response RNA binding protein (TRBP) dsRBDs to dsRNA substrates. Our results explain the exclusive selectivity of dsRBDs toward dsRNA and against DNA-RNA hybrid and dsDNA duplexes. We also provide corresponding experimental evidence. The dsRNA duplex is recognized by dsRBDs through the A-form of three duplex grooves and by the chemical properties of RNA bases, which have 2'-hydroxyl groups on their sugar rings. Our simulations show that TRBP dsRBD discriminates dsRNA- from DNA-containing duplexes primarily through interactions at two duplex grooves. The simulations also reveal that the conformation of the DNA-RNA duplex can be altered by dsRBD proteins, resulting in a weak binding of dsRBDs to DNA-RNA hybrids. Our study reveals the structural and molecular basis of protein-RNA interaction that gives rise to the observed substrate specificity of dsRNA binding proteins.

Poly(oligonucleotide).

Here we report the preparation of poly(oligonucleotide) brush polymers and amphiphilic brush copolymers from nucleic acid monomers via graft-through polymerization. We describe the polymerization of PNA-norbornyl monomers to yield poly-PNA (poly(peptide nucleic acid)) via ring-opening metathesis polymerization (ROMP) with the initiator, (IMesH2)(C5H5N)2(Cl)2RuCHPh.1 In addition, we present the preparation of poly-PNA nanoparticles from amphiphilic block copolymers and describe their hybridization to a complementary single-stranded DNA (ssDNA) oligonucleotide.

Consensus statement on screening, diagnosis, classification and treatment of endemic (Balkan) nephropathy.

Currently used diagnostic criteria in different endemic (Balkan) nephropathy (EN) centers involve different combinations of parameters, various cut-off values and many of them are not in agreement with proposed international guidelines. Leaders of EN centers began to address these problems at scientific meetings, and this paper is the outgrowth of those discussions. The main aim is to provide recommendations for clinical work on current knowledge and expertise. This document is developed for use by general physicians, nephrologists, urologist, public health experts and epidemiologist, and it is hoped that it will be adopted by responsible institutions in countries harboring EN. National medical providers should cover costs of screening and diagnostic procedures and treatment of EN patients with or without upper urothelial cancers.

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.

Fluorescence changes in carbon nanotube sensors correlate with THz absorption of hydration.

Single wall carbon nanotubes (SWCNTs) functionalized with (bio-)polymers such as DNA are soluble in water and sense analytes by analyte-specific changes of their intrinsic fluorescence. Such SWCNT-based (bio-)sensors translate the binding of a molecule (molecular recognition) into a measurable optical signal. This signal transduction is crucial for all types of molecular sensors to achieve high sensitivities. Although there is an increasing number of SWCNT-based sensors, there is yet no molecular understanding of the observed changes in the SWCNT's fluorescence. Here, we report THz experiments that map changes in the local hydration of the solvated SWCNT upon binding of analytes such as the neurotransmitter dopamine or the vitamin riboflavin. The THz amplitude signal serves as a measure of the coupling of charge fluctuations in the SWCNTs to the charge density fluctuations in the hydration layer. We find a linear (inverse) correlation between changes in THz amplitude and the intensity of the change in fluorescence induced by the analytes. Simulations show that the organic corona shapes the local water, which determines the exciton dynamics. Thus, THz signals are a quantitative predictor for signal transduction strength and can be used as a guiding chemical design principle for optimizing fluorescent biosensors.

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.