Investigation of the Effect of Peptide p5 Targeting CDK5-p25 Hyperactivity on Munc18-1 (P67) Regulating Neuronal Exocytosis Using Molecular Simulations.

Munc18-1 is an SM (sec1/munc-like) family protein involved in vesicle fusion and neuronal exocytosis. Munc18-1 is known to regulate the exocytosis process by binding with closed- and open-state conformations of Syntaxin1, a protein belonging to the SNARE family established to be central to the exocytosis process. Our previous work studied peptide p5 as a promising drug candidate for CDK5-p25 complex, an Alzheimer's disease (AD) pathological target. Experimental in vivo and in vitro studies suggest that Munc18-1 promotes p5 to selectively inhibit the CDK5-p25 complex without affecting the endogenous CDK5 activity, a characteristic of remarkable therapeutic implications. In this paper, we identify several binding modes of p5 with Munc18-1 that could potentially affect the Munc18-1 binding with SNARE proteins and lead to off-target effects on neuronal communication using molecular dynamics simulations. Recent studies indicate that disruption of Munc18-1 function not only disrupts neurotransmitter release but also results in neurodegeneration, exhibiting clinical resemblance to other neurodegenerative conditions such as AD, causing diagnostic and treatment challenges. We characterize such interactions between p5 and Munc18-1, define the corresponding pharmacophores, and provide guidance for the in vitro validation of our findings to improve therapeutic efficacy and safety of p5.

Functional Organic Materials for Photovoltaics: The Synthesis as a Tool for Managing Properties for Solid State Applications.

The continuous increase in the global energy demand deeply impacts the environment. Consequently, the research is moving towards more sustainable forms of energy production, storage and saving. Suitable technologies and materials are fundamental to win the challenge towards a greener and more eco-friendly society. Organic π-conjugated materials, including small molecules, oligomers and polymers are a wide and versatile class of functional materials with great potentiality, as they can be used as active matrixes in the fabrication of lightweight, flexible, cheap and large area devices. Their chemical and physical properties, both at a molecular level and mainly in the solid state, are a result of many factors, strictly related to the conjugated structure and functional groups on the backbone, which control the intermolecular forces driving solid state aggregations. The synthesis, through the molecular design, the choice of conjugated backbone and functionalization, represents the first and most powerful tool for finely tuning the chemico-physical properties of organic materials tailored for specific applications. In the present review, we report an overview of our works focused on synthetic methodologies, characterization, structure-properties correlation studies and applications of organic materials designed for energy-involving solid-state applications, organic photovoltaics in particular. The impact of functionalization on electro-optical properties and performance in device are discussed, also in relation to the specific applications.

Computational Study of the Allosteric Effects of p5 on CDK5-p25 Hyperactivity as Alternative Inhibitory Mechanisms in Neurodegeneration.

The cyclin-dependent kinase (CDK5) forms a stable complex with its activator p25, leading to the hyperphosphorylation of tau proteins and to the formation of plaques and tangles that are considered to be one of the typical causes of Alzheimer's disease (AD). Hence, the pathological CDK5-p25 complex is a promising therapeutic target for AD. Small peptides, obtained from the truncation of CDK5 physiological activator p35, have shown promise in inhibiting the pathological complex effectively while also crossing the blood-brain barrier. One such small 24-residue peptide, p5, has shown selective inhibition toward the pathological complex in vivo. Our previous research focused on the characterization of a computationally predicted CDK5-p5 binding mode and of its pharmacophore, which was consistent with competitive inhibition. In continuation of our previous work, herein, we investigate four additional binding modes to explore other possible mechanisms of interaction between CDK5 and p5. The quantitative description of the pharmacophore is consistent with both competitive and allosteric p5-induced inhibition mechanisms of CDK5-p25 pathology. The gained insights can direct further in vivo/in vitro tests and help design small peptides, linear or cyclic, or peptidomimetic compounds as adjuvants of orthosteric inhibitors or as part of a cocktail of drugs with enhanced effectiveness and lower side effects.

Synthesis and Investigation of Electro-Optical Properties of H-Shape Dibenzofulvene Derivatives.

We have synthetized two classes of dibenzofulvene-arylamino derivatives with an H-shape design, for a total of six different molecules. The molecular structures consist of two D-A-D units connected by a thiophene or bitiophene bridge, using diarylamino substituents as donor groups anchored to the 2,7- (Group A) and 3,6- (Group B) positions of the dibenzofulvene backbone. The donor units and the thiophene or bithiophene bridges were used as chemico-structural tools to modulate electro-optical and morphological-electrical properties. A combination of experiments, such as absorption measurements (UV-Vis spectroscopy), cyclic voltammetry, ellipsometry, Raman, atomic force microscopy, TD-DFT calculation and hole-mobility measurements, were carried out on the synthesized small organic molecules to investigate the differences between the two classes and therefore understand the relevance of the molecular design of the various properties. We found that the anchoring position on dibenzofulvene plays a crucial key for fine-tuning the optical, structural, and morphological properties of molecules. In particular, molecules with substituents in 2,7 positions (Group A) showed a lower structural disorder, a larger molecular planarity, and a lower roughness.

A Convolutional Neural Networks-Based Approach for Texture Directionality Detection.

The perceived texture directionality is an important, not fully explored image characteristic. In many applications texture directionality detection is of fundamental importance. Several approaches have been proposed, such as the fast Fourier-based method. We recently proposed a method based on the interpolated grey-level co-occurrence matrix (iGLCM), robust to image blur and noise but slower than the Fourier-based method. Here we test the applicability of convolutional neural networks (CNNs) to texture directionality detection. To obtain the large amount of training data required, we built a training dataset consisting of synthetic textures with known directionality and varying perturbation levels. Subsequently, we defined and tested shallow and deep CNN architectures. We present the test results focusing on the CNN architectures and their robustness with respect to image perturbations. We identify the best performing CNN architecture, and compare it with the iGLCM, the Fourier and the local gradient orientation methods. We find that the accuracy of CNN is lower, yet comparable to the iGLCM, and it outperforms the other two methods. As expected, the CNN method shows the highest computing speed. Finally, we demonstrate the best performing CNN on real-life images. Visual analysis suggests that the learned patterns generalize to real-life image data. Hence, CNNs represent a promising approach for texture directionality detection, warranting further investigation.

Lipid-Based Nanovesicles for Simultaneous Intracellular Delivery of Hydrophobic, Hydrophilic, and Amphiphilic Species.

Lipid nanovesicles (NVs) are the first nanoformulation that entered the clinical use in oncology for the treatment of solid tumors. They are indeed versatile systems which can be loaded with either hydrophobic or hydrophilic molecules, for both imaging and drug delivery, and with high biocompatibility, and limited immunogenicity. In the present work, NVs with a lipid composition resembling that of natural vesicles were prepared using the ultrasonication method. The NVs were successfully loaded with fluorophores molecules (DOP-F-DS and a fluorescent protein), inorganic nanoparticles (quantum dots and magnetic nanoparticles), and anti-cancer drugs (SN-38 and doxorubicin). The encapsulation of such different molecules showed the versatility of the developed systems. The size of the vesicles varied from 100 up to 300 nm depending on the type of loaded species, which were accommodated either into the lipid bilayer or into the aqueous core according to their hydrophobic or hydrophilic nature. Viability assays were performed on cellular models of breast cancer (MCF-7 and MDA-MB-231). Results showed that NVs with encapsulated both drugs simultaneously led to a significant reduction of the cellular activity (up to 22%) compared to the free drugs or to the NVs encapsulated with only one drug. Lipidomic analysis suggested that the mechanism of action of the drugs is the same, whether they are free or encapsulated, but administration of the drugs by means of nanovesicles is more efficient in inducing cellular damage, likely because of a quicker internalization and a sustained release. This study confirms the versatility and the potential of lipid NVs for cancer treatment, as well as the validity of the ultrasound preparation method for their preparation.

TP5, a Peptide Inhibitor of Aberrant and Hyperactive CDK5/p25: A Novel Therapeutic Approach against Glioblastoma.

We examined the efficacy of selective inhibition of cyclin-dependent kinase 5 (CDK5) in glioblastoma by TP5. We analyzed its impact in vitro on CDK5 expression and activity, cell survival, apoptosis and cell cycle. DNA damage was analyzed using the expression of γH2A.X and phosphorylated ATM. Its tolerance and efficacy were assessed on in vivo xenograft mouse models. We showed that TP5 decreased the activity but not the expression of CDK5 and p35. TP5 alone impaired cell viability and colony formation of glioblastoma cell lines and induced apoptosis. TP5 increased DNA damage by inhibiting the phosphorylation of ATM, leading to G1 arrest. Whereas CDK5 activity is increased by DNA-damaging agents such as temozolomide and irradiation, TP5 was synergistic with either temozolomide or irradiation due to an accumulation of DNA damage. Concomitant use of TP5 and either temozolomide or irradiation reduced the phosphorylation of ATM, increased DNA damage, and inhibited the G2/M arrest induced by temozolomide or irradiation. TP5 alone suppressed the tumor growth of orthotopic glioblastoma mouse model. The treatment was well tolerated. Finally, alone or in association with irradiation or temozolomide, TP5 prolonged mouse survival. TP5 alone or in association with temozolomide and radiotherapy is a promising therapeutic option for glioblastoma.

Rapid, quantitative therapeutic screening for Alzheimer's enzymes enabled by optimal signal transduction with transistors.

We show that commercially sourced n-channel silicon field-effect transistors (nFETs) operating above their threshold voltage with closed loop feedback to maintain a constant channel current allow a pH readout resolution of (7.2 ± 0.3) × 10-3 at a bandwidth of 10 Hz, or ≈3-fold better than the open loop operation commonly employed by integrated ion-sensitive field-effect transistors (ISFETs). We leveraged the improved nFET performance to measure the change in solution pH arising from the activity of a pathological form of the kinase Cdk5, an enzyme implicated in Alzheimer's disease, and showed quantitative agreement with previous measurements. The improved pH resolution was realized while the devices were operated in a remote sensing configuration with the pH sensing element off-chip and connected electrically to the FET gate terminal. We compared these results with those measured by using a custom-built dual-gate 2D field-effect transistor (dg2DFET) fabricated with 2D semi-conducting MoS2 channels and a signal amplification of 8. Under identical solution conditions the nFET performance approached the dg2DFETs pH resolution of (3.9 ± 0.7) × 10-3. Finally, using the nFETs, we demonstrated the effectiveness of a custom polypeptide, p5, as a therapeutic agent in restoring the function of Cdk5. We expect that the straight-forward modifications to commercially sourced nFETs demonstrated here will lower the barrier to widespread adoption of these remote-gate devices and enable sensitive bioanalytical measurements for high throughput screening in drug discovery and precision medicine applications.

Quantum capacitance-limited MoS2 biosensors enable remote label-free enzyme measurements.

We have demonstrated atomically thin, quantum capacitance-limited, field-effect transistors (FETs) that enable the detection of pH changes with 75-fold higher sensitivity (≈4.4 V per pH) over the Nernst value of 59 mV per pH at room temperature when used as a biosensor. The transistors, which are fabricated from monolayer films of MoS2, use a room temperature ionic liquid (RTIL) in place of a conventional oxide gate dielectric and exhibit very low intrinsic noise resulting in a pH resolution of 92 × 10-6 at 10 Hz. This high device performance, which is a function of the structure of our device, is achieved by remotely connecting the gate to a pH sensing element allowing the FETs to be reused. Because pH measurements are fundamentally important in biotechnology, the increased resolution demonstrated here will benefit numerous applications ranging from pharmaceutical manufacturing to clinical diagnostics. As an example, we experimentally quantified the function of the kinase Cdk5, an enzyme implicated in Alzheimer's disease, at concentrations that are 5-fold lower than physiological values, and with sufficient time-resolution to allow the estimation of both steady-state and kinetic parameters in a single experiment. The high sensitivity, increased resolution, and fast turnaround time of the measurements will allow the development of early diagnostic tools and novel therapeutics to detect and treat neurological conditions years before currently possible.

Deep-Learning-Assisted Volume Visualization.

Designing volume visualizations showing various structures of interest is critical to the exploratory analysis of volumetric data. The last few years have witnessed dramatic advances in the use of convolutional neural networks for identification of objects in large image collections. Whereas such machine learning methods have shown superior performance in a number of applications, their direct use in volume visualization has not yet been explored. In this paper, we present a deep-learning-assisted volume visualization to depict complex structures, which are otherwise challenging for conventional approaches. A significant challenge in designing volume visualizations based on the high-dimensional deep features lies in efficiently handling the immense amount of information that deep-learning methods provide. In this paper, we present a new technique that uses spectral methods to facilitate user interactions with high-dimensional features. We also present a new deep-learning-assisted technique for hierarchically exploring a volumetric dataset. We have validated our approach on two electron microscopy volumes and one magnetic resonance imaging dataset.

Hydration-controlled anisotropic and giant permittivity in TEG-functionalized eumelanin.

Although it has long been known that the peculiar electronic-ionic conductor behavior of eumelanin is critically dependent on hydration, the detailed mechanisms by which water-polymer interactions control and affect the conduction properties have remained largely obscure. In this paper, we report a remarkable anisotropy and giant polarization effect in a synthetic eumelanin (TEGMe) chemically functionalized with hydrophilic TEG residues. FT-IR analyses of water sorption isotherms and AC measurements were consistent with a microporous structure binding or hosting mainly isolated water molecules. In contrast, similar experiments on a commercial synthetic eumelanin (AMe) used as a reference were suggestive of a bulk macroporous scaffold binding or hosting liquid water. These data disclosed for the first time the differential impact on eumelanin conductivity of vapor, liquid and ice-like forms of water adsorbed onto or embedded into the polymer layer. It is thus demonstrated, for the first time, that hydration controls the conduction properties of eumelanin in a more complex manner than is commonly believed, involving, besides the reported semiquinone comproportionation equilibria, the mode of interaction of water molecules as governed by both the chemical and morphological features of the polymer.

A Bioinformatics 3D Cellular Morphotyping Strategy for Assessing Biomaterial Scaffold Niches.

Many biomaterial scaffolds have been advanced to provide synthetic cell niches for tissue engineering and drug screening applications; however, current methods for comparing scaffold niches focus on cell functional outcomes or attempt to normalize materials properties between different scaffold formats. We demonstrate a three-dimensional (3D) cellular morphotyping strategy for comparing biomaterial scaffold cell niches between different biomaterial scaffold formats. Primary human bone marrow stromal cells (hBMSCs) were cultured on 8 different biomaterial scaffolds, including fibrous scaffolds, hydrogels, and porous sponges, in 10 treatment groups to compare a variety of biomaterial scaffolds and cell morphologies. A bioinformatics approach was used to determine the 3D cellular morphotype for each treatment group by using 82 shape metrics to analyze approximately 1000 cells. We found that hBMSCs cultured on planar substrates yielded planar cell morphotypes, while those cultured in 3D scaffolds had elongated or equiaxial cellular morphotypes with greater height. Multivariate analysis was effective at distinguishing mean shapes of cells in flat substrates from cells in scaffolds, as was the metric L1-depth (the cell height along its shortest axis after aligning cells with a characteristic ellipsoid). The 3D cellular morphotyping technique enables direct comparison of cellular microenvironments between widely different types of scaffolds and design of scaffolds based on cell structure-function relationships.

[1]Benzothieno[3,2-b]benzothiophene-Based Organic Dyes for Dye-Sensitized Solar Cells.

Three new metal-free organic dyes with the [1]benzothieno[3,2-b]benzothiophene (BTBT) π-bridge, having the structure donor-π-acceptor (D-π-A) and labeled as 19, 20 and 21, have been designed and synthesized for application in dye-sensitized solar cells (DSSC). Once the design of the π-acceptor block was fixed, containing the BTBT as the π-bridge and the cyanoacrylic group as the electron acceptor and anchoring unit, we selected three donor units with different electron-donor capacity, in order to assemble new chromophores with high molar extinction coefficients (ε), whose absorption features well reflect the good performance of the final DSSC devices. Starting with the 19 dye, which shows a molar extinction coefficient ε of over 14,000 M(-1) cm(-1) and takes into account the absorption maximun at the longer wavelength, the substitution of the BFT donor unit with the BFA yields a great enhancement of absorptivity (molar extinction coefficient ε > 42,000 M(-1) cm(-1)), until reaching the higher value (ε > 69,000 M(-1) cm(-1)) with the BFPhz donor unit. The good general photovoltaic performances obtained with the three dyes highlight the suitable properties of electron-transport of the BTBT as the π-bridge in organic chromophore for DSSC, making this very cheap and easy to synthesize molecule particularly attractive for efficient and low-cost photovoltaic devices.

Benchmarking DFT and semi-empirical methods for a reliable and cost-efficient computational screening of benzofulvene derivatives as donor materials for small-molecule organic solar cells.

A systematic computational investigation on the optical properties of a group of novel benzofulvene derivatives (Martinelli 2014 Org. Lett. 16 3424-7), proposed as possible donor materials in small molecule organic photovoltaic (smOPV) devices, is presented. A benchmark evaluation against experimental results on the accuracy of different exchange and correlation functionals and semi-empirical methods in predicting both reliable ground state equilibrium geometries and electronic absorption spectra is carried out. The benchmark of the geometry optimization level indicated that the best agreement with x-ray data is achieved by using the B3LYP functional. Concerning the optical gap prediction, we found that, among the employed functionals, MPW1K provides the most accurate excitation energies over the entire set of benzofulvenes. Similarly reliable results were also obtained for range-separated hybrid functionals (CAM-B3LYP and wB97XD) and for global hybrid methods incorporating a large amount of non-local exchange (M06-2X and M06-HF). Density functional theory (DFT) hybrids with a moderate (about 20-30%) extent of Hartree-Fock exchange (HFexc) (PBE0, B3LYP and M06) were also found to deliver HOMO-LUMO energy gaps which compare well with the experimental absorption maxima, thus representing a valuable alternative for a prompt and predictive estimation of the optical gap. The possibility of using completely semi-empirical approaches (AM1/ZINDO) is also discussed.

Survey statistics of automated segmentations applied to optical imaging of mammalian cells.

BACKGROUND: The goal of this survey paper is to overview cellular measurements using optical microscopy imaging followed by automated image segmentation. The cellular measurements of primary interest are taken from mammalian cells and their components. They are denoted as two- or three-dimensional (2D or 3D) image objects of biological interest. In our applications, such cellular measurements are important for understanding cell phenomena, such as cell counts, cell-scaffold interactions, cell colony growth rates, or cell pluripotency stability, as well as for establishing quality metrics for stem cell therapies. In this context, this survey paper is focused on automated segmentation as a software-based measurement leading to quantitative cellular measurements. METHODS: We define the scope of this survey and a classification schema first. Next, all found and manually filteredpublications are classified according to the main categories: (1) objects of interests (or objects to be segmented), (2) imaging modalities, (3) digital data axes, (4) segmentation algorithms, (5) segmentation evaluations, (6) computational hardware platforms used for segmentation acceleration, and (7) object (cellular) measurements. Finally, all classified papers are converted programmatically into a set of hyperlinked web pages with occurrence and co-occurrence statistics of assigned categories. RESULTS: The survey paper presents to a reader: (a) the state-of-the-art overview of published papers about automated segmentation applied to optical microscopy imaging of mammalian cells, (b) a classification of segmentation aspects in the context of cell optical imaging, (c) histogram and co-occurrence summary statistics about cellular measurements, segmentations, segmented objects, segmentation evaluations, and the use of computational platforms for accelerating segmentation execution, and (d) open research problems to pursue. CONCLUSIONS: The novel contributions of this survey paper are: (1) a new type of classification of cellular measurements and automated segmentation, (2) statistics about the published literature, and (3) a web hyperlinked interface to classification statistics of the surveyed papers at https://isg.nist.gov/deepzoomweb/resources/survey/index.html.

Detection and characterization of nonspecific, sparsely populated binding modes in the early stages of complexation.

A method is proposed to study protein-ligand binding in a system governed by specific and nonspecific interactions. Strong associations lead to narrow distributions in the proteins configuration space; weak and ultraweak associations lead instead to broader distributions, a manifestation of nonspecific, sparsely populated binding modes with multiple interfaces. The method is based on the notion that a discrete set of preferential first-encounter modes are metastable states from which stable (prerelaxation) complexes at equilibrium evolve. The method can be used to explore alternative pathways of complexation with statistical significance and can be integrated into a general algorithm to study protein interaction networks. The method is applied to a peptide-protein complex. The peptide adopts several low-population conformers and binds in a variety of modes with a broad range of affinities. The system is thus well suited to analyze general features of binding, including conformational selection, multiplicity of binding modes, and nonspecific interactions, and to illustrate how the method can be applied to study these problems systematically. The equilibrium distributions can be used to generate biasing functions for simulations of multiprotein systems from which bulk thermodynamic quantities can be calculated.

Design and synthesis of fluorenone-based dyes: two-photon excited fluorescent probes for imaging of lysosomes and mitochondria in living cells.

Three fluorenone-derived two-photon fluorescent probes (TK) targeting the lysosomes (TK-Lyso) and mitochondria (TK-Mito1 and TK-Mito2) were synthesized by introducing different diphenylamine moieties into the fluorenone core. The TK dyes showed high biocompatibility and long-term retention, low cytotoxicity, large Stokes shift and good fluorescence quantum yield. The results of the present work disclose a class of organic dyes with potential wide applications as specific and efficient probes for lysosomes and mitochondria in the study of various biological processes.

Thiophene-based fluorescent probes with low cytotoxicity and high photostability for lysosomes in living cells.

BACKGROUND: Selective imaging of lysosomes by fluorescence microscopy using specific fluorescent probes allows the study of biological processes and it is potentially useful also for diagnosis. Lysosomes are involved in numerous physiological processes, such as bone and tissue remodeling, plasma membrane repair, and cholesterol homeostasis, along with cell death and cell signaling. Despite the great number of dyes available today on the market, the search for new fluorescent dyes easily up-taken by cells, biocompatible and bearing bright and long-lasting fluorescence is still a priority. METHODS: Two thiophene-based fluorescent dyes, TC1 and TC2, were synthetized as lysosome-specific probes. RESULTS: The new dyes showed high selectivity for fluorescent staining and imaging of lysosomes and disclosed high photostability, low toxicity and pH insensitivity in the range 2-10. CONCLUSIONS: The TC dyes exhibited high co-localization coefficients (>95%) and moderate quantum yields. They showed high biocompatibility and long-term retention, important features for biological applications. GENERAL SIGNIFICANCE: The results of the present work disclose a new class of organic dyes with potential wide applications as specific and efficient lysosome probes in the study of various biological processes.

Synthesis and structure of conjugated molecules with the benzofulvene core.

A general method to synthesize conjugated molecules with a benzofulvene core is reported. Up to four conjugated substituents have been introduced via a three-step sequence including (1) synthesis of 1,2-bis(arylethynyl)benzenes; (2) exo-dig electrophilic cyclization promoted by iodine; and (3) cross-coupling reaction of the resulting bis-iodobenzofulvenes with organoboron, organotin, or ethynyl derivatives under Pd catalysis. Structural aspects of the new compounds are discussed.

Specific and non-specific protein association in solution: computation of solvent effects and prediction of first-encounter modes for efficient configurational bias Monte Carlo simulations.

Weak and ultraweak protein-protein association play a role in molecular recognition and can drive spontaneous self-assembly and aggregation. Such interactions are difficult to detect experimentally, and are a challenge to the force field and sampling technique. A method is proposed to identify low-population protein-protein binding modes in aqueous solution. The method is designed to identify preferential first-encounter complexes from which the final complex(es) at equilibrium evolve. A continuum model is used to represent the effects of the solvent, which accounts for short- and long-range effects of water exclusion and for liquid-structure forces at protein/liquid interfaces. These effects control the behavior of proteins in close proximity and are optimized on the basis of binding enthalpy data and simulations. An algorithm is described to construct a biasing function for self-adaptive configurational-bias Monte Carlo of a set of interacting proteins. The function allows mixing large and local changes in the spatial distribution of proteins, thereby enhancing sampling of relevant microstates. The method is applied to three binary systems. Generalization to multiprotein complexes is discussed.