Phenanthroline Complexation Enhances the Cytotoxic Activity of the VO-Chrysin System

Metal complexation in general improves the biological properties of ligands. We have previously measured the anticancer effects of the oxidovanadium(IV) cation with chrysin complex, VO(chrys)2. In the present study, we synthesized and characterized a new complex generated by the replacement of one chrysin ligand by phenanthroline (phen), VO(chrys)phenCl, to confer high planarity for DNA chain intercalation and more lipophilicity, giving rise to a better cellular uptake. In effect, the uptake of vanadium has been increased in the complex with phen and the cytotoxic effect of this complex proved higher in the human lung cancer A549 cell line, being involved in its mechanisms of action, the production of cellular reactive oxygen species (ROS), the decrease of the natural antioxidant compound glutathione (GSH) and the ratio GSH/GSSG (GSSG, oxidized GSH), and mitochondrial membrane damage. Cytotoxic activity studies using the non-tumorigenic HEK293 cell line showed that [VO(chrys)phenCl] exhibits selectivity action towards A549 cells after 24 h incubation. The interaction with bovine serum albumin (BSA) by fluorometric determinations showed that the complex could be carried by the protein and that the binding of the complex to BSA occurs through H-bond and van der Waals interactions.

Residue Interactions Affecting The Deprotonation of Internal Guanine Moieties In Oligodeoxyribonucleotides, Calculated By FMO Methods

The effect of vicinal molecular groups on the intrinsic acidity of a central guanine residue in short single-stranded DNA models, and the potentials exerted by the backbone and the nucleobases on the leaving proton were determined by the Fragment Molecular Orbital (FMO) method, in terms of quantum descriptors (QD) and pair interaction interfragment decomposition analysis (PIEDA). The acidity of the central guanine moiety decreased with increasing oligonucleotide length, in response to changes by less than1 eV in the ionization potential, global softness, electrophilicity index and electronegativity descriptors. The differences in these descriptors were majorly interpreted in terms of the electrostatic influence of the negative charges residing on the backbone of the molecule. Additionally, this electric-field effect was determined explicitly for the displacement of the test hydronium ion to a distance of 250 Å from its original position, resulting in good agreement with calculations of the variation in Gibbs free energies, obtained from physical experiments conducted on the identical oligonucleotide sequences. The reported results are useful for biophysical applications of deoxyriboligonucleotides containing guanine residues in order to induce local negative charges at specific positions in the DNA chain.

Study of Electrical and Thermoelectrical Properties of One Strand DNA Chain for Nanoscale Thermoelectric Applications

The concept of using DNA molecules for designing nano-scale electronic systems has attracted researcher’s attention due to the unique properties of DNA, such as self-assembly and self-recognition. Thus, increased number of studies, theoretically and experimentally, have been carried out to study the possibility of adopting DNA molecules in designing nanoscale thermoelectric devices. In this work, a general expression of the electron transmission probability that describes the electron transfer through one strand DNA chain has been derived using the steady-state-formalism by assuming one strand of DNA molecules as line model. The energy-dependent transmission was studied, then energy-and temperature-dependent Seebeck coefficient, and thermoelectric characteristics of four one strand DNA sequences: (A-A)10, (C-C)10, (G-G)10 and (T-T)10 are theoretically studied. According to the obtained results, it is found that the transmission behavior (magnitude and position) is varying with the type of DNA sequence. Also, the energy dependent Seebeck coefficient (S-E) curves clearly show a nonlinear energy-dependence, while the relationship between Seebeck coefficient and temperature (S-T) is linear. Thermoelectric power factor as a function of temperature was found to be enhanced with the temperature increment for the four types of DNA nucleobases. The highest values of thermoelectric power factor belong to thymine (120Wm-1K-2) and cytosine (60 Wm-1K-2), that nominate them as outstanding candidate thermoelectric materials to be adopted in the fabrication of one strand DNA-base nanoscale thermoelectric devices.

Transition between Random and Periodic Electron Currents on a DNA Chain

By resorting to a model inspired to the standard Davydov and Holstein-Fröhlich models, in the present paper we study the motion of an electron along a chain of heavy particles modeling a sequence of nucleotides proper to a DNA fragment. Starting with a model Hamiltonian written in second quantization, we use the Time Dependent Variational Principle to work out the dynamical equations of the system. It can be found that, under the action of an external source of energy transferred to the electron, and according to the excitation site, the electron current can display either a broad frequency spectrum or a sharply peaked frequency spectrum. This sequence-dependent charge transfer phenomenology is suggestive of a potentially rich variety of electrodynamic interactions of DNA molecules under the action of electron excitation. This could imply the activation of interactions between DNA and transcription factors, or between DNA and external electromagnetic fields.

Quantification of Nitric Oxide Concentration Using Single-Walled Carbon Nanotube Sensors

Nitric oxide (NO), a free radical present in biological systems, can have many detrimental effects on the body, from inflammation to cancer. Due to NO’s short half-life, detection and quantification is difficult. The inability to quantify NO has hindered researchers’ understanding of its impact in healthy and diseased conditions. Single-walled carbon nanotubes (SWNTs), when wrapped in a specific single-stranded DNA chain, becomes selective to NO, creating a fluorescence sensor. Unfortunately, the correlation between NO concentration and the SWNT’s fluorescence intensity has been difficult to determine due to an inability to immobilize the sensor without altering its properties. Through the use of a recently developed sensor platform, systematic studies can now be conducted to determine the correlation between SWNT fluorescence and NO concentration. This paper explains the methods used to determine the equations that can be used to convert SWNT fluorescence into NO concentration. Through the use of the equations developed in this paper, an easy method for NO quantification is provided. The methods outlined in this paper will also enable researchers to develop equations to determine the concentration of other reactive species through the use of SWNT sensors.

Brief history of high-throughput nucleic acid sequencing methods.

The processes occurring during the enzymatic growth of the DNA chain in the form of elongation of the molecules, the release of pyrophosphate, proton, thermal energy, and an increase in electrical impedance, which are used in various methods of high-throughput DNA sequencing by synthesis, are briefly considered. The detection of DNA chain growth is controlled by high-voltage gel electrophoresis and has limited scalability. As for mentioned above other by-products of DNA chain polymerization, their detection can be easily scalable, which has led to the emergence of methods for whole genome sequencing of new generations of DNA, which have received the widely used abbreviation NGS - Next Generation Sequencing. However, the attribution of any new sequencing method to a particular generation is sometimes difficult due to the fact that the principle used in it was born earlier than the other one was implemented, which turned out to be less productive in the end. In addition, it is more important to distinguish the methods of new DNA sequencing into two groups in which the massive parallel sequencing of identical matrices takes place or the sequencing of single DNA molecules takes place and last one have received the designation monomolecular sequencing. In this review, along with the classical Sanger method of DNA sequencing, which is still the "gold standard", pyrosequencing, semiconductor sequencing, thermosequencing, electronic sequencing, fluorescent bridge sequencing and sequencing using nanoballs from the first group, as well as monomolecular methods – tSMS sequencing, SMRT sequencing and nanopore sequencing are considered. Attention is paid to the costs of DNA sequencing and the prospects for its development.

A Novel Consensus Fuzzy K-Modes Clustering Using Coupling DNA-Chain-Hypergraph P System for Categorical Data

In this paper, a data clustering method named consensus fuzzy k-modes clustering is proposed to improve the performance of the clustering for the categorical data. At the same time, the coupling DNA-chain-hypergraph P system is constructed to realize the process of the clustering. This P system can prevent the clustering algorithm falling into the local optimum and realize the clustering process in implicit parallelism. The consensus fuzzy k-modes algorithm can combine the advantages of the fuzzy k-modes algorithm, weight fuzzy k-modes algorithm and genetic fuzzy k-modes algorithm. The fuzzy k-modes algorithm can realize the soft partition which is closer to reality, but treats all the variables equally. The weight fuzzy k-modes algorithm introduced the weight vector which strengthens the basic k-modes clustering by associating higher weights with features useful in analysis. These two methods are only improvements the k-modes algorithm itself. So, the genetic k-modes algorithm is proposed which used the genetic operations in the clustering process. In this paper, we examine these three kinds of k-modes algorithms and further introduce DNA genetic optimization operations in the final consensus process. Finally, we conduct experiments on the seven UCI datasets and compare the clustering results with another four categorical clustering algorithms. The experiment results and statistical test results show that our method can get better clustering results than the compared clustering algorithms, respectively.

Protein-DNA target search relies on Quantum Walk

Protein-DNA interactions play a fundamental role in all life systems. A critical issue of such interactions is given by the strategy of protein search for specific targets on DNA. The mechanisms by which the protein are able to find relatively small cognate sequences, typically 15-20 base pairs (bps) for repressors, and 4-6 bps for restriction enzymes among the millions of bp of non-specific chromosomal DNA have hardly engaged researcher for decades. Recent experimental studies have generated new insights on the basic processes of protein-DNA interactions evidencing the underlying complex dynamic phenomena involved, which combine three-dimensional and one-dimensional motion along the DNA chain. It has been demonstrated that protein molecules spend most of search time on the DNA chain with an extraordinary ability to find the target very quickly, in some cases, with two orders of magnitude faster than the diffusion limit. This unique property of protein-DNA search mechanism is known as facilitated diffusion. Several theoretical mechanisms have been suggested to describe the origin of facilitated diffusion. However, none of such models currently has the ability to fully describe the protein search strategy.In this paper, we suggest that the ability of proteins to identify consensus sequence on DNA is based on the entanglement of π-π electrons between DNA nucleotides and protein amino acids. The π-π entanglement is based on Quantum Walk (QW), through Coin-position entanglement (CPE). First, the protein identifies a dimer belonging to the consensus sequence, and localize a π on such dimer, hence, the other π electron scans the DNA chain until the sequence is identified. By focusing on the example of recognition of consensus sequences by EcoRV or EcoRI, we will describe the quantum features of QW on protein-DNA complexes during search strategy, such as walker quadratic spreading on a coherent superposition of different vertices and environment-supported long-time survival probability of the walker. We will employ both discrete- or continuous-time versions of QW. Biased and unbiased classical Random Walk (CRW) has been used for a long time to describe Protein-DNA search strategy. QW, the quantum version of CRW, have been widely studied for its applications in quantum information applications. In our biological application, the walker (the protein) resides at a vertex in a graph (the DNA structural topology). Differently to CRW, where the walker moves randomly, the quantum walker can hop along the edges in the graph to reach other vertices entering coherently a superposition across different vertices spreading quadratically faster than CRW analogous evidencing the typical speed up features of the QW. When applied to protein-DNA target search problem, QW gives the possibility to achieve the experimental diffusional motion of proteins over diffusion classical limits experienced along DNA chains exploiting quantum features such as CPE and long-time survival probability supported by environment. In turn, we come to the conclusion that, under quantum picture, the protein search strategy does not distinguish between one-dimensional (1D) and three-dimensional (3D) case.SignificanceMost biological processes are associated to specific protein molecules binding to specific target sequences of DNA. Experiments have revealed a paradoxical phenomenon that can be synthesized as follows: proteins generally diffuse on DNA very slowly, but they can find targets very fast overwhelming two orders of magnitude faster than the diffusion limit. This paradox is known as facilitated diffusion. In this paper, we demonstrate that the paradox is solved by invoking the quantum walk picture for protein search strategy. This because the protein exploits quantum properties, such as long-time survival probability due to coherence shield induced by environment and coin-position entanglement to identify consensus sequence, in searching strategy. To our knowledge, this is the first application of quantum walk to the problem of protein-DNA target search strategy.