Electron-ion Interaction Potential Research Articles

Computational Study and Performance Evaluation of Different Genomic Signal Processing Methods for Identification of Protein Coding Regions (Exon Regions) of DNA Sequence

developments in the area of genomic signal processing (GSP) reveal that this approach has important role in the analysis of genomic sequence, structure and function as well as the gene regulation of different organisms. In this paper we analyze different genomic signal processing methods used for identification of exon coding regions in DNA sequence. The gene sequences of interest are mapped to electron ion interaction potential (EIIP) values of nucleotides and these transformed numerical gene sequences are processed through different signal processing techniques like discrete Fourier transform (DFT), auto regressive (AR) and adaptive auto regressive (AAR) methods. The performance evaluation in terms of computational time is estimated and analyzed. By applying the EIIP mapped sequence to these DFT, AR and AAR methods, the effective computational time is abruptly reduced in AAR method compared to the DFT and AR methods. We tested five sequences of c-elegans) (AF099922), (FO080874.2), (FO081434)), fruitfly (NM_170135) & homosapien (BDNF (NG_011794)).

Molecular phylogeny analysis using correlation distance and spectral distance.

A wide range of methods with or without sequence alignment have been used to study molecular phylogeny for information on the evolution of species. Two approaches to construct the phylogenetic tree using (a) direct correlation of protein sequences and (b) difference between the Discrete Fourier Transform coefficients are described. The proposed methods use a transformation where each amino acid is represented by its Electron-Ion Interaction Potential (EIIP) value. Phylogenetic tree of two mammalian orders, primates and cetacea, is generated based on Fitch-Margoliash, Neighbour-Joining and UPGMA methods and compared. The phylogenetic tree of evolutionary relationships thus obtained can be used for comparison of species and gene sequences. The information thus gathered provide meaningful insights into the pattern and process of evolution which will help researchers in developing new breeds of animals and plants.

Simple and General Criterion for “in silico” Screening of Candidate HIV Drugs

Highly active antiretroviral therapy (HAART) dramatically has changed the course of HIV infection. Currently, this therapy involves the use of agents from at least two distinct classes of antivirals: a protease inhibitor in combination with two nucleoside/nucleotide reverse transcriptase inhibitors (N(t)RTIs), or a non-nucleoside reverse transcriptase inhibitor (NNRTI) in combination with NRTIs. Recently, the third family of antivirals started to be used clinically, with the advent of enfuvirtide, the first fusion inhibitor. This broad spectrum of anti-HIV agents recently was extended with compounds inhibiting HIV integrase and vital entry. But these advances did not come without a cost: there were the short- and long-term drug toxicities, emergence of drug resistance, and persistence of viral reservoirs. For these reasons, there is a pressing need for novel anti-HIV drugs, particularly those that have a novel action mechanism, as these might be less likely to show cross-resistance with current therapies. The field of bioinformatics has become a major part of the drug discovery pipeline playing a key role in improvement and acceleration of the time and money consuming process of the drug development. Here we review the application of the EIIP/AQVN (Electron-Ion Interaction Potential, EIIP; Average Quasi Valence Number, AQVN) bioinformatics concept in the development of new anti-HIV drugs and propose a simple theoretical criterion for a virtual screening of molecular libraries for promising lead anti-HIV compounds and refinement of selected lead compounds in order to increase their biological activity.

Second-order Born approximation for the scattering phase shifts: Application to the Friedel sum rule

Screening effects are important to understand various aspects of ion–solid interactions and, in particular, play a crucial role in the stopping of ions in solids. In this paper the phase shifts and scattering amplitudes for the quantum-mechanical elastic scattering within up to the second-order Born (B2) approximation are revisited for an arbitrary spherically-symmetric electron–ion interaction potential. The B2 phase shifts and scattering amplitudes are then used to derive the Friedel sum rule (FSR) involving the second-order Born corrections. This results in a simple equation for the B2 perturbative screening parameter of an impurity ion immersed in a fully degenerate electron gas which, as expected, turns out to depend on the ion atomic number Z1 unlike the first-order Born (B1) screening parameter reported earlier by some authors. Furthermore, our analytical results for the Yukawa, hydrogenic, Hulthén, and Mensing potentials are compared, for both positive and negative ions and a wide range of one-electron radii, to the exact screening parameters calculated self-consistently by imposing the FSR requirement. It is shown that the B2 screening parameters agree excellently with the exact values at large and moderate densities of the degenerate electron gas, while at lower densities they progressively deviate from the exact numerical solutions but are nevertheless more accurate than the prediction of the B1 approximation. In addition, a simple Padé approximant to the Born series has been developed that improves the performance of the perturbative FSR for any negative ion as well as for Z1=+1.

Inverse bremsstrahlung heating rate for dense plasmas in laser fields

We report a theoretical analysis of inverse bremsstrahlung heating rate in the eikonal approximation. The present analysis is performed for a dense plasma using the screened electron-ion interaction potential for the ion charge state Zi = 1 and for both the weak and strong plasma screening cases. We have also compared the eikonal results with the first Born approximation (FBA) [M. Moll et al., New J. Phys. 14, 065010 (2012)] calculation. We find that the magnitudes of inverse bremsstrahlung heating rate within the eikonal approximation (EA) are larger than the FBA values in the weak screening case (κ = 0.03 a.u.) in a wide range of field strength for three different initial electron momenta (2, 3, and 4 a.u.). But for strong screening case (κ = 0.3 a.u.), the heating rates predicted by the two approximations do not differ much after reaching their maximum values. Furthermore, the individual contribution of photoemission and photoabsorption processes to heating rate is analysed for both the weak and strong screening cases. We find that the single photoemission and photoabsorption rates are the same throughout the field strength while the multiphoton absorption process dominates over the multiphoton emission process beyond the field strength ≈ 4×108 V/cm. The present study of the dependence of heating rate on the screening parameter ranging from 0.01 to 20 shows that whereas the heating rate predicted by the EA is greater than the FBA up to the screening parameter κ = 0.3 a.u., the two approximation methods yield results which are nearly identical beyond the above value.

Termodynamika metalichnoho heliyu

The internal and free energies of liquid metallic helium are calculated for wide ranges of density and temperature, and the corresponding equation of state is obtained in the framework of perturbation theory. The electron-ion interaction potential is selected as a small parameter, and the calculations are carried out to the third order of smallness inclusive. Conduction electrons are considered in the random phase approximation with regard for the exchange interaction and correlations in the local field approximation. The hard-sphere model is used for the nuclear subsystem, the sphere diameter being the only parameter of the theory. The sphere diameter and the system density, at which helium transforms from the single- into double-ionized state are evaluated by analyzing the effective pair interaction between helium nuclei also in the third order of perturbation theory. The case of double-ionized helium atoms is considered. The third-order correction turns out substantial in all examined cases. The values obtained for thermodynamic parameters such as the density, temperature, and pressure fall within the ranges typical of the central regions of giant planets, which allows us to suppose the existence of metallic helium in the solar system.

Phosphocholine-binding antibody activities are hierarchically encoded in the sequence of the heavy-chain variable region: dominance of self-association activity in the T15 idiotype

A methodology based on the representation of each amino acid of a protein sequence by the electron-ion interaction potential and subsequent analysis by signal processing was used to determine the characteristic or common frequency (in Hz) that reflects the biological activity shared among phosphocholine (PC)-binding antibodies. The common frequency for the variable portion of the heavy chain (VH) of the PC-specific antibodies is found to be at f = 0.37 Hz. The VH sequences of the PC-binding antibodies exhibit three subsites for the PC moiety where hypervariable region 2 (CDR2) plays a role in the interaction with the phosphate group. Mutations in this VH region have an impact on the ability of mutant variants to bind PC and its carrier molecule, as well as on the characteristic frequency shift toward f = 0.12 Hz for mutants failing to bind both hapten and carrier. The VH sequence of mutants that retain the ability to bind PC still shows f = 0.37 Hz, suggesting that this frequency determines PC binding. However, this statement was not confirmed as mutation in another PC subsite impairs PC binding but retains both the phosphate-group recognition and the frequency at f = 0.37 Hz. Herein, this finding is discussed to promote the idea that the VH sequence of the PC-binding antibodies encodes the subsite for phosphate-group binding as a dominant functional activity and that only CDR2 of the T15-idiotype antibodies together with FR3 region form an autonomous self-association function represented by the T15VH50-73 peptide with f = 0.37±0.05 Hz. Thus, these data confirmed that T15VH50-73 peptide might be used in superantibody technology.

Equation of state of metallic helium

The effective ion-ion interaction, free energy, pressure, and electric resistance of metallic liquid helium have been calculated in wide density and temperature ranges using perturbation theory in the electron-ion interaction potential. In the case of conduction electrons, the exchange interaction has been taken into account in the random-phase approximation and correlations have been taken into account in the local-field approximation. The solid-sphere model has been used for the nuclear subsystem. The diameter of these spheres is the only parameter of this theory. The diameter and density of the system at which the transition of helium from the singly ionized to doubly ionized state occurs have been estimated by analyzing the pair effective interaction between helium atoms. The case of doubly ionized helium atoms has been considered. Terms up to the third order of perturbation theory have been taken into account in the numerical calculations. The contribution of the third-order term is significant in all cases. The electric resistance and its temperature dependence for metallic helium are characteristic of simple divalent metals in the liquid state. The thermodynamic parameters—temperature and pressure densities-are within the ranges characteristic of the central regions of giant planets. This makes it possible to assume the existence of helium in the metallic state within the solar system.

Inverse bremsstrahlung heating beyond the first Born approximation for dense plasmas in laser fields

Inverse bremsstrahlung (IB) heating, an important process in the laser–matter interaction, involves two different kinds of interaction—the interaction of the electrons with the external laser field and the electron–ion interaction. This makes analytical approaches very difficult. In a quantum perturbative approach to the IB heating rate in strong laser fields, usually the first Born approximation with respect to the electron–ion potential is considered, whereas the influence of the electric field is taken exactly in the Volkov wave functions. In this paper, a perturbative treatment is presented adopting a screened electron–ion interaction potential. As a new result, we derive the momentum-dependent, angle-averaged heating rate in the first Born approximation. Numerical results are discussed for a broad range of field strengths, and the conditions for the applicability of a linear approximation for the heating rate are analyzed in detail. Going a step further in the perturbation series, we consider the transition amplitude in the second Born approximation, which enables us to calculate the heating rate up to the third order of the interaction strength.

On the theory of high-frequency permittivity of a fully ionized plasma I: Electron-ion interaction pseudopotential and rules of sum

In the context of the electron-ion interaction potential, a rigorous description is given of the permittivity ɛ(ω) of a fully ionized plasma in the frequency range ω ≫ \( \tilde v_{ei} \), where \( \tilde v_{ei} \) is the characteristic electron-ion collision frequency. The interaction and degeneration effects in the electron and ion subsystems are systematically taken into account. The asymptotics of the effective collision frequency ν(ω) and the renormalization function γ(ω) for the plasma frequency are found, and the rules of sums for the permittivity ɛ(ω) are determined.

Hybrid approach to analysis of β-sheet structures based on signal processing and statistical consideration

A number of biotechnology applications are based on protein design. For this design, the relationship between a protein’s primary structure and its conformation is of vital importance. A β-sheet is a common feature of a protein’s two-dimensional structure; therefore, elucidating the principles governing β-sheet structure and its stability is critical for understanding the protein-folding process. In the three-dimensional representation of protein molecules, C α carbon coordinates (carbon atom immediately adjacent to the carboxylate group) have often been employed instead of the complete set of coordinates for the corresponding residues. Using the C α carbon coordinates, we showed that particular amino acids are not randomly distributed within a β-sheet structure. On the basis of a new statistical approach for the analysis of a spatial distribution of amino acids in a protein, presented by their physico-chemical parameters, the electron–ion interaction potential (EIIP) and hydrophobicity, are described here. The relationship between amino acid positions inside the β-sheet and the EIIP and hydrophobicity parameters was established. The correlation between amino acid propensities related to the β-sheet was examined using multiple cross-spectra analysis. We also applied the continuous wavelet transform for the analysis of selected β-sheet structures using the EIIP and hydrophobicity parameters. The findings provide new insight into conformational propensities of amino acids for the adaption of β-sheet structures.

Effects of magnetic field and temperature on the nonrelativistic bremsstrahlung process in magnetized anisotropic plasmas

The magnetic field and thermal effects on the nonrelativistic electron–ion bremsstrahlung process are investigated in magnetized anisotropic plasmas. The effective electron–ion interaction potential is obtained in the presence of an external magnetic field. Using the Born approximation for the initial and final states of the projectile electron, the bremsstrahlung radiation cross section and bremsstrahlung emission rate are obtained as functions of the electron energy, radiation photon energy, magnetic field strength, plasma temperature, and Debye length. It is shown that the effects of the magnetic field enhance the bremsstrahlung radiation cross section for low plasma temperatures and, however, suppress the bremsstrahlung cross section for high plasma temperatures. It is also shown that the magnetic field effects diminish the bremsstrahlung emission rate in magnetized high temperature plasmas.

System identification: DNA computing approach

A DNA computing algorithm (DNACA) with an electron–ion interaction potential (EIIP) decoding scheme is proposed to identify a class of transfer functions. The DNACA includes enzyme and virus operators which provide a highly modular, flexible, and accurate self-organizing structure environment. Simulation study based on De Jong’s test functions show its superior performance when compared with the improved and standard genetic algorithms (GAs).

Nonthermal and Plasmon Effects on Elastic Electron-Ion Collisions in Hot Quantum Lorentzian Plasmas

The nonthermal and plasmon effects on elastic electron-ion collisions are investigated in hot quantum Lorentzian plasmas. The modified interaction model taking into account the nonthermal screening and plasmon effects is employed to represent the electron-ion interaction potential in hot quantum Lorentzian plasmas. The eikonal phase and differential collision cross-section are obtained as functions of the impact parameter, collision energy, spectral index, and plasma parameters by using the second-order eikonal analysis. It is shown that the plasmon effect suppresses the eikonal phase and collision cross-section for 0 < β (ћω0 /kBT < 0.6) and, however, enhances it for 0.6 < β < 1, where ω0 is the plasma frequency and T is the plasma temperature. It is also shown that the nonthermal character of the quantum Lorentzian plasma suppresses the elastic electron-ion collision cross-section.

Electron–electron collision effects on the bremsstrahlung emission in Lorentzian plasmas

Electron–electron collision effects on the electron–ion bremsstrahlung process are investigated in Lorentzian plasmas. The effective electron–ion interaction potential is obtained by including the far-field terms caused by electron–electron collisions with an effective Debye length in Lorentzian plasmas. The bremsstrahlung radiation cross section is obtained as a function of the electron energy, photon energy, collision frequency, spectral index and Debye length using the Born approximation for the initial and final states of the projectile electron. It is shown that the non-Maxwellian character suppresses the bremsstrahlung radiation cross section. It is also shown that the electron–electron collision effect enhances the bremsstrahlung emission spectrum. In addition, the bremsstrahlung radiation cross section decreases with an increase in the plasma temperature.

Analysis of Genomics and Proteomics Using DSP Techniques

With the enormous amount of data that is available in the public domain, signal processing concepts are playing an important role in genomic and proteomic data processing. The binary sequence method is well known in the literature for genomic signal processing. As an alternative to the binary sequence method, this paper presents a new view to the genomic sequence processing with the electron-ion interaction potential (EIIP) values for nucleotides. The efficacy of the EIIP values-based method is demonstrated through implementation results for the prediction of the gene F56F11.4 with five exons and for cystic-fibrosis gene identification. The biological function of a protein is determined by the amino-acid sequence within the protein. Identification of the amino acids (hot spots) that contribute to the characteristic frequency characterizing a particular biological function is an important task in the protein sequence analysis. Hence, using EIIP values for amino acids, this paper presents a continuous-wavelet transform approach using the modified Morlet wavelet for the identification of active sites (hot spots) in a protein sequence. The efficacy of the approach is illustrated through implementation results on hemoglobin human alpha, human immunodeficiency virus, and oncogene protein sequences.

Novel Virtual Screening Protocol Based on the Combined Use of Molecular Modeling and Electron-Ion Interaction Potential Techniques To Design HIV-1 Integrase Inhibitors

HIV-1 integrase (IN) is an essential enzyme for viral replication and represents an intriguing target for the development of new drugs. Although a large number of compounds have been reported to inhibit IN in biochemical assays, no drug active against this enzyme has been approved by the FDA so far. In this study, we report, for the first time, the use of the electron-ion interaction potential (EIIP) technique in combination with molecular modeling approaches for the identification of new IN inhibitors. An innovative virtual screening approach, based on the determination of both short- and long-range interactions between interacting molecules, was employed with the aim of identifying molecules able to inhibit the binding of IN to viral DNA. Moreover, results from a database screening on the commercial Asinex Gold Collection led to the selection of several compounds. One of them showed a significant inhibitory potency toward IN in the overall integration assay. Biological investigations also showed, in agreement with modeling studies, that these compounds prevent recognition of DNA by IN in a fluorescence fluctuation assay, probably by interacting with the DNA binding domain of IN.

Application Of The EIIP/ISM Bioinformatics Concept in Development of New Drugs

The development of a new therapeutic drug is a complex, lengthy and expensive process. On average, only one out of 10,000 - 30,000 originally synthesized compounds will clear all the hurdles on the way to becoming a commercially available drug. The process of early and full preclinical discovery and clinical development for a new drug can take twelve to fifteen years to complete, and cost approximately 800 million dollars. The field of bioinformatics has become a major part of the drug discovery pipeline playing a key role in improvement and acceleration of this time and money consuming process. Here we reviewed the application of the EIIP/ISM bioinformatics concept for the development of new drugs. This approach, connecting the electron-ion interaction potential of organic molecules and their biological properties, can significantly reduce development time through (i) identification of promising lead compounds that have some activity against a disease by fast virtual screening of the large molecular libraries, (ii) refinement of selected lead compounds in order to increase their biological activity, and (iii) identification of domains of proteins and nucleotide sequences representing potential targets for therapy. Special attention is paid in this review to the application of the EIIP/ISM bioinformatics platform along with other experimental techniques (screening of a phage displayed peptide libraries, testing selected peptides and small molecules for antiviral activity in vitro) in development of HIV entry inhibitors, representing a new generation of the AIDS drugs.

Nonthermal Screening Effects on Elastic Atomic Collisions in Kappa-Maxwellian Distribution Plasmas

Nonthermal and anisotropic screening effects on elastic electron-ion collision processes in kappa-Maxwellian distribution plasmas are investigated using the first-order eikonal method. The electron-ion interaction potential in kappa-Maxwellian distribution plasmas has been obtained by the introduction of the longitudinal plasma dielectric function (εκM). In the first-order eikonal analysis, it is found that the dynamic screening effect on the eikonal phase becomes the static screening effect. The nonthermal screening effects on the elastic scattering cross sections are found to be more significant for smaller spectral indices.

Investigation of the applicability of dielectric relaxation properties of amino acid solutions within the resonant recognition model

The resonant recognition model (RRM) is a physicomathematical approach used to analyze the interactions of a protein and its target, using digital signal processing methods. The RRM is based on the finding that there is a significant correlation between the spectra of numerical presentation of protein sequences and their biological activities. Initially, the electron-ion interaction potential was used to represent each amino acid in the protein sequences. In this paper, the dielectric constant (epsilon') and dielectric loss tangent (tan delta) parameters have been determined for their possible use in the RRM. These parameters are based on the values of capacitance and conductance obtained experimentally for 20 amino acid solutions using dielectric spectroscopy for the case of the real component of dielectric permittivity; the parameter used is the dielectric increment (deltaepsilon'), the difference between dielectric constant of the amino acid solution and that of the solvent alone. The results of multiple cross-spectral analyses have shown that parameters analyzed generate in the consensus spectrum one dominant peak corresponding to the common biological activity of proteins studied, allowing the conclusion that these new parameters are suitable for use in the RRM approach.