Abstract

Topological quantum computation is a promising technique to achieve large-scale, error-corrected computation. Quantum hardware is used to create a large, 3-dimensional lattice of entangled qubits while performing computation requires strategic measurement in accordance with a topological circuit specification. The specification is a geometric structure that defines encoded information and fault-tolerant operations. The compilation of a topological circuit is one important aspect of programming a quantum computer, another is the mapping of the topological circuit into the operations performed by the hardware. Each qubit has to be controlled, and measurement results are needed to propagate encoded quantum information from input to output. Anticancer peptides (ACPs) are polycationic amphiphiles capable of preferentially killing a widespectrum of cancer cells relative to non-cancerous cells. Their primary mode of action is aninteraction with the cell membrane and subsequent activation of lytic effects, however it remainscontroversial the exact mechanism responsible for this mode of action. It has in previous studies been shown that utilizing zeta potential analyses it was possible to demonstrate the interaction of a small anticancer peptide with membrane modelsystems and cancer cells. Electrostatic interactions have a pivotal role in the cell killing processand in contrast to the AMPs action cell death occurs without achieving full neutralization of themembrane charge. The advent of microarray technology has revolutionized the search for genes that are differentially expressed across a range of cell types or experimental conditions. Traditional clustering methods, such as hierarchical clustering, are often difficult to deploy effectively since genes rarely exhibit similar expression pattern across a wide range of conditions. Web-enabled service called GEMS (Gene Expression Mining Server) for biclustering microarray data where Users may upload expression data and specify a set of criteria.GEMS performs bicluster mining based on a Gibbs sampling paradigm. Here, in Biogenea we have for the first time discovered an In silico designed of an Anticancer Peptide SVS-1 multipharmacophore as a potential drug-like efficator in Preceding Membrane Neutralization by Mapping of Topological Quantum Circuits to a Physical Hardware multi-mimotopic algorithmic approach for biclustering analysis of expression data.

Keywords

Mapping; Topological; Quantum Circuits; Physical Hardware; In silico; Anticancer Peptide; SVS-1 multipharmacophore; drug-like; efficator; Preceding Membrane; Neutralization; algorithmic approach; biclustering analysis; expression data;

Abstract

Topological quantum computation is a promising technique to achieve large-scale, error-corrected computation. Quantum hardware is used to create a large, 3-dimensional lattice of entangled qubits while performing computation requires strategic measurement in accordance with a topological circuit specification. The specification is a geometric structure that defines encoded information and fault-tolerant operations. The compilation of a topological circuit is one important aspect of programming a quantum computer, another is the mapping of the topological circuit into the operations performed by the hardware. Each qubit has to be controlled, and measurement results are needed to propagate encoded quantum information from input to output. Anticancer peptides (ACPs) are polycationic amphiphiles capable of preferentially killing a widespectrum of cancer cells relative to non-cancerous cells. Their primary mode of action is aninteraction with the cell membrane and subsequent activation of lytic effects, however it remainscontroversial the exact mechanism responsible for this mode of action. It has in previous studies been shown that utilizing zeta potential analyses it was possible to demonstrate the interaction of a small anticancer peptide with membrane modelsystems and cancer cells. Electrostatic interactions have a pivotal role in the cell killing processand in contrast to the AMPs action cell death occurs without achieving full neutralization of themembrane charge. The advent of microarray technology has revolutionized the search for genes that are differentially expressed across a range of cell types or experimental conditions. Traditional clustering methods, such as hierarchical clustering, are often difficult to deploy effectively since genes rarely exhibit similar expression pattern across a wide range of conditions. Web-enabled service called GEMS (Gene Expression Mining Server) for biclustering microarray data where Users may upload expression data and specify a set of criteria.GEMS performs bicluster mining based on a Gibbs sampling paradigm. Here, in Biogenea we have for the first time discovered an In silico designed of an Anticancer Peptide SVS-1 multipharmacophore as a potential drug-like efficator in Preceding Membrane Neutralization by Mapping of Topological Quantum Circuits to a Physical Hardware multi-mimotopic algorithmic approach for biclustering analysis of expression data.

Keywords

Mapping; Topological; Quantum Circuits; Physical Hardware; In silico; Anticancer Peptide; SVS-1 multipharmacophore; drug-like; efficator; Preceding Membrane; Neutralization; algorithmic approach; biclustering analysis; expression data;

Abstract

Anticancer peptides (ACPs) are polycationic amphiphiles capable of preferentially killing a widespectrum of cancer cells relative to non-cancerous cells. Their primary mode of action is aninteraction with the cell membrane and subsequent activation of lytic effects, however it remainscontroversial the exact mechanism responsible for this mode of action. It has in previous studies been shown that utilizing zeta potential analyses it was possible to demonstrate the interaction of a small anticancer peptide with membrane modelsystems and cancer cells. Electrostatic interactions have a pivotal role in the cell killing processand in contrast to the AMPs action cell death occurs without achieving full neutralization of themembrane charge. The advent of microarray technology has revolutionized the search for genes that are differentially expressed across a range of cell types or experimental conditions. Traditional clustering methods, such as hierarchical clustering, are often difficult to deploy effectively since genes rarely exhibit similar expression pattern across a wide range of conditions. Web-enabled service called GEMS (Gene Expression Mining Server) for biclustering microarray data where Users may upload expression data and specify a set of criteria.GEMS performs bicluster mining based on a Gibbs sampling paradigm. Here, in Biogenea we have for the first time discovered an In silico designed multi-mimotopic algorithmic approach for biclustering analysis of an Anticancer Peptide SVS-1 multipharmacophore expression data as a potential drug-like efficator in Preceding Membrane Neutralization.

Abstract

Background

Molecular Mechanics (MM) is the method of choice for computational studies of biomolecular systems owing to its modest computational cost, which makes it possible to routinely perform molecular dynamics (MD) simulations on chemical systems of biophysical and biomedical relevance.Abstract: Inflammatory Th1 cells reacting to tissue/myelin derived antigens likely contribute to the pathogenesis of diseases such as multiple sclerosis (MS), rheumatoid arthritis (RA), and psoriasis. One regulatory mechanism that may be useful for treating autoimmune diseases involves an innate second set of Th2 cells specific for portions of the T cell receptor of clonally expanded pathogenic Th1 cells. These Th2 cells are programmed to respond to internally modified V region peptides from the T cell receptor (TCR) that are expressed on the Th1 cell surface in association with major histocompatibility molecules. TB Mobile can now manage a small collection of compounds that can be imported from external sources, or exported by various means such as email or app-to-app inter-process communication. This means that TB Mobile can be used as a node within a growing ecosystem of mobile apps for cheminformatics. It can also cluster compounds and use internal algorithms to help identify potential targets based on. Here, in Biogenea we have for the first time discovered CHARMM additive and polarizable force fields for biophysics and computer-aided drug design rational approach for the in silico generation of a TCR Peptide Mimetic Pharmacoligand as a potential chemo-modulator in Human Autoimmune Diseases.

Keywords

CHARMM additive; polarizable force fields; biophysics; computer-aided; drug design; Computer-aided; rational approach; in silico; TCR Peptide; Mimetic; Pharmacoligand; chemo-modulator; Human Autoimmune Diseases;.molecular dynamics; empirical force field; potential energy function; molecular mechanics;

Abstract

We study two particle quantum walks on one dimensional chain. Probability distribution of two particle quantum walks is dependent on the initial state, and symmetric quantum walk or asymmetric quantum walk is analogous to that of one particle quantum walk. The quantum correlation probability is much different from classical coincidence probability. In this paper the difference reflects quantum interference between two particles as a Quantum Walk of Two Quantum Particles on One computer-aided drug design rational Dimensional System for the in silico generation of a TCR Peptide Mimetic Pharmacoligand as a potential chemo-modulator in Human Autoimmune Diseases.

Keywords

Quantum Walk; Two Quantum Particles; Dimensional System; computer-aided; drug design; Computer-aided; rational approach; in silico; TCR Peptide Mimetic; Pharmacoligand; chemo-modulator; Human Autoimmune Diseases;

Abstract

In weak measurement thought experiment, an ensemble consists of M quantum particles and N states. We observe that separability of the particles is lost, and hence we have fuzzy occupation numbers for the particles in the ensemble. Without sharply measuring each particle state, quantum interferences add extra possible configurations of the ensemble, this explains the Quantum Pigeonhole Principle. This principle adds more entropy to the system; hence the particles seem to have a new kind of correlations emergent from particles not having a single, well-defined state. We formulated the Quantum Pigeonhole Principle in the language of abstract Hilbert spaces, then generalized it to systems consisting of mixed states. This insight into the fundamentals of quantum statistical mechanics could help us understand the interpretation of quantum mechanics more deeply, and possibly have implication on quantum computing and information theory as Computer rational Statistical Mechanics for Weak Measurements and Quantum computer-aided drug design Inseparabilities for the in silico generation of a TCR Peptide Mimetic Pharmacoligand as a potential chemo-modulator in Human Autoimmune Diseases.

Keywords

Statistical Mechanics; Weak Measurements; Quantum Inseparability;computer-aided; drug design; Computer-aided; rational approach; in silico; TCR Peptide Mimetic; Pharmacoligand; chemo-modulator; Human Autoimmune Diseases;Quantum Computing, Copenhagen Interpretation, Quantum Pigeonhole Principle, Quantum Correlation, Information Theory, Quantum Statistical Mechanics, Weak Measurement, Quantum Measurement, Post Selection1.

Abstract

We investigate a quantum communication protocol, of so-called approximate quantum state sharing (AQSS), that protocol is basically based on pair of private quantum channels. In this paper, we prove that the scheme is secure against any external and internal attacks of wiretapping in principle. Although the protocol leaks small amount of information corresponding to a security parameter, of the scheme of the Quantum State Sharings approximations via Pair of Private Quantum In silico designed Channels of an Anticancer Peptide SVS-1 multipharmacophore as a potential drug-like efficator in Preceding Membrane Neutralization. still preserves its information-theoretic security.

Keywords

Quantum State Sharings; Pair of Private; Quantum Channels; In silico designed; Anticancer Peptide; SVS-1; multipharmacophore; drug-like; efficator; Preceding Membrane Neutralization;

Abstract

It is of great interest in modern drug design to accurately calculate the free energies of protein-ligand or nucleic acid-ligand binding. MM-PBSA (Molecular Mechanics-Poisson Boltzmann Surface Area) and MM-GBSA (Molecular Mechanics-Generalized Born Surface Area) have gained popularity in this field. For both methods, the conformational entropy, which is usually calculated through normal mode analysis (NMA), is needed to calculate the absolute binding free energies. Unfortunately, NMA is computationally demanding and becomes a bottleneck of the MM-PB/GBSA-NMA methods. In this work, we have developed a fast approach to estimate the conformational entropy based upon solvent accessible surface area calculations. In our approach, the conformational entropy of a molecule, S, can be obtained by summing up the contributions of all atoms, no matter they are buried or exposed. Each atom has two types of surface areas, solvent accessible surface area (SAS) and buried SAS (BSAS). The two types of surface areas are weighted to estimate the contribution of an atom to S. Atoms having the same atom type share the same weight and a general parameter k is applied to balance the contributions of the two types of surface areas.

Keywords

In silico; Anticancer Peptide; SVS-1; multipharmacophore; drug-like; efficator; Preceding; Membrane Neutralization; multi-mimotopic; algorithmic approach; biclustering analysis; expression data; Develop and Test; Solvent Accessible; Surface Area-Based Model; Conformational Entropy; Calculations; Conformational Entropy, Configurational Entropy, WSAS, Solvent Accessible Surface Area, MM-PBSA, MM-GBSA, Binding Free Energy Calculations, Protein Design, Drug Design.

Abstract

This paper focuses on the geometric modeling and computational algorithm development of biomolecular structures from two data sources: Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in the Eulerian (or Cartesian) representation. Molecular surface (MS) contains non-smooth geometric singularities, such as cusps, tips and self-intersecting facets, which often lead to computational instabilities in molecular simulations, and violate the physical principle of surface free energy minimization. Variational multiscale surface definitions are proposed based on geometric flows and solvation analysis of biomolecular systems. Our approach leads to geometric and potential driven Laplace-Beltrami flows for biomolecular surface evolution and formation. The resulting surfaces are free of geometric singularities and minimize the total free energy of the biomolecular system. High order partial differential equation (PDE)-based nonlinear filters are employed for EMDB data processing. We show the efficacy of this approach in feature-preserving noise reduction. After the construction of protein multiresolution surfaces, we explore the analysis and characterization of surface morphology by using a variety of curvature definitions. Apart from the classical Gaussian curvature and mean curvature, maximum curvature, minimum curvature, shape index, and curvedness are also applied to macromolecular surface analysis for the first time. Our curvature analysis is uniquely coupled to the analysis of electrostatic surface potential, which is a by-product of our variational multiscale solvation models. As an expository investigation, we particularly emphasize the numerical algorithms and computational protocols for practical applications of the above multiscale geometric models. Such information may otherwise be scattered over the vast literature on this topic. Based on the curvature and electrostatic analysis from our multiresolution surfaces, we introduce a new concept, the polarized curvature, for the prediction of protein binding sites.Keloids result from aberrations in the normal wound healing cascade and can lead to pruritus, contractures and pain. The underlying mechanisms of excessive scarring are not yet understood, and most therapeutic strategies remain unsatisfactory. Psoriasin (S100A7) and koebnerisin (S100A15) are released by keratinocytes during physiological wound healing. Psoriasin (S100A7) and koebnerisin (S100A15) are released by keratinocytes during physiological wound healing. S100 production is markedly decreased in keloid scar tissue. The disturbed epidermal S100 expression might contribute to keloid formation; thus, it has been previously studied their effect on dermal fibroblasts and extracellular matrix (ECM) production. Here, in Biogenea Pharmaceuticals Ltd we discovered for the first time the GENEA-AntiPsorerisin-10715 utilising Multiscale geometric modeling of macromolecules I: Cartesian representation Quantum-SAR Extension of the Spectral-SAR Algorithm Application to Polyphenolic Anticancer Bioactivity through a decision-tree induction algorithm-based Drug Discovery, homology modeling, hierarchical docking and virtual screening approaches of Antimicrobial Peptide-mimetic Psoriasin (S100A7) and Koebnerisin (S100A15) high binding free energy pharmacophoric hyper-scaffolds as a novel synthetic pharmaco-ligand with potential inhibitory activities for the Suppression of the Extracellular Matrix Production and Proliferation of Human Fibroblasts.

Keywords

Protein characterization, Variational multiscale surfaces, Curvature analysis, High order geometric PDEs, Free energy functional, EMDataBank, Protein data bank, Multiscale geometric modeling of macromolecules I, Cartesian representation, Quantum-SAR Extension, Spectral-SAR Algorithm, decision-tree, induction, algorithm-based, Drug Discovery, homology modeling, hierarchical docking and virtual screening approaches to identify the known ligand binding cavities for slingshot phosphatase pharmacophoric-peptide mimetic inhibitors. in silico, rational, computer-aided, Antimicrobial Peptide-mimetic, Psoriasin (S100A7), Koebnerisin (S100A15), high binding free energy, pharmacophoric, hyper-scaffolds, synthetic pharmaco-ligand, inhibitory activities, Suppression Extracellular Matrix, Production, Proliferation, Human Fibroblasts,

Abstract

During foundation stages, interior design students are faced difficulties in mental perception of the relationship between matching two-dimensional drawings and expressive design ideas, especially when designing compositions and building relationships between design elements. The purpose of this study is to determine what is the teaching strategy that enables students to perceive relations between ideas of design and their foundations of projection during the foundation stage? The researcher has come up with basic steps enabling students to project their design’s ideas easily. Each stage of these stages is dependent on self-assessment criteria, certified as a reference, to be assigned to students and allow them to link the theoretical findings with practical work. The purpose of this study is to determine what is the teaching strategy that enables students to perceive relations between ideas of design and their foundations of projection during the foundation stage? The researcher has come up with three basic steps enabling students to project their design’s ideas easily, and gradually perceives the concept of building relationships between the design’s idea and foundations of their projections in the foundation stage. These steps are represented in the stage of sketching the composition prior to their embodiment (cutting paper template), the stage of alternate adjustment of embodiment and sketching, and finally the stage of sketching composition after their embodiment Proposed Strategy in Teaching Design Fundamentals for Understanding the Relationship between Idea and Idea’s Projection of an in silico rational computer-aided designed Antimicrobial Peptide-mimetic Psoriasin (S100A7) and Koebnerisin (S100A15) high binding free energy pharmacophoric hyper-scaffolds as a novel synthetic pharmaco-ligand with potential inhibitory activities for the Suppression of the Extracellular Matrix Production and Proliferation of Human Fibroblasts.

Keywords

Proposed Strategy; Teaching Design Fundamentals; Relationship; Idea’s Projection; in silico, rational computer-aided, Antimicrobial Peptide-mimetic; Psoriasin (S100A7); Koebnerisin (S100A15); high binding free energy; pharmacophoric; hyper-scaffolds; synthetic pharmaco-ligand; inhibitory activities; Suppression; Extracellular Matrix; Production; Proliferation; Human Fibroblasts;Design, Teaching, Strategy, Studio, Sketching