Abstract

The Schrödinger perturbation energy for an arbitrary order N of the perturbation has been presented with the aid of a circular scale of time. The method is of a recurrent character and developed for a non-degenerate quantum state. It allows one to reduce the inflation of terms necessary to calculate known from the Feynman’s diagrammatical approach to a number below that applied in the original Schrödinger perturbation theory. Gene therapy using RNA interference (RNAi) technology has been explored to treat cancers, by regulating the expression of oncogene. However, even though small interfering RNA (siRNA), which triggers RNAi, may have great therapeutic potential, efforts at using them in vivo have been hampered by the difficulty of effective and safe delivery into cells of interest. Safe and efficient carrier for in vitro and in vivo siRNA delivery have been also developed by designed peptide libraries. These peptides are improved variants of a known peptide based siRNA carrier C6. Dark energy is shown to be the absolute value of the negative kinetic energy of the halo-like quantum wave modeled mathematically by the empty set in a five dimensional Kaluza-Klein (K-K) spacetime. Ordinary or position energy of the particle on the other hand is the dual of dark energy and is contained in the dynamic of the quantum particle modeled by the zero set in the same five dimensional K-K spacetime. The sum of both dark energy of the wave and the ordinary energy of the particle is exactly equal to the energy given by the well known formula of Einstein which is set in a four dimensional spacetime. Various interpretations of the results are presented and discussed based on the three fundamental energy density equations developed. In particular where E is the energy, m is the mass and c is the speed of light, is Hardy’s quantum entanglement and gives results in complete agreement with the cosmological measurements of WMAP and Supernova. On the other hand gives an intuitive explanation of negative gravity and the observed increased rate of cosmic expansion. Adding to one finds which as we mentioned above is Einstein’s famous relativity formula. We conclude that similar to the fact that the quantum wave interpreted generally as probability wave which is devoid of ordinary energy decides upon the location of a quantum particle, it also exerts a negative gravity effect on the cosmic scale of our clopen, i.e. closed and open universe. Analysis and conclusions are framed in a reader friendly manner in Figures 1-14 with detailed commentary Quantum Entanglement Dark Energy and Negative Gravity measurements plus Circular Scale of quantitative structure-activity relationship time as a Way of Calculating the Quantum-Mechanical Perturbation Energy Given by the Schrödinger Method with novel Stanisław Olszewski Accelerated Expansion Universe automated lazy learning modelings for the generation of pharmacophore-based custom fingerprinting of high quality atom encoding Endosomolytic Peptide-mimetic agent as siRNA carrier.

Keywords

Evaluation, Endosomolytic Biocompatible, Peptide-mimetic, Pharmacophores, Carriers, siRNA Delivery, Quantum-Mechanical Perturbation Energy, Circular Scale of Time1, Dark Kinetic Energy of the Quantum Wave; Ordinary Position Energy Quantum Particle; Anti Gravity; Negative Curvature; Collapse; Hawking-Hartle; Quantum Wave; Universe; Revising Einstein’s Relativity; Quantum Gravity;

Abstract

Cancer has become a great concern in public health. The harmful side effects and multidrug resistance of traditional chemotherapy prompt urgent needs for novel anticancer drugs or therapeutic approaches. Anticancer peptides (ACPs) have become promising molecules as new anticancer agents due to the unique mechanism and several extraordinary properties. Most α-helical ACPs target on cell membrane and the interactions between ACPs and cell membrane components are believed to be a key factor in the selective killing of cancer cells. As a result we discovered for the first time the GENEA-Alphecanitir-4846, an Alpha-Helical Cationic Anticancer Peptide-mimetic Pharmacophore as a promising candidate novel anticancer drug like scaffold utilizing α Survey of Quantum Lyapunov Control maximum common substructure-based support vector machine algorithmic methods for the Fragment based drug discovery of drug like optimized Alpha-Helical Cationic Anticancer Peptide-mimetic annotated Pharmacophore.

Keywords

A Survey of Quantum Lyapunov Control maximum common substructure-based support vector machine algorithmic Methods for the Fragment based drug discovery of drug like optimized Alpha-Helical Cationic Anticancer Peptide-mimetic annotated Pharmacophore.

Abstract

The condition of a quantum Lyapunov-based control which can be well used in a closed quantum system is that the method can make the system convergent but not just stable. In the convergence study of the quantum Lyapunov control, two situations are classified: nondegenerate cases and degenerate cases. For these two situations, respectively, in this paper the target state is divided into four categories: the eigenstate, the mixed state which commutes with the internal Hamiltonian, the superposition state, and the mixed state which does not commute with the internal Hamiltonian. For these four categories, the quantum Lyapunov control methods for the closed quantum systems are summarized and analyzed. Particularly, the convergence of the control system to the different target states is reviewed, and how to make the convergence conditions be satisfied is summarized and analyzed a Survey of Quantum Lyapunov Control maximum common substructure-based support vector machine algorithm for the Fragment based drug discovery of drug like optimized Alpha-Helical Cationic Anticancer Peptide-mimetic annotated Pharmacophore.

Keywords

Survey;Quantum Lyapunov Control; Methods; maximum common; substructure-based; support vector; machine algorithm; Fragment based drug discovery; drug like; optimized Alpha-Helical; Cationic Anticancer; Peptide-mimetic; annotated Pharmacophore;

Abstract

Drug discovery is a complex process with the aim of discovering efficacious molecules where their potency and selectivity are balanced against ADMET properties to set the appropriate dose and dosing interval. The link between physicochemical properties and molecular structure are well established. The subsequent connections between physicochemical properties and a drug’s biological behavior provide an indirect link back to structure, facilitating the prediction of a biological property as a consequence of a particular molecular manipulation. Due to this understanding, during early drug discovery in vitro physicochemical property assays are commonly performed to eliminate compounds with properties commensurate with high attrition risks. However, the goal is to accurately predict physicochemical properties to prevent the synthesis of high risk compounds and hence minimize wasted drug discovery efforts.It has long been considered that the most significant risks for breast cancer are gender and age but, as many other tumors, this cancer has also been undeniably linked to gene mutations. The vast majority of breast cancers in postmenopausal women are estrogen-responsive, a hormone which is biosynthesized from blood-circulating androgens through an aromatization reaction, catalyzed by aromatase (AR). Here, in Biogenea Pharmaceuticals Ltd we discovered for the first time the GENEA-Aromahibinir-4492 Quantum algorithms for topological and geometric analysis of computational methods and a metastasis perfomed thermodynamic integration approach for the discovery of a potent aromatase/collagen IV derived biomimetic dual targeted small poly-active compound with future anti-tumor inhibitory activities.

Keywords

Quantum algorithms; topological;geometric analysis; Computational methods; a metastasis; thermodynamic integration; discovery; potent; aromatase/collagen IV; biomimetic; dual targeted; small poly-active; compound; future; anti-tumor; inhibitory activities;

Abstract

We revisit the quantum features of an anti-ferromagnetic (AF) spin environment at finite temperature with gap in its frequency spectrum, on the dynamics quantum correlations of a coupled central two qubits system with Dzyaloshinskii-Moriya (DM) interaction, prepared in two entangled Bell states. Using entanglement and quantum discord as quantum meters of decoherence, the prepared entangled states are classified as robust or fragile relative to the degree of information leakage to the AF environment. By tailoring the size of the frequency gap, anisotropy field strength and induced field, due to system AF spin environment coupling, size of the AF environment and DM interaction parameter, a decoherence-free sub-space can be accessed for efficient execution of quantum protocols encoded in the entangled states Tailoring Quantum Correlations of a Coupled Central Two Qubits Soaked in a Finite Temperature Antiferromagnetic Environment with Frequency Gap the discovery of a potent aromatase/collagen IV derived biomimetic dual targeted small poly-active compound with future anti-tumor inhibitory activities.

Keywords

Tailoring Quantum Correlations; Coupled Central; Two Qubits; Soaked; Finite Temperature; Antiferromagnetic Environment; Frequency Gap; discovery; potent; aromatase/collagen IV; biomimetic; dual targeted; small poly-active compound;

Abstract

The prediction of binding modes (BMs) occurring between a small molecule and a target protein of biological interest has become of great importance for drug development. The overwhelming diversity of needs leaves room for docking approaches addressing specific problems. A Fast docking using the CHARMM force field with EADock DSS for the Implementation of the Hungarian algorithm to account for ligand symmetry and similarity in structure-based design of drug-like molecules by a fragment-based molecular evolutionary approach. HIV-1 P24-derived peptides were examined to predict anti-HIV-1 activity among them. The efficacy of the prediction has already been validated in vitro. Our in silico experimental studies performed on the mentioned peptides, which may lead to new anti-HIV-1 peptide-mimotopic therapeutics candidates. In this research study we presented for the first time a computational approach and a combined molecular docking-based and pharmacophore-based target prediction strategy with a probabilistic fusion method for Quantum Biology on the Edge of Quantum Chaos Computational mining approach, a combined molecular docking-based and pharmacophore-based target prediction strategy through a probabilistic fusion method for target ranking of anti-HIV-I P24-derived peptide mimic promising pharmacophores.

Keywords

Computational prediction, anti-HIV-1 peptide-mimic. Pharmastructures, HIV-1, P24-derived, peptides Quantum Biology on the Edge of Quantum Chaos Computational mining approach, a combined molecular docking-based and pharmacophore-based target prediction strategy through a probabilistic fusion method for target ranking of anti-HIV-I P24-derived peptide mimic promising pharmacophores.

Abstract

In this work the quantum chemistry Tersoff potential in combination with classical trajectory calculations was used to investigate the interaction of the DNA molecule with a carbon nanotube (CNT). The so-called hybrid approach—the classical and quantum-chemical modeling, where the force fields and interaction between particles are based on a definite (but not unique) description method, has been outlined in some detail. In such approach the molecules are described as a set of spheres and springs, thereby the spheres imitate classical particles and the spring the interaction force fields provided by quantum chemistry laws. The Tersoff potential in hybrid molecular dynamics (MD) simulations correctly describes the nature of covalent bonding. The aim of the present work was to estimate the dynamical and structural behavior of the DNA-CNT system at ambient temperature conditions. The dynamical configurations were built up for the DNA molecule interacting with the CNT. The analysis of generated МD configurations for the DNA-CNT complex was carried out. For the DNA-CNT system the observations reveal an encapsulation-like behavior of the DNA chain inside the CNT chain. The discussions were made on possible use of the DNA-CNT complex as a candidate material in drug delivery and related systems Hybrid Quantum Chemistry Molecular Dynamics Simulations of the Classical Trajectory DNA-CNT combined molecular docking-based and pharmacophore-based target prediction strategy through a probabilistic fusion method for target ranking of anti-HIV-I P24-derived peptide mimic promising pharmacophores.

Keywords

Molecular Dynamics; Carbon Nanotube; DNA Molecule; Drug Delivery; DNA-CNT Interaction Quantum Chemistry Potential and Classical Trajectory Approach a combined molecular docking-based and pharmacophore-based target prediction strategy through a probabilistic fusion method for target ranking of anti-HIV-I P24-derived peptide mimic promising pharmacophores.

Abstract

In this paper we outline a non-perturbative quantum relativity theory. Subsequently an actual design of a nanotech energy reactor is based on spacetime vacuum fluctuation of the said quantum relativity theory. Using a compact heap of Fullerene nano particle moduli of a nano matrix device we propose that by maximizing the Casimir forces between these particles as a desirable effect, we can achieve a gradual rather than a sudden implosion pressure. We expect that this will result in a mini holographic universe from which energy can be extracted in a way to constitute a nano energy reactor and function effectively on a hybrid principle somewhere between a Casimir effect and a cold fusion process based on the fusion algebra of a highly structured golden ring quantum field theory. The present theory depends upon many concepts and results, in particular J. Schwinger’s source theory as well as the modern theory of quantum sets, nonlinear dynamics, chaos and chaotic fractals with applications on a Non-Perturbative Quantum Relativity Theory Leading to a Casimir-Dark Energy Nanotech Reactor Proposal on a combined molecular docking-based and pharmacophore-based target prediction strategy through a probabilistic fusion method for target ranking of anti-HIV-I P24-derived peptide mimic promising pharmacophores.

Keywords

Non-Perturbative; Quantum Relativity Theory; Leading Casimir-Dark Energy; Nanotech Reactor; combined; molecular docking-based; pharmacophore-based; target; prediction strategy; probabilistic fusion; ranking; anti-HIV-I P24-derived peptide mimic; promising pharmacophores;

Abstract

As the fundamental theory of quantum information science, recently I proposed the linguistic interpretation of quantum mechanics, which was characterized as the linguistic turn of the Copenhagen interpretation of quantum mechanics. This turn from physics to language does not only extend quantum theory to classical theory but also yield the quantum mechanical world view. Although the wave function collapse (or more generally, the post-measurement state) is prohibited in the linguistic interpretation, in this paper I show that the phenomenon like wave function collapse can be realized. That is, the projection postulate is completely clarified in the Linguistic Interpretation of Quantum Mechanics in a combined molecular docking-based and pharmacophore-based target prediction Projection Postulate Approach strategy-derived peptide mimic promising pharmacophores.

Keywords

Linguistic Interpretation; Quantum Mechanics; Projection Postulate Approach; molecular docking-based; pharmacophore-based; prediction strategy; probabilistic fusion method; ranking; anti-HIV-I P24-derived; peptide mimic; promising pharmacophores;

Abstract

Abstract

Computational molecular design is a useful tool in modern drug discovery. Virtual screening is an approach that docks and then scores individual members of compound libraries. In contrast to this forward approach, inverse approaches construct compounds from fragments, such that the computed affinity, or a combination of relevant properties, is optimized. We have recently developed a new inverse approach to drug design based on the dead-end elimination and A* algorithms employing a physical potential function. This approach has been applied to combinatorially constructed libraries of small-molecule ligands to design high-affinity HIV-1 protease inhibitors [M. D. Altman et al. J. Am. Chem. Soc. 130: 6099–6013, 2008]. Here we have evaluated the new method using the well studied W191G mutant of cytochrome c peroxidase. This mutant possesses a charged binding pocket and has been used to evaluate other design approaches. The results show that overall the new inverse approach does an excellent job of separating binders from non-binders. For a few individual cases, scoring inaccuracies led to false positives. The majority of these involve erroneous solvation energy estimation for charged amines, anilinium ions and phenols, which has been observed previously for a variety of scoring algorithms. Interestingly, although inverse approaches are generally expected to identify some but not all binders in a library, due to limited conformational searching, these results show excellent coverage of the known binders while still showing strong discrimination of the non-binders. Anti-cytotoxic T-lymphocyte antigen-4 (CTLA-4) antibodies, such as ipilimumab, have generated measurable immune responses to Melan-A, NY-ESO-1, and gp100 antigens in metastatic melanoma. Vaccination against such targets has potential forimmunogenicity and may produce an effector memory T-cell response. It has been previously determined the effect of CTLA-4 blockador on antigen-specific responses following vaccination. In-depth immune monitoring was performed on three ipilimumab-treated patientsprevaccinated with gp100 DNA (IMF-24), gp100209–217 and tyrosinase peptides plus GM-CSFDNA (IMF-32), or NY-ESO-1 protein plus imiquimod (IMF-11). In previous studies it was shown that peripheral blood mononuclearcells were analyzed by tetramer and/or intracellular cytokine staining following 10-day culturewith HLA-A*0201-restricted gp100209–217 (ITDQVPFSV), tyrosinase369–377 (YMDGTMSQV),or 20-mer NY-ESO-1 overlapping peptides, respectively. It has also been evaluated on the PDBbind v2012 core set where istar platform combining with RF-Score manages to reproduce Pearson’s correlation coefficient and Spearman’s correlation coefficient of as high as 0.855 and 0.859 respectively between the experimental binding affinity and the predicted binding affinity of the docked conformation. Here, we have discovered for the first time an in silico predicted and computer-aided molecular designed CTLA-4 (YMDGTMSQV) mimic blockador for the increasement of the antigen-specific CD8+ T-cells to the inprevaccinated patients with melanoma.

Keywords

multifunctional, peptide-mimic;pharma-activechemo-structure-based, neutrophil;immune-defense, hyper-molecule;High-dimension profiling data; multifunctional; peptide-mimic chemo-structure; connecting conserved fragments; neutrophil immune defense; CAP37 protein; in-silico antibacterial; wound-healing; canditate agent.; Quantum dynamics; continuum; proton transport II; Variational solvent-solute interface; Proton transport, Quantum dynamics; Multiscale model, Laplace-Beltrami equation, Poisson-Boltzmann equation, Kohn-Sham equation, Variational principle;