Abstract

Molecular dynamics (MD) simulation is an emerging in silico technique with potential applications in diverse areas of pharmacology. Over the past three decades MD has evolved as an area of importance for understanding the atomic basis of complex phenomena such as molecular recognition, protein folding, and the transport of ions and small molecules across membranes. The application of MD simulations in isolation and in conjunction with experimental approaches have provided an increased understanding of protein structure-function relationships and demonstrated promise in drug discovery. In this study, Molecular dynamics simulations are applied from structure function relationships to αn advanced fragment-based multi-dimensional chemico-informatic drug discovery approach on a ex vivo derivation and expansion of human neuropoietic cell progenitors using highly conserved poly-peptidomimic linked-pharmacophores targeted to neural pathways for neurodegenerative disease modeling.

Keywords

Molecular dynamics, simulations, structure, function relationships, drug discovery, Ex vivo, derivation, expansion, human neuropoietic cell progenitors, highly conserved poly-peptidomimic, linked-pharmacophores, neural pathways, neurodegenerative, disease modeling, advanced fragment-based, multi-dimensional, chemico-informatic, approach, molecular dynamics simulations, Cytochrome P450, Drug-drug interactions, Genetic polymorphism, Drug design, Allosteric binding sites, Cryptic binding sites.

Abstract

The existence of any elementary particle in universe requires the existence of some region of universe occupied by it. By taking the volume of this occupied region, the author will reformulate the relativistic quantum field theory using new 3-dimensional region-like idealization of elementary particles and hereinafter will call the total volume of all regions occupied by the elementary constituent particles of the quantum system the occupied volume. Also the author will call the set of all regions of universe filled by elementary constituent particles of the quantum system the occupied path. Always any quantum system is existed at a head of its occupied path. This path is growing by mutual filling and leaving regions of universe by its elementary constituent particles. The conservation of this elementary constituent particle requires the conservation of its occupied volume during this process. This requirement could be summarized by the following conditions: 1) the total volume of all regions of universe filled by the elementary constituent particles of the quantum system minus the total volume of all regions of universe left by these elementary constituent particles must be equal to the occupied volume of the quantum system; 2) the total increase in the occupied volume of the quantum system due to the absorption of another elementary particles from outside its occupied regions minus the total decreasing in its occupied volume due to the emission of another elementary particles outside its occupied regions must be equal to the occupied volume of human neuropoietic cell progenitors using highly conserved poly-peptidomimic linked-pharmacophores targeted to neural pathways for neurodegenerative disease modeling. An advanced fragment-based multi-dimensional chemico-informatic approach The wave-particle duality of the elementary constituent particles implied accumulation of them as the finite set of interfered waves. This accumulation of elementary constituent particles causes the absolute probabilistic nature of event of finding the elementary consistent particle in specified interfered wave, and hence the mathematical representation of this interfered wave should take into account the value of probability amplitude of finding an elementary particle inside the region occupied specified interfered wave. In quantum theory this probability amplitude corresponds to complex amplitude of the wave function of interfered wave. Also in Hilbert’s representation of the quantum theory these wave functions are representing the components of the quantum state vector. In this paper the author will develop the transformation theory of the region-like quantum state of the quantum system for the Reformulation of Relativistic Quantum Field Theory using an advanced fragment-based multi-dimensional chemico-informatic Region-Like Idealization approach of the ex vivo derivation and expansion of Eeentary Particle human neuropoietic cell progenitors on highly conserved poly-peptidomimic linked-pharmacophores targeted to neural pathways for neurodegenerative disease modeling.

Keywords

Reformulation of Relativistic Quantum Field Theory Using Region-Like Idealization of the Elementary ParticleEx vivo derivation and expansion of human neuropoietic cell progenitors using highly conserved poly-peptidomimic linked-pharmacophores targeted to neural pathways for neurodegenerative disease modeling. An advanced fragment-based multi-dimensional chemico-informatic approach, Region-Like Idealization, Creation, Annihilation, Animation, Occupied Volume, Occupied Path, Relativistic Quantum Field Theory,

Abstract

Molecular dynamics (MD) simulation is an emerging in silico technique with potential applications in diverse areas of pharmacology. Over the past three decades MD has evolved as an area of importance for understanding the atomic basis of complex phenomena such as molecular recognition, protein folding, and the transport of ions and small molecules across membranes. In this study the application of MD simulations in isolation and in conjunction with experimental approaches have provided an increased understanding of protein structure-function relationships and demonstrated promise in drug discovery of a novel multi-chemo-structure super-agonistic CellshOX Decoy Peptide Mimetic Construct as a Human Umbilical Cord blood Stem Cell Expansion Molecule in a QSAR automating modeling lead compound design approach.

Keywords

Molecular dynamics simulations, structure, function relationships, drug discovery, in silico discovery, novel multi-chemo-structure, super-agonistic, CellshOX, Decoy Peptide, Mimetic Construct, Human Umbilical, Cord blood, Stem Cell Expansion, Molecule, QSAR automating modeling, lead compound, design approach.

Abstract

In this paper, I shall sketch a new way to consider a Lindenbaum-Tarski algebra as a 3D logical space in which any one (of the 256 statements) occupies a well-defined position and it is identified by a numerical ID. This allows pure mechanical computation both for generating rules and inferences. It is shown that this abstract formalism can be geometrically represented with logical spaces and subspaces allowing a vectorial representation. Finally, it shows the application to quantum computing through the example of three coupled harmonic oscillators of a novel multi-chemo-structure super-agonistic CellshOX Decoy Peptide Mimetic Construct as a Human Umbilical Cord blood Stem Cell Expansion Molecule in a QSAR automating modeling lead compound design approach.

Keywords

Lindenbaum-Tarski Algebra; 3D Logical Space; Mechanical Computation; Inference; Quantum Computing; Raising Operators; Lowering Operators; Implement Quantum Computation; In silico discovery; multi-chemo-structure; super-agonistic; CellshOX; Decoy Peptide; Mimetic Construct; Human Umbilical Cord blood; Stem Cell Expansion Molecule; QSAR automating modeling; lead compound; design approach;

Abstract

A kind of novel three-party quantum secure direct communication protocol is proposed with the correlation of two-particle entangled state. In this scheme the qubit transmission forms a closed loop and every one of the three participants is both a receiver and a sender of particle sequences in the bidirectional quantum channels. Each party implements the corresponding unitary operations according to its secret bit value over the quantum channels and then extracts the other two parties’ unitary operations by performing Bell measurements on the encoded particles. Thus they can obtain the secret information simultaneously. Finally, our security analysis in this paper shows that the present three-party scheme is a secure in silico discovery protocol of a novel multi-chemo-structure super-agonistic CellshOX Decoy Peptide Mimetic Construct as a Human Umbilical Cord blood Stem Cell Expansion Molecule in a QSAR automating modeling lead compound design approach.

Keywords

Three-Party Simultaneous; Quantum Secure Communication Based; Closed TransmissionI; n silico discovery; novel multi-chemo-structure; super-agonistic; CellshOX Decoy; Peptide Mimetic; Construct; Human Umbilical Cord blood; Stem Cell Expansion Molecule; QSAR automating modeling; lead compound design approach;

Abstract

Molecular simulation is increasingly demonstrating its practical value in the investigation of biological systems. Computational modelling of biomolecular systems is an exciting and rapidly developing area, which is expanding significantly in scope. A range of simulation methods has been developed that can be applied to study a wide variety of problems in structural biology and at the interfaces between physics, chemistry and biology. Here, we give an overview of methods and some recent developments in atomistic biomolecular simulation. Some recent applications and theoretical developments are highlighted.Biomolecular simulation and modelling: status, progress and prospects on a Computational mining Biomolecular simulation modelling 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

Biomolecular simulation΄; modelling status; progress; prospects; computational mining approach; combined molecular docking-based; pharmacophore-based; target prediction strategy; probabilistic fusion method; target ranking; anti-HIV-I; P24-derived; peptide mimic; pharmacophores; biomolecular simulation; molecular modelling; molecular dynamics; force fields; quantum mechanics/molecular mechanics; quantum chemical modelling

Abstract

We discuss the fact that there is a crucial contradiction within Von Neumann’s theory. We derive a proposition concerning a quantum expected value under an assumption of the existence of the orientation of reference frames in N spin-1/2 systems (1 ≤ N < +∞). This assumption intuitively depictures our physical world. However, the quantum predictions within the formalism of Von Neumann’s projective measurement violate the proposition with a magnitude that grows exponentially with the number of particles. We have to give up either the existence of the directions or the formalism of Von Neumann’s projective measurement. Therefore, Von Neumann’s theory cannot depicture our physical world with a violation factor that grows exponentially with the number of particles. The theoretical formalism of the implementation of the Deutsch-Jozsa algorithm relies on Von Neumann’s theory. We investigate whether Von Neumann’s theory meets the Deutsch-Jozsa algorithm. We discuss the fact that the crucial contradiction makes the quantum-theoretical formulation of Deutsch-Jozsa algorithm questionable. Further, we discuss the fact that projective measurement theory does not meet an easy detector model for a single Pauli observable. Especially, we systematically describe our assertion based on more mathematical analysis using raw data. We propose a solution of the problem. Our solution is equivalent to changing Planck’s constant (h) to a new constant. It may be said that a new type of the quantum theory early approaches Newton’s theory in the macroscopic scale than the old quantum theory does. We discuss how our solution is used in an implementation of Von Neumann’s Theory, Projective Measurement and Quantum Computation Computational mining combined molecular docking-based and pharmacophore-based approach as a target prediction strategy through a probabilistic fusion method for target ranking of anti-HIV-I P24-derived peptide mimic promising pharmacophores.

Keywords

Von Neumann’s Theory; Projective Measurement; Quantum Computation; Computational mining approach; combined molecular docking-based; pharmacophore-based; target prediction strategy; probabilistic fusion method; target ranking; anti-HIV-I P24-derived; peptide mimic; promising pharmacophores; Quantum Computation; Quantum Measurement Theory; Formalism;

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 Von Neumann’s Theory Projective Measurement Quantum Computational mining combined molecular docking and pharmacophore-based approach on Molecular Dynamics Simulations of the DNA-CNT Interaction Process to Hybrid Quantum Chemistry Potential and Classical Trajectory prediction strategies through a probabilistic fusion method for target ranking of anti-HIV-I P24-derived peptide mimic promising pharmacophores possible use of the DNA-CNT complex as a candidate material in drug delivery and related systems.

Keywords

Molecular Dynamics Simulations; DNA-CNT Interaction Process; Hybrid Quantum; Chemistry Potential; Classical Trajectory; Approach; Von Neumann’s Theory; Projective Measurement; Quantum Computation; Computational mining approach; combined molecular; docking-based; pharmacophore-based; target; prediction strategy; probabilistic fusion method; target ranking; anti-HIV-I P24-derived peptide; mimic promising pharmacophores;

Abstract

ASARM-peptides are substrates and ligands for PHEX, the gene responsible for X-linked hypophosphatemic rickets (HYP). PHEX binds to the DMP1-ASARM-motif to form a trimeric-complex with α5β3-integrin on the osteocyte surface and this suppresses FGF23 expression. ASARM-peptide disruption of this complex increases FGF23 expression. A 4.2kDa peptide (SPR4) has been previously used that binds to ASARM-peptide and ASARM-motif to DMP1-PHEX interact and by assessing SPR4 for treating inherited hypophosphatemic rickets. Here, we discovered for the first time the GENEA-Bonespemitron-5527, a Computer-aided designed of a SPR4-peptide-mimetic pharmacophoric super-agonist for the regulation of bone metabolism utilizing Computational modelling of biomolecular simulation methods in structural biology interfaces between physics, chemistry and biology on an atomistic scalable literature computer-based discovery of an annotated SPR4-peptide-similar multi-molecular pharmacophoric reverse docked super-agonist scaffold as a canditate bone metabolism regulator.

Keywords

SPR4 peptide mimetic; pharmacophoric; super agonist; regulation; bone-metabolism; scalable Literature Based; β-catenin; Computational modelling; biomolecular systems; simulation methods; structural biology; interfaces; physics chemistry and biology in atomistic biomolecular simulation scalable literature;

Abstract

Static and dynamic models (incorporating the time course of the inhibitor) were assessed for their ability to predict drug–drug interactions (DDIs) using a population-based ADME simulator (Simcyp®V8). In this study we analyse the impact of bone active metabolites, dosing time and the ability to predict inter-individual variability in DDI magnitude were investigated using assessments of comparison of dynamic and static algorithmic models for predicting drug–drug interactions via inhibition mechanisms for a scalable literature Computer-based discovery of an annotated SPR4-peptide-similar multi-molecular reverse docked super-agonist pharmacophoric scaffold as a canditate bone metabolism regulator.

Keywords

Assessment algorithms; predicting drug–drug interactions; via inhibition mechanisms; comparison; dynamic; static models; scalable literature; Computer-based discovery; annotated SPR4-peptide-similar; multi-molecular pharmacophoric; reverse docked; super-agonist scaffold; canditate regulator; bone metabolism;