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

Abstract

The Copenhagen interpretation is the most authorized interpretation of quantum mechanics, but there are a number of ideas that are associated with the Copenhagen interpretation. It is certain that this fact is not nec-essarily desirable. Thus, we propose a new interpretation of measurement theory, which is the linguistic as-pect (or, the mathematical generalization) of quantum mechanics. Although this interpretation is superficially similar to a part of so-called Copenhagen interpretation, we show that it has a merit to be applicable to both quantum and classical systems. For example, we utilise Bell’s inequality is broken even in classical sys-tems as a New Interpretation of an in silico rational computer-aided designed Quantum Mechanics 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

Evaluation, Inverse Molecular Design Algorithm, Model Binding Site, In silico predicted, computer-aided molecular designed CTLA-4 blockador, increasement, antigen-specific CD8+ T-cells, inprevaccinated patients, melanoma, new cluster, algorithms, Large-Scale Protein-Ligand Docking experiment, inverse design, scoring function, protein-ligand interaction, cytochrome c peroxidase, dead-end elimination, drug design

Abstract

This paper discusses quantum mechanical schemas for describing waves with non-abelian phases, Fock spaces of annihilation-creation operators for these structures, and the Feynman recipe for obtaining descriptions of particle interactions with external fields applied to predicted chemo-polypharmacophoric agent on Hypercomplex Extensions of a Quantum Theory Bayesian parameter estimation for nonlinear modelling of biological pathways comprising (Propeptide-Fc)/MGF peptide mimicking high free binding energy properties towards Wnt7a/Fzd7 signalling Akt/mTOR anabolic growth IGF-I/PI3K/Akt -I/MAPK/ERK pathways.

Keywords

Hypercomplex Extensions; Quantum Theory; Bayesian parameter estimation; nonlinear modelling; biological pathways; chemo-polypharmacophoric agent; (Propeptide-Fc)/MGF; peptide mimicking; high free binding energy; properties towards Wnt7a/Fzd7 signalling; Akt/mTOR anabolic growth; IGF-I/PI3K/Akt -I/MAPK/ERK pathways; Composition Algebras, Hilbert Spaces, Fock Spaces, Non-Abelian Gauge Fields

Abstract

The insulin-like growth factor-I (IGF-I) is a key regulator of skeletal muscle growth in vertebrates, promoting mitogenic and anabolic effects through the activation of the MAPK/ERK and the PI3K/Akt signaling pathways. Also, these results show that there is a time-dependent regulation of IGF-I plasma levels and its signaling pathways in muscle. The insulin-like growth factor-I (IGF-I) is a key regulatory hormone that controls growth in vertebrates. Particularly, skeletal muscle growth is strongly stimulated by this hormone. IGFI stimulates both proliferation and differentiation of myoblasts, as well as promoting myotube hypertrophy in vitro and in vivo. The mitogenic and anabolic effects of IGF-I on muscle cells are mediated through specific binding with the IGF-I receptor (IGF-IR). This ligand-receptor interaction promotes the activation of two major intracellular signaling pathways, the mitogen-activated protein kinases (MAPKs), specifically the extracellular signal-regulated kinase (ERK), and the phosphatidylinositol 3 kinase (PI3K)/Akt. The MAPK (RAF/MEK/ERK) is a key signaling pathway in skeletal muscle, where its activation is absolutely indispensable for muscle cell proliferation. Biologically active polypeptides derived from the E domain that forms the C-terminus of the insulin-like growth factor I (IGF-I) splice variant known as mechano growth factor which have been demonstrated neuroprotective and cardioprotective properties, as well as the ability to increase the strength of normal and dystrophic skeletal muscle. Ligands selected from phage-displayed random peptide libraries tend to be directed to biologically relevant sites on the surface of the target protein. Protein-peptide interactions form the basis of many cellular processes. Consequently, peptides derived from library screenings often modulate the target protein’s activity in vitro and in vivo and can be used as lead compounds in drug design and as alternatives to antibodies for target validation in both genomics and drug discovery. In this research and science project we for the first time a predicted chemo-polypharmacophoric agent comprising (Propeptide-Fc)/MGF peptide mimicking properties for the possible increasement of the Muscle Mass Fiber Size towards Wnt7a/Fzd7 Signalling to the Akt/mTOR Anabolic Growth IGF-I/PI3K/Akt -I/MAPK/ERK pathways utilising (Propeptide-Fc)/MGF phage-displayed random peptide libraries through a predicted chemo-polypharmacophoric agent Bayesian parameter estimation for nonlinear modelling of biological pathways comprising (Propeptide-Fc)/MGF peptide mimicking of high free binding energy properties towards Wnt7a/Fzd7 signalling Akt/mTOR anabolic growth IGF-I/PI3K/Akt -I/MAPK/ERK pathways.

Keywords

Bayesian parameter estimation; nonlinear modelling; biological pathways; Bayesian parameter estimation; nonlinear modelling; biological pathways; chemo-polypharmacophoric agent; (Propeptide-Fc)/MGF; peptide mimicking; interactive of high free binding energy properties; Wnt7a/Fzd7; Akt/mTOR; anabolic growth; IGF-I/PI3K/Akt -I/MAPK/ERK pathways;

Abstract

Parameter estimation for fractional-order chaotic systems is an important issue in fractional-order chaotic control and synchronization and could be essentially formulated as a multidimensional optimization problem. A novel algorithm called quantum parallel particle swarm optimization (QPPSO) is proposed to solve the parameter estimation for fractional-order chaotic systems. The parallel characteristic of quantum computing is used in QPPSO. This characteristic increases the calculation of each generation exponentially. The behavior of particles in quantum space is restrained by the quantum evolution equation, which consists of the current rotation angle, individual optimal quantum rotation angle, and global optimal quantum rotation angle. Numerical simulation based on several typical fractional-order systems and comparisons with some typical existing algorithms show the effectiveness and efficiency of the proposed algorithm.L Saint Louis encephalitis virus, a member of the $aviviridae subgroup, is a culex mosquito-borne pathogen. Despite severe epidemic outbreaks on several occasions, not much progress has been made with regard to an epitope-based vaccine designed for Saint Louis encephalitis virus. Covalent binding is an important mechanism for many drugs to gain its function. Computational algorithms to model this chemical event and extended it to a web server have been previously generated. The CovalentDock Cloud provides a simple yet user-friendly web interface to perform covalent docking experiments and analysis online. The web server accepts the structures of both the ligand and the receptor uploaded by the user or retrieved from online databases with valid access id. It identifies the potential covalent binding patterns, carries out the covalent docking experiments and provides visualization of the result for user analysis. Here, in Biogenea we have discovered for the first time a Computational Parameter Estimation of Fractional-Order Chaotic Systems by Using Quantum Parallel Particle Swarm Optimization Algorithm Assay to Design an Epitope-Based Mimo-Peptidic hyper agonist consisting of linked active Pharmacophoric chemo-Scaffolds comprising in silico demonstrated vaccine-like potential properties against Saint Louis Encephalitis Virus conserved binding domains.

Keywords

Parameter Estimation of Fractional-Order Chaotic Systems by Using Quantum Parallel Particle Swarm Optimization Algorithm A Computational Assay to Design an Epitope-Based Mimo-Peptidic hyper agonist consisting of linked active Pharmacophoric chemo-Scaffolds comprising in silico demonstrated vaccine-like potential properties against Saint Louis Encephalitis Virus conserved binding domains.

Abstract

We investigate the quantum discord of a two-qubit anisotropy XXZ Heisenberg chain with Dzyaloshinskii-Moriya (DM) interaction under magnetic field. It is shown that the quantum discord highly depends on the system’s temperature T, DM interaction D, homogenous magnetic field B and the anisotropy Δ. For lower temperature T, by modulating D and B, the quantum discord can be controlled and the quantum discord switch can be realized. Wilms’ Tumour 1 (WT1) is a zinc finger transcription factor that is overexpressed in acute myeloid leukaemia (AML). Its restricted expression in normal tissues makes it a promising target for novel immunotherapies aiming to accentuate the cytotoxic T lymphocyte (CTL) response against AML. It has been previously reported a phase I/II clinical trial of subcutaneous peptide vaccination with two separate HLA-A2-binding peptide epitopes derived from WT1, together with a pan-DR binding peptide epitope (PADRE), in Montanide adjuvant. Here, in Biogenea we have for the first time discovered an in silico Quantum Discord of a Two-Qubit Anisotropy XXZ Heisenberg Chain with Dzyaloshinskii-Moriya Interactions on a designed Fusion Inhibitor consisting of five cancer filtered conserved pharmacophoric chemical fragments with Greatly Promising Pharmaco-Mimic Properties to a Rationally Engineered Wilms’ Tumor Peptide as a future computer generated hyper-molecule for the potential treatment of the acute myeloid leukemia.

Keywords

in silico; Fusion Inhibitor; cancer filtered; conserved pharmacophoric; chemical fragments; Pharmaco-Mimic; Rationally Engineered; Wilms’ Tumor; Peptide; computer generated; hyper-molecule; acute myeloid leukemia;Quantum Discord, Heisenberg Chain, Dzyaloshinskii-Moriya Interaction, Anisotropy, Magnetic Field

Abstract

It has been shown that the Oral administration for 6 days of 100 mg/kg MMK-1, of an agonist peptide selective for the FPRL1 receptor, suppressed alopecia induced by the anticancer drug etoposide in neonatal rats. However, the anti-alopecia effect of orally administered MMK-1 was inhibited by indomethacin, an inhibitor of cyclooxygenase (COX), or AH-23848B, an antagonist of the EP4 receptor for prostaglandin (PG) E2, suggesting involvement of PGE2 release and the EP4 receptor in the oral MMK-1 anti-alopecia mechanism. The anti-alopecia effect of orally administered MMK-1 was also blocked by an inhibitor of nuclear factor-kappaB (NF-kappaB), pyrrolidine dithiocarbamate, suggesting that the oral anti-alopecia effect of MMK-1 may be mediated by activation of NF-kappaB. These results suggested that MMK-1 bound to FPRL1 receptor might suppress etoposide-induced apoptosis of hair follicle cells and alopecia by way of PGE2 release and NF-kappaB activation. Previously, it has also been found that an intraperitoneally administered chemotactic peptide, N-formyl-Met-Leu-Phe (fMLP), and MMK-1, a selective agonist of formyl peptide receptor-like 1 (FPRL1) receptor, the low affinity subtype of the fMLP receptor, prevented the alopecia in neonatal rats induced by the anticancer agent etoposide. The anti-alopecia effect of fMLP was not inhibited at all by Boc-FLFLF, a selective antagonist of formylpeptide receptor (FPR), which is the high affinity subtype of the receptor, but it was partly inhibited by Trp-Arg-Trp-Trp-Trp-Trp-NH(2) (WRW(4)), an antagonist of FPRL1 receptor. The anti-alopecia effects of fMLP and MMK-1 were also inhibited by Lys-D-Pro-Thr (K(D)PT) and pyrrolidine dithiocarbamate, which are inhibitors of interleukin-1 (IL-1) and nuclear factor-kappaB (NF-kappaB) respectively. Computational methods utilizing the structural and functional information help to understand specific molecular recognition events between the target biomolecule and candidate hits and make it possible to design improved lead molecules for the target. 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. Here we represents a massive on-going scientific endeavor to provide a freely accessible state of the art software suite for protein and DNA targeted lead molecule of a Mechanistic in silico molecular recognized approach for the ligand based generation of a dual N-formyl-Met-Leu-Phe (fMLP), and MMK-1peptide mimetic agonists formyl-peptide hyper-agonist interactive receptors against chemotherapy-induced alopecia.

Keywords

mechanistic; in silico; molecular; recognized approach; ligand based; dual N-formyl-Met-Leu-Phe (fMLP), MMK-1peptide mimetic; hyper-agonist; fMLP targeted receptor; PGE2 EP4 pathway; chemotherapy-induced alopecia;

Abstract

In the past decade, it was observed that the relationship between the emerging New Molecular Entities and the quantum of R&D investment has not been favorable. There might be numerous reasons but few studies stress the introduction of target based drug discovery approach as one of the factors. Although a number of drugs have been developed with an emphasis on a single protein target, yet identification of valid target is complex. The approach focuses on an in vitro single target, which overlooks the complexity of cell and makes process of validation drug targets uncertain. Thus, it is imperative to search for alternatives rather than looking at success stories of target-based drug discovery. It would be beneficial if the drugs were developed to target multiple components. New approaches like reverse engineering and translational research need to take into account both system and target-based approach. This review evaluates the strengths and limitations of known drug discovery approaches and proposes alternative approaches for increasing the of Complementary Approaches to Existing Target Based Drug Discovery for Identifying Novel Drug Targets A mechanistic in silico molecular recognized approach for the ligand based generation of a dual N-formyl-Met-Leu-Phe (fMLP), and MMK-1peptide mimetic hyper-agonist fMLP targeted receptor against the PGE2 EP4 pathway chemotherapy-induced alopecia.

Keywords

Complementary Approaches; Existing Target Based; Drug Discovery; Identifying Novel; Drug Targets; mechanistic; in silico; molecular recognized approach; ligand based; dual N-formyl-Met-Leu-Phe (fMLP), MMK-1peptide mimetic; hyper-agonist; fMLP targeted receptor; PGE2 EP4 pathway; chemotherapy-induced alopecia; drug discovery, drug design, drug targets, repositioning, molecular imaging;

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.Survey of Quantum Lyapunov Control MethodsA computer simulated gp100 Peptide mimic designed pharmacophore as a Vaccine-like and Interleukin-2 in silico generated superagonist with potential clinical effect in Patients with Advanced Melanoma using an Improved Algorithm for Chemically Tractable, Semi-Automated Protein Inhibitor Design.Stimulating an immune response against cancer with the use of vaccines remainsa challenge. We hypothesized that combining a melanoma vaccine with interleukin-2, an immuneactivating agent, could improve outcomes. In a previous phase 2 Research Scientific Project, patients with metastaticmelanoma receiving high-dose interleukin-2 plus the gp100:209–217(210M) peptide vaccine hada higher rate of response than the rate that is expected among patients who are treated withinterleukin-2 alone. We here, present an evolutionary algorithm that works in conjunction with existing open-source software to automatically optimize candidate ligands for predicted binding affinity and other druglike properties. We used the rules of click chemistry to guide optimization, greatly enhancing synthesizability. Here, we have for the first time computationally simulated Survey of Quantum Lyapunov Control Methods of a gp100 Peptide pharmacophore mimic Vaccine-like and Interleukin-2 targeted as a in silico generated superagonist with potential clinical effect in Patients with Advanced Melanoma using an Improved Algorithm for Chemically Tractable, Semi-Automated Protein Inhibitor Design.

Keywords

Survey of Quantum Lyapunov; Control Methods; computer simulated; gp100 Peptide; mimic designed pharmacophore; Vaccine-like; Interleukin-2; in silico; superagonist; clinical effect; Patients; Advanced Melanoma; Improved Algorithm; Chemically Tractable;, Semi-Automated Protein Inhibitor Design;