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 of multi-mimotopic algorithmic approach for biclustering analysis of In silico designed expression data on an Anticancer Peptide SVS-1 multipharmacophore as a potential drug-like efficator in Preceding Membrane Neutralization.

Keywords

In silico designed; Anticancer Peptide SVS-1; multipharmacophore; drug-like; efficator in Preceding Membrane Neutralization; multi-mimotopic algorithmic approach; biclustering analysis; expression data.

Abstract

Vitiligo is a skin disorder characterized by selective melanocyte destruction and concomitant appearance of depigmented macules that over time enlarge, coalesce, and form patches. It has been suggested that vitiligo is, at least in part, caused by autoimmune responses mediated by cytotoxic T cells against melanocytes, causing depigmentation Immune responses contribute to the pathogenesis of vitiligo and target melanoma sometimes associated with vitiligo-like depigmentation in some melanoma patients. It has been perviously reported that the tyrosinase autoantigen was immunorecognized with the same molecular pattern by sera from vitiligo and melanoma patients. Five autoantigen peptides was found to compose the immunodominant antityrosinase response: aa95-104FMGFNCGNCK; aa175-182 LFVWMHYY; aa176-190FVWMHYYVSMDALLG; aa222-236IQKLTGDENFTIPYW, and aa233-247IPYWDWRDAEKCDIC. Synergistic therapies for the treatment of vitiligo are provided. The major therapies for the treatment of vitiligo a pigmentary disorder characterized by patchy depigmentation of skin are Psoralens plus UV-A, steroids, basic fibroblast growth factor (bFGF) peptide location or surgical procedures. Psoralens plus UV-A is effective in about 50% of cases, steroids are limitedly effective only in fast spreading cases of vitiligo and often reoccurs on stoppage of treatment. Surgical treatment is the last resort for vitiligo therapy, when all other therapies failed. It is limitedly effective. Basic fibroblast growth factor peptide(s) location was developed as a new mode therapy for the treatment of vitiligo. Therefore, SEQ ID NO: 01 VPHIPPN, SEQ ID NO: 02 MPPTQVS, SEQ ID NO: 03 QMHPWPP, SEQ ID NO: 1 1 LPLTPLP, SEQ ID NO: 12 QLNVNHQARADQ, SEQ ID NO: 13 TSASTRPELHYP, SEQ ID NO: 14 TFLPHQMHPWPP peptides, modified peptides and antibody or antibody fragments inhibiting the activity of MIA and can be used for treating vitiligo by inducing re-pigmentation. Fragment-based lead discovery is a method used for finding lead compounds as part of the drug in silico chemoproteomic prediction-scannings discovery process for the Quantum Dynamics in Continuum for Proton Transport I Basic Formulation of a tyrosinase aa95-104FMGFNCGNCK antigenic patternLFA-3/IgG fusion polypeptide IleAlaArgArgPheLeuOH (Kinetensin) mimetic pharmacophore on conserved Vitiligo post-trancripts domains.

Keywords

Quantum Dynamics; Continuum for Proton Transport I: Basic Formulation; in silico; chemoproteomic prediction-scannings; tyrosinase aa95-104FMGFNCGNCK; antigenic pattern;LFA-3/IgG fusion polypeptide; IleAlaArgArgPheLeuOH (Kinetensin); mimetic pharmacophore ;conserved Vitiligo; post-trancripts domains.

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 Collapsing paradigm of a Perfect Superposition to an in silico Anticancer Peptide SVS-1 multipharmacophore Chosen Quantum State without expression data Measurements of the potential multi-mimotopic algorithmic biclustering analysis of drug-like efficators in Preceding Membrane Neutralization.

Keywords

Collapsing; Perfect Superposition; Chosen Quantum State; Measurement; In silico designed; Anticancer Peptide; SVS-1; multipharmacophore; drug-like; efficator; Preceding Membrane Neutralization; multi-mimotopic; algorithmic approach; biclustering analysis; expression data.

Abstract

Generation of non-classical states of light compatible with atomic quantum memory has been an outstanding challenge driven by various applications in quantum information processing [1]. Various approaches to generation of single photon states compatible with atoms have been pursued [2]: single atoms in free space [3] and in high-finesse cavities [4] and atomic ensembles [5], and non-classical features such as photon antibunching and violation of classical inequalities have been demonstrated. The ever-increasing number of tumor-associated antigens has provided a major stimulus for the development of therapeutic peptides vaccines. Tumor-associated peptides can induce high immune response rates and have been developed as vaccines for several types of solid tumors, and many are at various stages of clinical testing. MAGED4B, a melanoma antigen, is overexpressed in oral squamous cell carcinoma (OSCC) and this expression promotes proliferation and cell migration. In previous scientifc projects it has also been identified that 9 short peptides derived from MAGED4B protein are restricted in binding to the HLA subtypes common in the Asian population (HLA-A2, A11, and A24). As a result, we here discovered for the first time the GENEA-Immunomagetor-45700d utilizing the KNIME-BiogenetoligandorolTM-PASS-KNIME-based GA(M)E-QSAR-FIPSDock: a new molecular docking combinatorial clustering technique driven by fully informed swarm optimization algorithm and GA(M)E-QSAR: a novel, fully automatic genetic-algorithm-(meta)-ensembles approach for binary classification in ligand-based drug design based on Chemical and biological properties of frequent screening hits in predicting drug targets based on conserved binding pocket active MAGED4B protein domains of a Collapsing Perfect Superposition to a Chosen Quantum State without Measurements to a Rationally immunogenic MAGED4B peptide-mimetic pharmacophoric robust agent as a potential fragment-library derived drug-compound comprising vaccine mimic annotated properties in oral cancer immunotherapies.

Keywords

Collapsing a Perfect Superposition; Chosen Quantum State; Measurement; Rationally; in silico Identification; immunogenic MAGED4Bl peptide-mimeticl pharmacophoricl robust agentl fragment-library; drug-compound; vaccine mimic; annotated properties; oral cancer immunotherapies.

Abstract

The p53 and nuclear factor κB (NF-κB) pathways play crucial roles in human cancer development. Simultaneous targeting of both pathways is an attractive therapeutic strategy against cancer. The use of pharmacologically active short peptide sequences has prooven to be a better option in cancer therapeutics than the full-lengthprotein. It has been previously report ed one such 44-mer peptide sequence of SMAR1 (TAT-SMAR1 wild type, P44) that retains the tumor suppressor activity of the full-length protein.P44 peptide could efficiently activate p53 by mediating its phosphorylation at serine15, resulting in the activation of p21 and in effect regulating cell cycle checkpoint. In vitrophosphorylation assays with point-mutated P44-derived pep-tides suggested that serine 347 of SMAR1 was indispensable forits activity and represented the substrate motif for the proteinkinase C family of proteins. In this Research Scientific Project we generated an antitumor multi-targeted hyper-molecule that bears a pyrrolo[3,4-clomifene-diamizido-c]pyrazole scaffold and functions as an enantiomeric P44 peptide mimeto inhibitor against both the p53-MDM2 interaction and the NF-κB activation. This pharmacophjoric scaffold may be a first-in-class dual targeted enantiomeric inhibitor with dual efficacy for cancer therapy with potential synergistic effect in vitro and in vivo. Docking and molecular dynamics simulation studies further provided insights into the nature of stereoselectivity. Here, we have for the first time in silico discovered novel chemo-hyperstructures as a novel drug discovery incorporated novel Quantum Clock Synchronizations with a Single Qudit chemo-hyperstructure as a novel drug discovery dual targeting of the p53 and NF-κB pathways for the activation of the p53 tumor suppressor pathway by an engineered P44 cyclotidomimic agonisitic mechanistic pharmacoligand.

Keywords

Quantum Clock Synchronization; Single Qudit;In silico discovery; novel chemo-hyperstructure; novel drug discovery; dual targeting; p53;NF-κB pathways; tumor suppressor pathway; engineered P44; cyclotidomimic agonisitic; mechanistic pharmacoligand.

Abstract

Glycoprotein-96, a non-polymorphic heat-shock protein, associates with intracellular peptides. Autologous tumor-derived heat shock protein-peptide complex 96 (HSPPC-96) can elicit potent tumor-specific T cell responses and protective immunity in animal models. Chemokines were described originally in the context of providing migrational cues for leukocytes. They are now known to have broader activities, including those that favor tumor growth. Treatment with autologous tumor-derived HSPPC-96 was feasible and safe at all doses tested. Observed immunological effects and antitumor activity were modest, precluding selection of a biologically active dose. Coevolution between proteins is crucial for understanding protein-protein interaction. Simultaneous changes allow a protein complex to maintain its overall structural-functional integrity. In this Research Scientific Project, we combined statistical coupling analysis (SCA) and molecular dynamics simulations on thecomplex-96 (HSPPC-96) protein complex to evaluate coevolution between conserved binding protein domain regions. We reconstructed an inter-protein residue coevolution network, consisting of 37 residues and 37complex-96 (HSPPC-96) binding domains conserved peptide derived residues and its fitness scoring reverse ligand docking interactions. It shows that most of the coevolved residue pairs are spatially proximal. When the mutations happened, the stable local structures were broken up and thus the protein interaction was decreased or inhibited, with a following increased risk of melanoma. The identification of inter-protein coevolved residues in thecomplex-96 (HSPPC-96) complex can be helpful for designing protein drug target and in silico discovery of engineering novel nanomolecule experiments. In this scientific study we have in silico discovered a Unique Small Molecule Modulator of CXCR4 tumor-derived heat-shock protein peptide complex-96 (HSPPC-96) by identifying Hits of Quantum Navigation and Ranking Complex Networks for the in silico development of a unique fragment poly-pharmacologic modulator of CXCR4 tumor-derived heat-shock GGHFGPFDY peptide mimotopic complex-96 (HSPPC-96) by highthroughput identifying hits on the hydrophobic autotaxin/lysophospholipase D pocket.

Keywords

Quantum Navigation; Ranking in Complex Networks; in silico; fragment; poly-pharmacologic; modulator; CXCR4 tumor-derived; heat-shock; GGHFGPFDY peptide; mimotopic complex-96; (HSPPC-96); highthroughput identifying hits; hydrophobic autotaxin/lysophospholipase D pocket.

Abstract

The quantum stochastic differential equation derived from the Lindblad form quantum master equation is investigated. The general formulation in terms of environment operators representing the quantum state diffusion is given. The numerical simulation algorithm of stochastic process of direct photodetection of a driven two-level system for the predictions of the dynamical behavior is proposed. The effectiveness and superiority of the algorithm are verified by the performance analysis of the accuracy and the computational cost in comparison with the classical Runge-Kutta algorithm. A conditionally replicative adenovirus is a novel anticancer agent designed to replicate selectively in tumor cells. However, a leak of the virus into systemic circulation from the tumors often causes ectopic infection of various organs. Therefore, suppression of naive viral tropism and addition of tumor-targeting potential are necessary to secure patient safety and increase the therapeutic effect of an oncolytic adenovirus in the clinical setting. It has also recently been developed a direct selection method of targeted vector from a random peptide library displayed on an adenoviral fiber knob to overcome the limitation that many cell type-specific ligands for targeted adenovirus vectors are not known. In previous studies it has also been further examined whether the addition of a tumor-targeting ligand to a replication-competent adenovirus ablated for naive tropism enhances its therapeutic index. Structure-based drug design is an iterative process, following cycles of structural biology, computer-aided design, synthetic chemistry and bioassay. In favorable circumstances, this process can lead to the structures of hundreds of protein-ligand crystal structures. In addition, molecular dynamics simulations are increasingly being used to further explore the conformational landscape of these complexes. Currently, methods capable of the analysis of ensembles of crystal structures and MD trajectories are limited and usually rely upon least squares superposition of coordinates. Novel methodologies are described for the analysis of multiple short linear motif like peptide structures of a protein-drug active binding conserved site. Statistical approaches that rely upon residue equivalence, but not superposition, are developed as chemogenomic informatic tasks can be performed includinig the identification of hinge regions, allosteric conformational changes and transient binding sites. Here, we have for the first time discovered an in silico rational Simulation of Quantum Dynamics Differential Equation Based on the Quantum Stochastic designed of a adenovirus library displaying random viral naive tropism replication-competent Oncolytic virus peptide-mimic pharmacophoric ligand supressor with potential therapeutic properties for pancreatic cancer.

Keywords

Simulation of Quantum Dynamics; Differential Equation; Quantum Stochastic in silico rational; adenovirus library; random peptide-mimic; pharmacophoric ligand supressor; viral naive tropism; replication-competent; Oncolytic virus; therapeutic properties; pancreatic cancer.

Abstract

We propose a method to construct universal order parameters for quantum phase transitions in many-body lattice systems. The method exploits the H-orthogonality of a few near-degenerate lowest states of the Hamiltonian describing a given finite-size system, which makes it possible to perform finite-size scaling and take full advantage of currently available numerical algorithms. An explicit connection is established between the fidelity per site between two H-orthogonal states and the energy gap between the ground state and low-lying excited states in the finite-size system. The physical information encoded in this gap arising from finite-size fluctuations clarifies the origin of the universal order parameter. We demonstrate the procedure for the one-dimensional quantum formulation of the q-state Potts model, for q = 2, 3, 4 and 5, as prototypical examples, using finite-size data obtained from the density matrix renormalization group algorithm. 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 disxovered a Finite-Size Universal Order Parameters and Quantum Phase computer simulated gp100 Peptide mimic Transitions on improved Algorithm for Chemically Tractable Semi-Automated Protein Inhibitor designed pharmacophore as a Vaccine-like and Interleukin-2 in silico generated superagonist with potential clinical effect in Patients with Advanced Melanoma.

Keywords

Universal Order Parameters and Quantum Phase Transitions: A Finite-Size Approach
A 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.

Abstract

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.These novel hyperstructures were generated by Using the BiogenetoligandorolTM AND the CovalentDock Cloud: a web server for automated covalent docking. An improved quantum-behaved particle swarm optimization with elitist breeding (EB-QPSO) for unconstrained optimization is presented and empirically studied in this paper. In EB-QPSO, the novel elitist breeding strategy acts on the elitists of the swarm to escape from the likely local optima and guide the swarm to perform more efficient search. During the iterative optimization process of EB-QPSO, when criteria met, the personal best of each particle and the global best of the swarm are used to generate new diverse individuals through the transposon operators. The new generated individuals with better fitness are selected to be the new personal best particles and global best particle to guide the swarm for further solution exploration. A comprehensive simulation study is conducted on a set of twelve benchmark functions. Compared with five state-of-the-art quantum-behaved particle swarm optimization algorithms, the proposed EB-QPSO performs more competitively in all of the benchmark functions in terms of better global search capability and faster convergence rate. Here, in Biogenea we have discovered for the first time an Improved Computational Quantum-Behaved Particle Swarm Optimization Algorithm with Elitist Breeding for Unconstrained Optimization 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

Improved Quantum-Behaved; Particle Swarm; Optimization Algorithm; Elitist Breeding; Unconstrained Optimization; Computational Assay; Design an Epitope-Based; Mimo-Peptidic; hyper agonist; inked active Pharmacophoric; chemo-Scaffolds; in silico; vaccine-like; potential properties; Saint Louis Encephalitis ;Virus conserved; binding domains.

Abstract

Quantum information processing devices need to be robust and stable against external noise and internal imperfections to ensure correct operation. In a setting of measurement-based quantum computation, we explore how an intelligent agent endowed with a projective simulator can act as controller to adapt measurement directions to an external stray field of unknown magnitude in a fixed direction. We assess the agent’s learning behavior in static and time-varying fields and explore composition strategies in the projective simulator to improve the agent’s performance. We demonstrate the applicability by correcting for stray fields in a measurement-based algorithm for Grover’s search. Thereby, we lay out a path for adaptive controllers based on intelligent agents for quantum information tasks. Allergic and autoimmune diseases are forms of immune hypersensitivity that increasingly cause chronic ill health. Most current therapies treat symptoms rather than addressing underlying immunological mechanisms. The ability to modify antigen-specific pathogenic responses by therapeutic vaccination offers the prospect of targeted therapy resulting in long-term clinical improvement without nonspecific immune suppression. Examples of specific immune modulation can be found in nature and in established forms of immune desensitization. Allergic and autoimmune diseases are forms of immune hypersensitivity that increasingly cause chronic ill health. Most current therapies treat symptoms rather than addressing underlying immunological mechanisms. The ability to modify antigen-specific pathogenic responses by therapeutic vaccination offers the prospect of targeted therapy resulting in long-term clinical improvement without nonspecific immune suppression. Examples of specific immune modulation can be found in nature and in established forms of immune desensitization. Targeting pathogenic T cells using vaccines consisting of synthetic peptides representing T cell epitopes is one such strategy that is currently being evaluated with encouraging results. Future challenges in the development of therapeutic vaccines include selection of appropriate antigens and peptides, optimization of peptide dose and route of administration and identifying strategies to induce bystander suppression. Structure-based computational methods have been widely used in exploring protein-ligand interactions, including predicting the binding ligands of a given peptide based on their structural complementarity. Compared to other peptide and ligand representations, the advantages of a surface representation include reduced sensitivity to subtle changes in the pocket and ligand conformation and fast search speed. Peptidomimetics, deriving from structure-based, combinatorial or protein dissection approaches, can play a key role as hit compounds. We believe that using a surface patch approach to better understand protein-ligand interactions has the potential to significantly enhance the design of new ligands for a wide array of drug-targets. Here, in Biogenea we have for the first time generated a surface representation adaptive quantum computation in changing environments using projective IHMVYSK peptide-mimo based chemo-ligand simulation designed of therapeutic vaccine-like agonistic properties as a potential novel druggable synthetic regulator for future allergic and autoimmune treatment applications.

Keywords

Adaptive quantum computation in changing environments using projective simulation A surface representation designed IHMVYSK peptide-mimo based chemo-ligand comprising therapeutic vaccine-like agonistic properties as a potential novel druggable synthetic regulator for future allergic and autoimmune treatment applications.