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;

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. 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 Deutsch’s algorithm, Von Neumann’s Theory, Projective Measurement, and Quantum Computation data generations of a multifunctional peptide-mimic chemo-structure by connecting conserved fragments based on the neutrophil immune defense CAP37 protein as an in-silico antibacterial and wound-healing canditate agent.

Keywords

Von Neumann’s Theory, Projective Measurement, Quantum Computation data; multifunctional; peptide-mimic; chemo-structure; connecting conserved fragments; neutrophil immune defense; CAP37 protein; in-silico; antibacterial; wound-healing; canditate agent, Quantum Computation, Quantum Measurement Theory, Formalism;

Abstract

Hydrocarbon stapling can restore bioactive α-helical structure to natural peptides, yielding research tools and prototype therapeutics to dissect and target protein interactions. The capacity of peptide stapling to generate high-fidelity, protease-resistant mimics of antigenic structures for vaccine development has been previoulsy explored. HIV-1 has been refractory to vaccine technologies thus far, although select human antibodies can broadly neutralize HIV-1 by targeting sequences of the gp41 juxtamembrane fusion apparatus. Candidate HIV-1 immunogens, have been generated and characterized stabilized α-helices of the membrane-proximal external region (SAH-MPER) of gp41 have been utilized. SAH-MPER peptides were remarkably protease resistant and bound to the broadly neutralizing 4E10 and 10E8 antibodies with high affinity, recapitulating the structure of the MPER epitope when differentially engaged by the two anti-HIV Fabs. Here, we discovered for the first time the GENEA-StacHIVenar-10085 utilising a computer aided generation of a prototype superset Stapled HIV-1 peptide-similar full-match pharmacophoric poly-agent recapitulating antigenic viral replication structures bounded broadly targeted to the neutralizing 4E10 and 10E8 antibodies.

Keywords

computer-aided; predicted;Stapled-HIV-1;peptide-mimic;pharmacophoric-poly-agent;
recapitulating-antigenic;structures;computer aided; generation; prototype; superset; Stapled HIV-1; peptide-similar; full-match; pharmacophoric; poly-agent; recapitulating antigenic; viral replication; structures; bounded broadly; neutralizing 4E10 and 10E8 antibodies;

Abstract

Quantum computers promise to efficiently solve important problems that are intractable on a conventional computer. For quantum systems, where the physical dimension grows exponentially, finding the eigenvalues of certain operators is one such intractable problem and remains a fundamental challenge. The quantum phase estimation algorithm efficiently finds the eigenvalue of a given eigenvector but requires fully coherent evolution. Here we present an alternative approach that greatly reduces the requirements for coherent evolution and combine this method with a new approach to state preparation based on ansätze and classical optimization. We implement the algorithm by combining a highly reconfigurable photonic quantum processor with a conventional computer. We experimentally demonstrate the feasibility of this approach with an A variational eigenvalue solver rational design of a computer-aided poly-pharmacophore on a photonic quantum processor synthetic molecule comprising therapeutic peptide-mimic superagonistic properties of 829,16kcal.mol against to Ebola virus conserved protein regions from quantum chemistry—calculating the ground-state molecular energy for He–H+. The proposed approach drastically reduces the coherence time requirements, enhancing the potential of quantum resources available today and in the near future.

Keywords

A variational eigenvalue solver on a photonic quantum processor Rational design of a computer-aided poly-pharmacophore synthetic molecule comprising therapeutic peptide-mimic superagonistic properties of 829,16kcal.mol against to Ebola virus conserved protein regions.A variational eigenvalue solver on a photonic quantum processor.

Abstract

The molecular mechanics energies combined with the Poisson–Boltzmann or generalized Born and surface area continuum solvation (MM/PBSA and MM/GBSA) methods are popular approaches to estimate the free energy of the binding of small ligands to biological macromolecules. They are typically based on molecular dynamics simulations of the receptor–ligand complex and are therefore intermediate in both accuracy and computational effort between empirical scoring and strict alchemical perturbation methods. They have been applied to a large number of systems with varying success. Antimicrobial peptides (AMPs) which predominantly act via membrane active mechanisms have emerged as an exciting class of antimicrobial agents with tremendous potential to overcome the global epidemic of antibiotics-resistant infections. The first generation of AMPs derived from natural sources as diverse as plants, insects and humans has provided a wealth of compositional and structural information to design novel synthetic AMPs with enhanced antimicrobial potencies and selectivities, reduced cost of production due to shorter sequences and improved stabilities under physiological conditions. As a rational result we discovered for the first time the GENEA-Antimamphiler-109 utilizing Rational Elaborated Common Strategies employed MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities for the efficient in silico optimization of an accesible synthetically (AMPs) peptidomimetic-similar to an amphiphile-based pharmacophoric agent as a promising enhanced therapeutic antimicrobial agent.

Keywords

MM/PBSA;MM/GBSA; methods; ligand-binding affinities; Rational Elaborated; Common Strategies; in silico; optimization; accesible; synthetically; (AMPs) peptidomimetic; amphiphile-based; pharmacophoric agent; therapeutic antimicrobial agent;

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 de novo ligand Identification Complementary Approaches to Existing Target Based Drug Discovery for Identifying Novel Drug Targets of a structural ligand-based synthetically accesible pharmacophoric determinant on tau protein-mimic conserved motif peptide chemical elements as an annotated promising therapy in drug discovery approaches and proposes alternative approaches for increasing efficiency against Alzheimer’s disease treatment.

Keywords

drug discovery, drug design, drug targets, repositioning, molecular imaging, Complementary Approaches; Existing; Target Based; Drug Discovery; Identifying; Novel Drug Targets; De novo ligand; Identification;structural; ligand-based; synthetically accesible; pharmacophoric determinant ; tau protein-mimic; conserved motif; peptide chemical; elements; annotated; promising in Alzheimer’s disease;