Abstract

Molecular mechanics (MM) methods are computationally affordable tools for screening chemical libraries of novel compounds for sites of P450 metabolism. One challenge for MM methods has been the absence of a consistent and transferable set of parameters for the heme within the P450 active-site. Experimental data indicates that mammalian P450 enzymes vary greatly in the size, architecture, and plasticity of their active sites. Thus, obtaining x-ray based geometries for the development of accurate MM parameters for the major classes of hepatic P450 remains a daunting task. Our previous work with preliminary gas-phase quantum mechanics (QM) derived atomic partial charges, greatly improved the accuracy of docking studies of raloxifene to CYP3A4. Different patterns for substrate docking are also observed depending on the choice of heme model and state. Newly parameterized heme models are tested in implicit and explicitly solvated MD simulations in the absence and presence of enzyme structures, for CYP3A4, and appear to be stable on the nanosecond simulation timescale. The new force field for the various heme states may aid the community for simulations of P450 enzymes and other heme containing enzymes. The prognosis of patients with advanced biliary tract cancer (BTC) is extremely poor and thereare only a few standard treatments. We conducted a phase I trial to investigate the safety, immune response,and antitumor effect of vaccination with four peptides derived from cancer-testis antigens, with a focus ontheir fluctuations during long-term vaccination until the disease had progressed. A unified statistical model to support local sequence order independent similarity searching for ligand-binding sites and its application to genome-based drug discovery. Bioinformatics, 25, i305–i312.]. These algorithms have been extensively benchmarked and shown to outperform most existing algorithms. Moreover, several predictions resulting from SMAP-WS have been validated experimentally. Thus far SMAP-WS has been applied to predict drug side effects, and to repurpose existing drugs for new indications. SMAP-WS provides both a user-friendly web interface and programming API for scientists to address a wide range of compute intense questions in biology and drug discovery. Here, we have for the first time discovered a multi-epitope mimic poly-pharmacophore to Multiple Peptides Derived from Cancer-Testis Antigens for the maintance of a Specific T-cell Response in Long-term Vaccinated patients with Advanced Biliary Tract Cancer using the BiogenetoligandorolTM based SMAP-WS chemical informatic parallel web service for structural proteome-wide ligand-binding site comparison.

Keywords

Algebraically in silico discovery, multi-epitope, mimic, poly-pharmacophore, Multiple Peptides, Cancer-Testis, Antigens, anti-tumor, pharmaco-agent, Specific T-cell Response, Long-term, Vaccinated patients, Advanced Biliary Tract Cancer, parallel web service, structural proteome-wide, ligand-binding site, comparison, Cytochrome P450 enzymes, heme force field parameters, molecular mechanics, RESP charges, AMBER, drug-metabolism,

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. An in silico designed dosimetric autologous living vaccine consisting of with Multiple Wilms’ Tumor 1 WT1-ConSynthetic–Restricted Peptide mimotopic Epitopes RMFPNAPYLP pulsed dendritic cells on a personalized Active Network analysis for asymptomatic or minimally symptomatic metastatic Pancreatic Cancer.

Keywords

Evaluation, Inverse Molecular Design Algorithm, Model Binding Site, in silico designed, dosimetric, autologous living vaccine, Multiple Wilms’ Tumor 1 WT1-ConSynthetic–Restricted, Peptide, mimotopic Epitopes, RMFPNAPYLP pulsed, dendritic cells, personalized, Active Network, analysis, asymptomatic, minimally, symptomatic metastatic, Pancreatic Cancer, inverse design, scoring function, protein-ligand interaction, cytochrome c peroxidase, dead-end elimination, drug design,

Abstract

Quantum mechanics has long been recognized as a counter-intuitive theory, with ideas such as wave-particle duality, quantum superposition and entanglement defying our natural way of thinking. In recent years, these sorts of uniquely quantum properties are being exploited to develop revolutionary technologies, such as quantum cryptography, quantum metrology and perhaps the most well-known example, quantum computation. In the field of quantum computation, the circuit model was used to show that universal quantum computation is possible1, and the circuit model has since been an incredibly successful tool, leading to important quantum algorithms which greatly outperform their classical counterparts2. The circuit model takes advantage of the fact that quantum mechanics allows for the superposition and interference of quantum bits (qubits) in different states to achieve a computational speed-up. However, in addition to the superpositions of states, quantum mechanics also allows for the superposition of quantum circuits3,4—a feature which is not used in the standard quantum circuit model. Nevertheless, such superpositions of quantum circuits are rapidly becoming central to several foundational research programs studying the role of time and causality in quantum theory5,6,7,8,9. These superpositions of quantum circuits (sometimes called a ‘superposition of causal orders’) give rise to new counter-intuitive quantum predictions, and it has recently been predicted that they could provide quantum computers with even further computational advantages8,10. In particular, superimposing quantum circuits, each with a different gate ordering, can allow one to accomplish a specific computational task with fewer quantum gate uses than a quantum computer which has a fixed-gate order10. Quantum computers achieve a speed-up by placing quantum bits (qubits) in superpositions of different states. However, it has recently been appreciated that quantum mechanics also allows one to ‘superimpose different operations’. Furthermore, it has been shown that using a qubit to coherently control the gate order allows one to accomplish a task—determining if two gates commute or anti-commute—with fewer gate uses than any known quantum algorithm. Here we experimentally demonstrate this advantage, in a photonic context, using a second qubit to control the order in which two gates are applied to a first qubit. We create the required superposition of gate orders by using additional degrees of freedom of the photons encoding our qubits. The new resource we exploit can be interpreted as a superposition of causal orders, and could allow quantum algorithms to be implemented with an efficiency unlikely to be achieved on a fixed-gate-order quantum computer.An in silico designed dosimetric autologous living vaccine consisting of with Multiple Wilms’ Tumor 1 WT1-ConSynthetic–Restricted Peptide mimotopic Epitopes RMFPNAPYLP pulsed dendritic cells on a personalized Active Network analysis for asymptomatic or minimally symptomatic metastatic Pancreatic Cancer.

Keywords

Experimental superposition of orders of quantum gatesAn in silico designed dosimetric autologous living vaccine consisting of with Multiple Wilms’ Tumor 1 WT1-ConSynthetic–Restricted Peptide mimotopic Epitopes RMFPNAPYLP pulsed dendritic cells on a personalized Active Network analysis for asymptomatic or minimally symptomatic metastatic Pancreatic Cancer.

Abstract

It is well known that quantum computers are superior to classical computers in efficiently simulating quantum systems. Here we report the first experimental simulation of quantum tunneling through potential barriers, a widespread phenomenon of a unique quantum nature, via NMR techniques. Our experiment is based on a digital particle simulation algorithm and requires very few spin-1/2 nuclei without the need of ancillary qubits. The occurrence of quantum tunneling through a barrier, together with the oscillation of the state in potential wells, are clearly observed through the experimental results. This experiment has clearly demonstrated the possibility to observe and study profound physical phenomena within even the reach of small quantum computers. Quantum simulation is one of the most important aims of quantum computation ever since Feynman studied the likelihood of simulating one quantum system by another1. Recent years have witnessed fruitful results in the development of quantum computation, and it has been demonstrated that quantum computers can solve certain types of problems with a level of efficiency beyond the capability of classical computers2,3,4,5,6, among which the simulation of the dynamics of quantum systems is especially attractive because of the exponential improvement in computational resources and speeds. Quantum simulation has become a subject of intense investigation and has been realized in various situations, such as system evolution with a many-body interaction Hamiltonian7,8,9,10, the dynamics of entanglement11,12, quantum phase transitions13,14, and calculations of molecular properties15,16,17,18,19. Since we live in a dirty environment, we have developed many host defenses to contend with microorganisms. The epithelial lining of our skin, gastrointestinal tract and bronchial tree produces a number of antibacterial peptides, and our phagocytic neutrophils rapidly ingest and enzymatically degrade invading organisms, as well as produce peptides and enzymes with antimicrobial activities. Some of these antimicrobial moieties also appear to alert host cells involved in both innate host defense and adaptive immune responses.RNAs fold into intricate and precise secondary structures. In this study for the first time we have been evaluted experimental simulation of Novel procedure quantum tunneling in small Computational Scaffolding systems on tumorigenic stem cell bacterial infected hybrids for the in silico rescaffolding and side-chain optimization on the neutrophil immune defense CAP37 protein.

Keywords

Novel procedure Computational Scaffolding, tumorigenic stem cell, bacterial infected hybrids, in silico rescaffolding, side-chain optimization, neutrophil immune defense, CAP37 protein, Experimental simulation, quantum tunneling, small systems.

Abstract

As quantum counterpart of classical computer, quantum computer reveals incredible efficiency to execute arithmetic tasks and threatens the security of classical communication. Quantum algorithm is the sole of quantum computation, which shows the amazing power of quantum parallelism and quantum interference. It attracts particular concern to develop new quantum algorithms in recent years. The concept of simulating physics progresses with quantum computers was originated in Richard Feynman’s observation that computers built from quantum mechanical components would be ideally suited to simulating quantum mechanics1. Since then, the first efficient quantum algorithm was proposed by Deutsch in 19852 and generalized by Deutsch and Jozsa in 19873. Lately, an increasing number of practical programs were presented, such as factoring large integer4, Grover’s searching algorithm for database5 and Simon’s exponential acceleration algorithm for the black box problem6. What’s more, Harrow et al. came up with a quantum scheme to decrease the computational complexity of solving linear system of equations from O(n) to log(n) , and this was the first quantum algorithm to work out the most fundamental problems in engineering science7. Some quantum algorithms have been demonstrated in different physical systems, such as ion traps8,9,10,11, superconducting devices12,13,14, optical lattices15,16, quantum dots17,18, and linear optics19,20,21,22,23,24,25. Due to its good scalability, easy-handling and high stability, linear optical system is a good candidate for implementing quantum algorithms.We report an experiment to demonstrate a quantum permutation determining algorithm with linear optical system. By employing photon’s polarization and spatial mode, we realize the quantum ququart states and all the essential permutation transformations. The quantum permutation determining algorithm displays the speedup of quantum algorithm by determining the parity of the permutation in only one step of evaluation compared with two for classical algorithm. This experiment is accomplished in single photon level and the method exhibits universality in high-dimensional quantum computation.Combinatorial learning procedures and graph transformations for the discovery of tumor-like cardiomyocyte derived eletroporated combined hybrids on a Meta-Dynamic Meta-node stemness reconstructing approach for the in silico generation of a anti-(JAM-A) drug-construct.

Keywords

Demonstration, quantum permutation algorithm, single photon, ququart, Combinatorial learning procedures, graph transformations, discovery tumor-like cardiomyocyte, eletroporated, combined hybrids, Meta-Dynamic, Meta-node, stemness, reconstructing, approach, in silico, generation, anti-(JAM-A), drug-construct.

Abstract

We report an experiment to demonstrate a quantum permutation determining algorithm with linear optical system. By employing photon’s polarization and spatial mode, we realize the quantum ququart states and all the essential permutation transformations. The quantum permutation determining algorithm displays the speedup of quantum algorithm by determining the parity of the permutation in only one step of evaluation compared with two for classical algorithm. This experiment is accomplished in single photon level and the method exhibits universality in high-dimensional quantum computation. As quantum counterpart of classical computer, quantum computer reveals incredible efficiency to execute arithmetic tasks and threatens the security of classical communication. Quantum algorithm is the sole of quantum computation, which shows the amazing power of quantum parallelism and quantum interference. It attracts particular concern to develop new quantum algorithms in recent years. The concept of simulating physics progresses with quantum computers was originated in Richard Feynman’s observation that computers built from quantum mechanical components would be ideally suited to simulating quantum mechanics1. Since then, the first efficient quantum algorithm was proposed by Deutsch in 19852 and generalized by Deutsch and Jozsa in 19873. Lately, an increasing number of practical programs were presented, such as factoring large integer4, Grover’s searching algorithm for database5 and Simon’s exponential acceleration algorithm for the black box problem6. What’s more, Harrow et al. came up with a quantum scheme to decrease the computational complexity of solving linear system of equations from O(n) to log(n) , and this was the first quantum algorithm to work out the most fundamental problems in engineering science7. Some quantum algorithms have been demonstrated in different physical systems, such as ion traps8,9,10,11, superconducting devices12,13,14, optical lattices15,16, quantum dots17,18, and linear optics19,20,21,22,23,24,25. Due to its good scalability, easy-handling and high stability, linear optical system is a good candidate for implementing quantum algorithms. Here, for the first time we have performed a fast stochastic optimization of a quantum permutation algorithm with a single photon ququart algorithm on DC-tumor like high yield minimal magnetic signatures of electrotransfectioned ex vivo mediated hybrids for the generation of a computer-aided designed candidate drugable Toll-like receptor (Pam2IDG) peptide-domain agonistic agent.

Keywords

Fast stochastic optimization algorithm, DC-tumor like high yield, minimal magnetic signatures, electrotransfectioned ex vivo mediated hybrids, generation, computer-aided, designed candidate, drugable, Toll-like receptor, (Pam2IDG) peptide-domain, agonistic agent, demonstration, quantum permutation, algorithm, single, photon ququart.

Abstract

The structure of peptide p6.7, a mimotope of the nicotinic receptor ligand site that binds alpha-bungarotoxin and neutralizes its toxicity, was compared to that of the acetylcholine binding protein. The central loop of p6.7, when complexed with alpha-bungarotoxin, fits the structure of the acetylcholine binding protein (AChBP) ligand site, whereas peptide terminal residues seem to be less involved in toxin binding. The minimal binding sequence of p6.7 was confirmed experimentally by synthesis of progressively deleted peptides. Affinity maturation was then achieved by random addition of residues flanking the minimal binding sequence and by selection of new alpha-bungarotoxin binding peptides on the basis of their dissociation kinetic rate. The MAP peptide binds alpha-bungarotoxin in solution and inhibits its binding to the receptor with a K(A) and an IC(50) similar to the monomeric peptide. Peptidomimetics are designed to circumvent some of the problems associated with a natural peptide: e.g. stability against proteolysis (duration of activity) and poor bioavailability. In this regard, we discuss its potential to become a routinely used drug design tool of QM/MM in rational drug discovery and molecular diversity for the construction of anti-alpha-bungarotoxin binding peptide mimetic antidotes consisting of essential elements with high affinity and promised vivo efficiency.

Keywords

QM/MM, rational drug discovery, molecular diversity, construction, anti-alpha-bungarotoxin, binding peptide, mimetic antidotes, elements, high affinity, MAP-p6.7 peptide mimetic ligand, nicotinic receptor, binding site, potent snake neurotoxin, synthetic antidote, merging, scoring, molecular interactions,

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. he structure of peptide p6.7, a mimotope of the nicotinic receptor ligand site that binds alpha-bungarotoxin and neutralizes its toxicity, was compared to that of the acetylcholine binding protein. The central loop of p6.7, when complexed with alpha-bungarotoxin, fits the structure of the acetylcholine binding protein (AChBP) ligand site, whereas peptide terminal residues seem to be less involved in toxin binding. The minimal binding sequence of p6.7 was confirmed experimentally by synthesis of progressively deleted peptides. Affinity maturation was then achieved by random addition of residues flanking the minimal binding sequence and by selection of new alpha-bungarotoxin binding peptides on the basis of their dissociation kinetic rate. The MAP peptide binds alpha-bungarotoxin in solution and inhibits its binding to the receptor with a K(A) and an IC(50) similar to the monomeric peptide. Peptidomimetics are designed to circumvent some of the problems associated with a natural peptide: e.g. stability against proteolysis (duration of activity) and poor bioavailability. In this regard, we discuss its potential to become a routinely used drug design tool of QM/MM in rational drug discovery and molecular diversity for the construction of anti-alpha-bungarotoxin binding peptide mimetic antidotes consisting of essential elements with high affinity and promised vivo efficiency. Finally, we applied to the Circular Scale of Time computations as a Way of Calculating the Quantum-Mechanical Perturbation Energy Given by the Schrödinger Method in QM/MM rational drug discovery and molecular diversity for the construction of an anti-alpha-bungarotoxin binding MAP-p6.7 peptide mimetic ligand against nicotinic receptor binding site as a potent snake neurotoxin synthetic antidote.

Keywords

Quantum-Mechanical, Perturbation Energy, Circular Scale of Time, QM/MM, rational drug discovery, molecular diversity, construction, anti-alpha-bungarotoxin, binding MAP-p6.7 peptide, mimetic ligand, against nicotinic receptor, binding site, potent snake neurotoxin, synthetic antidote, Circular Scale of Time, Way of Calculating, Quantum-Mechanical, Perturbation Energy, Schrödinger Method

Abstract

There is evidence that the α-synucleinopathies Parkinson’s disease (PD) and the Parkinson variant of multiple system atrophy (MSA-P) overlap at multiple levels. Both disorders are characterized by deposition of abnormally phosphorylated fibrillar α-synuclein within the central nervous system suggesting shared pathophysiological mechanisms. Currently, there is no disease-modifying treatment for MSA. In other senses, it has been previously shown that next-generation active vaccination technology with short peptides, AFFITOPEs®, was effective in two transgenic models of synucleinopathies at reducing behavioral deficits, α-syn accumulation and inflammation. Recently, it is shown that there is a crucial contradiction within von Neumann’s theory [K. Nagata and T. Nakamura, Int. J. Theor. Phys. 49, 162 (2010)]. We derive a proposition concerning a quantum expected value under the assumption of the existence of the directions in a spin-1/2 system. The quantum predictions within the formalism of von Neumann’s projective measurement cannot coexist with the proposition concerning the existence of the directions. Therefore, we have to give up either the existence of the directions or the formalism of von Neumann’s projective measurement. Hence, there is a crucial contradiction within von Neumann’s theory. We discuss that this crucial contradiction makes the theoretical formulation of Deutsch’s algorithm questionable. Especially, we systematically describe our assertion based on more mathematical analysis using raw data. We demonstrate here for the first time a drug discovery platform for the generation of analogues of the heptapeptide H-Arg-Lys-Val-MePhe-Tyr-Thr-Trp- OH2, an novel multitargeted inhibitors of Aβ-peptide aggregation, to cross-react with α-synuclein interfering with its fibril formation through novel Aggregation simulated studies on Amyloid β-sheet helix-rich Val-Gly-Gly-Ala-Thr-Thr-Thr-Gly-Val-Thr peptide mimic modulators of α-Synuclein aggregation as a emerging template for drug discovery in α-synucleinopathy interfering amyloidogenesis pathways.

Keywords

Aggregation simulated studies, Amyloid β-sheet helix-richpeptide, mimic modulators, α-Synuclein, aggregation, emerging template, drug discovery, α-synucleinopathies, interfering amyloidogenesis pathways, Can Von Neumann’s Theory, Meet Quantum, Aggregation Computation, simulated studies, on Amyloid β-sheet helix-rich Val-Gly-Gly-Ala-Thr-Thr-Thr-Gly-Val-Thr, peptide mimic, modulators, α-Synuclein aggregation, emerging template.

Abstract

A statistical-mechanical framework for estimation of solvation entropies and enthalpies is proposed, which is based on the analysis of water as a mixture of correlated water oxygens and water hydrogens. Entropic contributions of increasing order are cast in terms of a Mutual Information Expansion that is evaluated to pairwise interactions. In turn, the enthalpy is computed directly from a distance-based hydrogen bonding energy algorithm. The resulting expressions are employed for grid-based analyses of Molecular Dynamics simulations. In this first assessment of the methodology, we obtained global estimates of the excess entropy and enthalpy of water that are in good agreement with experiment and examined the method’s ability to enable detailed elucidation of solvation thermodynamic structures, which can provide valuable knowledge toward molecular design.An algorithm for high-resolution refinement and binding affinity estimation of inhibitors of CGQMCTVWCSSGC targeted conserved peptide substitution mimetic pharmacostructures antagonizing VEGFR-3-mediated oncogenic effects.

Keywords

Estimation, olvation Entropy, Enthalpy, Analysis, Water, Oxygen–Hydrogen Correlations, algorithm, high-resolution refinement, binding affinity, inhibitors, CGQMCTVWCSSGC targeted, conserved peptide, substitution, mimetic, pharmacostructures, antagonizing, VEGFR-3-mediated oncogenic effects,