The Experts below are selected from a list of 294 Experts worldwide ranked by ideXlab platform
Ricard V Sole - One of the best experts on this subject based on the ideXlab platform.
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the topology of drug target interaction networks Implicit Dependence on drug properties and target families
Molecular BioSystems, 2009Co-Authors: Jordi Mestres, Elisabet Gregoripuigjane, Sergi Valverde, Ricard V SoleAbstract:The availability of interaction data between small molecule drugs and protein targets has increased substantially in recent years. Using seven different databases, we were able to assemble a total of 4767 unique interactions between 802 drugs and 480 targets, which means that on average every drug is currently acknowledged to interact with 6 targets. The application of network theory to the analysis of these data reveals an unexpectedly complex picture of drug–target interactions. The results confirm that the topology of drug–target networks depends Implicitly on data completeness, drug properties, and target families. The implications for drug discovery are discussed.
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The topology of drug–target interaction networks: Implicit Dependence on drug properties and target families
Molecular bioSystems, 2009Co-Authors: Jordi Mestres, Sergi Valverde, Elisabet Gregori-puigjané, Ricard V SoleAbstract:The availability of interaction data between small molecule drugs and protein targets has increased substantially in recent years. Using seven different databases, we were able to assemble a total of 4767 unique interactions between 802 drugs and 480 targets, which means that on average every drug is currently acknowledged to interact with 6 targets. The application of network theory to the analysis of these data reveals an unexpectedly complex picture of drug–target interactions. The results confirm that the topology of drug–target networks depends Implicitly on data completeness, drug properties, and target families. The implications for drug discovery are discussed.
Sergi Valverde - One of the best experts on this subject based on the ideXlab platform.
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the topology of drug target interaction networks Implicit Dependence on drug properties and target families
Molecular BioSystems, 2009Co-Authors: Jordi Mestres, Elisabet Gregoripuigjane, Sergi Valverde, Ricard V SoleAbstract:The availability of interaction data between small molecule drugs and protein targets has increased substantially in recent years. Using seven different databases, we were able to assemble a total of 4767 unique interactions between 802 drugs and 480 targets, which means that on average every drug is currently acknowledged to interact with 6 targets. The application of network theory to the analysis of these data reveals an unexpectedly complex picture of drug–target interactions. The results confirm that the topology of drug–target networks depends Implicitly on data completeness, drug properties, and target families. The implications for drug discovery are discussed.
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The topology of drug–target interaction networks: Implicit Dependence on drug properties and target families
Molecular bioSystems, 2009Co-Authors: Jordi Mestres, Sergi Valverde, Elisabet Gregori-puigjané, Ricard V SoleAbstract:The availability of interaction data between small molecule drugs and protein targets has increased substantially in recent years. Using seven different databases, we were able to assemble a total of 4767 unique interactions between 802 drugs and 480 targets, which means that on average every drug is currently acknowledged to interact with 6 targets. The application of network theory to the analysis of these data reveals an unexpectedly complex picture of drug–target interactions. The results confirm that the topology of drug–target networks depends Implicitly on data completeness, drug properties, and target families. The implications for drug discovery are discussed.
Jordi Mestres - One of the best experts on this subject based on the ideXlab platform.
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the topology of drug target interaction networks Implicit Dependence on drug properties and target families
Molecular BioSystems, 2009Co-Authors: Jordi Mestres, Elisabet Gregoripuigjane, Sergi Valverde, Ricard V SoleAbstract:The availability of interaction data between small molecule drugs and protein targets has increased substantially in recent years. Using seven different databases, we were able to assemble a total of 4767 unique interactions between 802 drugs and 480 targets, which means that on average every drug is currently acknowledged to interact with 6 targets. The application of network theory to the analysis of these data reveals an unexpectedly complex picture of drug–target interactions. The results confirm that the topology of drug–target networks depends Implicitly on data completeness, drug properties, and target families. The implications for drug discovery are discussed.
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The topology of drug–target interaction networks: Implicit Dependence on drug properties and target families
Molecular bioSystems, 2009Co-Authors: Jordi Mestres, Sergi Valverde, Elisabet Gregori-puigjané, Ricard V SoleAbstract:The availability of interaction data between small molecule drugs and protein targets has increased substantially in recent years. Using seven different databases, we were able to assemble a total of 4767 unique interactions between 802 drugs and 480 targets, which means that on average every drug is currently acknowledged to interact with 6 targets. The application of network theory to the analysis of these data reveals an unexpectedly complex picture of drug–target interactions. The results confirm that the topology of drug–target networks depends Implicitly on data completeness, drug properties, and target families. The implications for drug discovery are discussed.
Ben F. Mcmillan - One of the best experts on this subject based on the ideXlab platform.
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A reanalysis of a strong-flow gyrokinetic formalism
Physics of Plasmas, 2015Co-Authors: Amil Sharma, Ben F. McmillanAbstract:We reanalyse an arbitrary-wavelength gyrokinetic formalism [A. M. Dimits, Phys. Plasmas $\bf17$, 055901 (2010)], which orders only the vorticity to be small and allows strong, time-varying flows on medium and long wavelengths. We obtain a simpler gyrocentre Lagrangian up to second order. In addition, the gyrokinetic Poisson equation, derived either via variation of the system Lagrangian or explicit density calculation, is consistent with that of the weak-flow gyrokinetic formalism [T. S. Hahm, Phys. Fluids $\bf31$, 2670 (1988)] at all wavelengths in the weak flow limit. The reanalysed formalism has been numerically implemented as a particle-in-cell code. An iterative scheme is described which allows for numerical solution of this system of equations, given the Implicit Dependence of the Euler-Lagrange equations on the time derivative of the potential.
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A consistent strong-flow gyrokinetic Poisson equation
2014Co-Authors: A. Y. Sharma, Ben F. McmillanAbstract:We reanalyse an arbitrary-wavelength gyrokinetic formalism [A. M. Dimits, Phys. Plasmas $\bf17$, 055901 (2010)], which orders only the vorticity to be small and allows strong, time-varying flows on medium and long wavelengths. We obtain a simpler gyrocentre Lagrangian up to second order. In addition, the gyrokinetic Poisson equation, derived either via variation of the system Lagrangian or explicit density calculation, is consistent with that of the weak-flow gyrokinetic formalism [T. S. Hahm, Phys. Fluids $\bf31$, 2670 (1988)] at all wavelengths in the weak flow limit. The reanalysed formalism has been numerically implemented as a particle-in-cell code. An iterative scheme is described which allows for numerical solution of this system of equations, given the Implicit Dependence of the Euler-Lagrange equations on the time derivative of the potential.
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A reanalysis of a strong-flow gyrokinetic theory
2014Co-Authors: A. Y. Sharma, Ben F. McmillanAbstract:We reanalyse an arbitrary-wavelength gyrokinetic formalism [A. M. Dimits, Phys. Plasmas $\bf17$, 055901 (2010)], which orders only the vorticity to be small and allows strong, time-varying flows on medium and long wavelengths. We obtain a simpler gyrocentre Lagrangian up to second order. In addition, the gyrokinetic Poisson equation, derived either via variation of the system Lagrangian or explicit density calculation, is consistent with that of the weak-flow gyrokinetic formalism [T. S. Hahm, Phys. Fluids $\bf31$, 2670 (1988)] at all wavelengths in the weak flow limit. The reanalysed formalism has been numerically implemented as a particle-in-cell code. An iterative scheme is described which allows for numerical solution of this system of equations, given the Implicit Dependence of the Euler-Lagrange equations on the time derivative of the potential.
Jochen Autschbach - One of the best experts on this subject based on the ideXlab platform.
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the unexpected roles of σ and π orbitals in electron donor and acceptor group effects on the 13c nmr chemical shifts in substituted benzenes
Chemical Science, 2017Co-Authors: Renan V Viesser, Lucas C Ducati, Claudio F Tormena, Jochen AutschbachAbstract:Effects of electron-donating (R = NH2) and electron-withdrawing (R = NO2) groups on 13C NMR chemical shifts in R-substituted benzene are investigated by molecular orbital analyses. The 13C shift substituent effect in ortho, meta, and para position is determined by the σ bonding orbitals in the aryl ring. The π orbitals do not explain the substituent effects in the NMR spectrum as conventionally suggested in textbooks. The familiar electron donating and withdrawing effects on the π system by NH2 and NO2 substituents induce changes in the σ orbital framework, and the 13C chemical shifts follow the trends induced in the σ orbitals. There is an Implicit Dependence of the σ orbital NMR shift contributions on the π framework, via unoccupied π* orbitals, due to the fact that the nuclear shielding is a response property.
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The unexpected roles of σ and π orbitals in electron donor and acceptor group effects on the 13C NMR chemical shifts in substituted benzenes.
Chemical science, 2017Co-Authors: Renan V Viesser, Lucas C Ducati, Claudio F Tormena, Jochen AutschbachAbstract:Effects of electron-donating (R = NH2) and electron-withdrawing (R = NO2) groups on 13C NMR chemical shifts in R-substituted benzene are investigated by molecular orbital analyses. The 13C shift substituent effect in ortho, meta, and para position is determined by the σ bonding orbitals in the aryl ring. The π orbitals do not explain the substituent effects in the NMR spectrum as conventionally suggested in textbooks. The familiar electron donating and withdrawing effects on the π system by NH2 and NO2 substituents induce changes in the σ orbital framework, and the 13C chemical shifts follow the trends induced in the σ orbitals. There is an Implicit Dependence of the σ orbital NMR shift contributions on the π framework, via unoccupied π* orbitals, due to the fact that the nuclear shielding is a response property.
