This document discusses using computational methods like molecular mechanics and molecular dynamics to minimize the energy of ligands bound to cyclin-dependent kinase 2 (CDK2) proteins. Two ligands (from 1H1S and 1OIT proteins) were selected and their minimum energy states calculated using different molecular mechanics algorithms and force fields. Fletcher-Reeves algorithm with MM+ force field produced the lowest energies of 34.32 kcal/mol for 1H1S ligand and 47.90 kcal/mol for 1OIT ligand. Molecular dynamics simulations at varying runtimes also minimized ligand energies further.
Molecular dynamics (MD) simulations calculate particle trajectories by integrating Newton's equations of motion. This document discusses the history and basic principles of MD, force fields, the NAMD simulation package, and applications. NAMD is a parallelized MD program for biomolecular simulations that uses spatial decomposition and multithreading. It supports features like CHARMM force fields, ensembles, and interactive modeling with VMD for structure visualization. MD simulations are useful for modeling protein structures, comparing protein templates, and predicting protein behavior through refinement of simulation approaches.
This document provides an overview of molecular dynamics (MD) simulation, which calculates the time-dependent behavior of biological molecules. MD simulation can provide detailed information on protein fluctuations and conformational changes. It is used to study protein stability, folding, molecular recognition and other biological processes. The document discusses how MD simulations are set up and run, including using force fields to calculate molecular interactions and numerical integration algorithms to solve equations of motion. It also covers statistical mechanics approaches for relating atomic-level simulation data to macroscopic properties.
This document outlines classical molecular dynamics simulations. It discusses using force fields to model molecular interactions and integrating equations of motion to simulate molecular motion. Molecular dynamics simulations allow studying processes such as protein folding but are limited by timescale. Ensembles, thermostats, and barostats control temperature, pressure and allow sampling different conditions. The document highlights challenges in achieving longer timescales and higher accuracy simulations.
Cloud Pharmaceuticals white paper.LIE_2016Shahar Keinan
Cloud Pharmaceuticals uses Quantum Molecular Design (QMD), which combines artificial intelligence, cloud computing, and quantum mechanics/molecular mechanics (QM/MM) calculations, to efficiently and accurately predict ligand binding potency to protein targets. QMD searches chemical space to design novel drug candidates and calculates binding affinities between targets and ligands. Results show QMD achieves high correlation between calculated and measured binding values for several protein targets, demonstrating its ability to predict ligand potency.
Computational chemistry uses theoretical chemistry calculations incorporated into computer programs to calculate molecular structures and properties. It can calculate properties such as structure, energy, charge distribution, and spectroscopic quantities using methods ranging from highly accurate ab initio methods to less accurate semi-empirical and molecular mechanics methods. Computational chemistry has advantages like allowing medicinal chemists to measure molecular geometry, energies, and perform conformational analysis using computer power. It can also determine ligand and target structures through computational docking methods.
Monte Carlo Simulations & Membrane Simulation and DynamicsArindam Ghosh
Monte Carlo simulations and molecular dynamics simulations are common computational methods to study membrane proteins and lipid bilayers. Monte Carlo simulations use random sampling to explore the behavior of complex systems. Molecular dynamics simulations numerically simulate particle motions under internal and external forces based on empirical energy functions. There are different levels of molecular dynamics simulations including atomistic, united atom, and coarse grained simulations, each with varying degrees of atomic detail and accessible timescales. Parameterized force fields are used to model interactions in lipid and protein systems. These computational methods provide insights into membrane and protein dynamics that are difficult to obtain experimentally.
Molecular Mechanics in Molecular ModelingAkshay Kank
In this slide you learn about the computational chemistry and its role in designing a drug molecule. Also learn concept about the molecular mechanics and its application to Computer Aided Drug Design. difference between the Quantum mechanics and Molecular Mechanics.
The document discusses various energy minimization methods used to optimize molecular geometries and find low energy conformations. It describes molecular mechanics force fields and parameters used in energy minimization. Common energy minimization methods include first-order methods like steepest descent and conjugate gradient, as well as second-order Newton-Raphson methods. Examples are given of minimizing the energies of small organic molecules like lactic acid and drug molecules glyburide and repaglinide using conjugate gradient minimization.
Molecular dynamics (MD) simulations calculate particle trajectories by integrating Newton's equations of motion. This document discusses the history and basic principles of MD, force fields, the NAMD simulation package, and applications. NAMD is a parallelized MD program for biomolecular simulations that uses spatial decomposition and multithreading. It supports features like CHARMM force fields, ensembles, and interactive modeling with VMD for structure visualization. MD simulations are useful for modeling protein structures, comparing protein templates, and predicting protein behavior through refinement of simulation approaches.
This document provides an overview of molecular dynamics (MD) simulation, which calculates the time-dependent behavior of biological molecules. MD simulation can provide detailed information on protein fluctuations and conformational changes. It is used to study protein stability, folding, molecular recognition and other biological processes. The document discusses how MD simulations are set up and run, including using force fields to calculate molecular interactions and numerical integration algorithms to solve equations of motion. It also covers statistical mechanics approaches for relating atomic-level simulation data to macroscopic properties.
This document outlines classical molecular dynamics simulations. It discusses using force fields to model molecular interactions and integrating equations of motion to simulate molecular motion. Molecular dynamics simulations allow studying processes such as protein folding but are limited by timescale. Ensembles, thermostats, and barostats control temperature, pressure and allow sampling different conditions. The document highlights challenges in achieving longer timescales and higher accuracy simulations.
Cloud Pharmaceuticals white paper.LIE_2016Shahar Keinan
Cloud Pharmaceuticals uses Quantum Molecular Design (QMD), which combines artificial intelligence, cloud computing, and quantum mechanics/molecular mechanics (QM/MM) calculations, to efficiently and accurately predict ligand binding potency to protein targets. QMD searches chemical space to design novel drug candidates and calculates binding affinities between targets and ligands. Results show QMD achieves high correlation between calculated and measured binding values for several protein targets, demonstrating its ability to predict ligand potency.
Computational chemistry uses theoretical chemistry calculations incorporated into computer programs to calculate molecular structures and properties. It can calculate properties such as structure, energy, charge distribution, and spectroscopic quantities using methods ranging from highly accurate ab initio methods to less accurate semi-empirical and molecular mechanics methods. Computational chemistry has advantages like allowing medicinal chemists to measure molecular geometry, energies, and perform conformational analysis using computer power. It can also determine ligand and target structures through computational docking methods.
Monte Carlo Simulations & Membrane Simulation and DynamicsArindam Ghosh
Monte Carlo simulations and molecular dynamics simulations are common computational methods to study membrane proteins and lipid bilayers. Monte Carlo simulations use random sampling to explore the behavior of complex systems. Molecular dynamics simulations numerically simulate particle motions under internal and external forces based on empirical energy functions. There are different levels of molecular dynamics simulations including atomistic, united atom, and coarse grained simulations, each with varying degrees of atomic detail and accessible timescales. Parameterized force fields are used to model interactions in lipid and protein systems. These computational methods provide insights into membrane and protein dynamics that are difficult to obtain experimentally.
Molecular Mechanics in Molecular ModelingAkshay Kank
In this slide you learn about the computational chemistry and its role in designing a drug molecule. Also learn concept about the molecular mechanics and its application to Computer Aided Drug Design. difference between the Quantum mechanics and Molecular Mechanics.
The document discusses various energy minimization methods used to optimize molecular geometries and find low energy conformations. It describes molecular mechanics force fields and parameters used in energy minimization. Common energy minimization methods include first-order methods like steepest descent and conjugate gradient, as well as second-order Newton-Raphson methods. Examples are given of minimizing the energies of small organic molecules like lactic acid and drug molecules glyburide and repaglinide using conjugate gradient minimization.
In photovoltaic (PV) systems, maximum power point tracking (MPPT) techniques are used to track the maximum power from the PV array under the change in irradiance and temperature conditions. The perturb and observe (P&O) is one of the most widely used MPPT techniques in recent times due to its simple implementation and improved performance. However, the P&O has limitations such as oscillation around the MPP during which time the P&O algorithm will become confused due to rapidly changing atmospheric conditions. To overcome the above limitation, this paper uses the fuzzy logic controller (FLC) to track the maximum power from the PV system under different irradiance, integrates it with a DC-DC boost converter as a tracker. The result of the FLC performance is compared with the traditional P&O method and shows the MPPT algorithm based on FLC ensures continuous tracking of the maximum power within a short period compared with the traditional P&O method. Besides that, the proposed method (FLC) has a faster dynamic response and low oscillations at the operating point around the MPP under steady-state conditions and dynamic change in irradiance.
This document discusses molecular mechanics force fields, specifically the Merck Molecular Force Field (MMFF). It provides details on the functional form and parameters of MMFF, including that it is a Class II force field designed to accurately model conformational energies and non-bonded interactions of pharmaceutical compounds. The total energy expression for MMFF is provided, including terms for internal interactions like bonds, angles, and torsions, as well as nonbonded van der Waals and electrostatic terms. Application of MMFF in the CHARMM program is also described.
This document discusses GROMACS, a software package for molecular dynamics simulations. GROMACS can simulate hundreds to millions of particles and is primarily used for biochemical molecules like proteins, lipids and nucleic acids. It contains tools like mdrun for basic molecular dynamics calculations and mpimdrun, which executes mdrun in parallel across multiple computers. Running GROMACS simulations can take 16-48 hours depending on the system, and using more computational cores allows faster simulations. The document proposes making GROMACS available on the GISELA e-infrastructure to allow researchers to perform molecular dynamics simulations without needing local computational resources.
Computational chemistry uses theoretical chemistry calculations incorporated into computer programs to calculate molecular structures and properties. It can calculate properties such as structure, energy, charge distribution, and spectroscopic quantities using methods that range from highly accurate ab initio methods to less accurate semi-empirical and molecular mechanics methods. Computational chemistry allows medicinal chemists to use computer power to measure molecular geometry, electron density, energies, and more for applications such as conformational analysis, docking ligands in receptor sites, and comparing ligands.
This document provides an overview of molecular dynamics (MD) simulations and their analysis. MD simulations calculate the time-dependent behavior of molecules and can be used to study conformational changes in proteins and nucleic acids. The document outlines various analyses that can be done on MD simulations including root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration, hydrogen bonding, secondary structure analysis using Ramachandran plots, free energy surfaces, and principal component analysis. It also provides examples of running MD simulations using VMD and applications of MD simulations such as understanding allostery and molecular docking.
This document discusses molecular mechanics and molecular dynamics simulations. It explains that molecular mechanics uses Newtonian mechanics to calculate energies and forces between atoms to model molecular motion. The potential energy is calculated based on contributions from bond lengths, bond angles, torsion angles, van der Waals interactions, and electrostatic interactions. Force fields are used to describe how potential energy depends on parameters. Energy minimization and molecular dynamics simulations are used to find low energy conformations and model molecular motion by overcoming energy barriers. Examples provided include simulations of benzene rings and modeling ATP and water in an enzyme active site.
Molecular modeling is a technique used to develop simplified models and simulations of molecular systems and chemical reactions. It allows scientists to investigate, interpret, and discover new phenomena that are difficult to study experimentally. Molecular modeling uses parameterized potential functions to describe molecular interactions and can be performed with specialized software. It has various applications including aiding drug design through direct and indirect methods, analyzing experimental data, and predicting molecular properties.
THE ENERGY MINIMIZATION, FOR THE STUDENTS OF M.PHARM, B.PHARM AND OTHERS USEFUL FOR ACADEMIC TOO. THE PRESENT DATA IS MOST USEFUL FOR PHARMACY PURPOSE.
Gaussian is a computational chemistry software package used to calculate the structures and properties of molecules. It uses quantum mechanics and density functional theory to solve chemical problems without experiments. Gaussian can optimize molecular geometries, calculate vibrational frequencies, and determine properties like infrared spectra. It provides information on molecular energies, structures, reaction pathways and more through simulation.
MPPT control of PV array based on PSO and adaptive controllerTELKOMNIKA JOURNAL
In general, Photovoltaic (PV) array is not able to generate maximum power automatically, because some partial shading caused by trees, clouds, or buildings. Irradiation imperfections received by the PV array are overcome by applying maximum power point tracking (MPPT) to the output of the PV array. In order to overcome these partial shading problems, this system is employing particle swarm optimization (PSO) as MPPT method. It optimizes the output power of the solar PV array by Zeta converter. Output voltage of MPPT has high rate such that it needs stepdown device to regulate certain voltage. Constant voltage will be the input voltage of buck converter and controlled using adaptive PID. Adaptive control based on model reference adaptive control (MRAC) has design that almost same as the conventional PID structure and it has better performance in several conditions. The proposed system is expected to have stable output and able to perfectly emulate the response of the reference model. From the simulation results, it appears that PSO have high tracking accuracy and high tracking speed to reach maximum power of PV array. In the output voltage regulation, adaptive control does not have a stable error status and consistently follows the set point value.
Advantages and applications of computational chemistrymanikanthaTumarada
The document discusses computational chemistry methods for calculating various thermodynamic and electronic properties of molecules. It provides an overview of computational chemistry and the properties that can be calculated, such as structure, energy, dipole moment, polarizability, ionization potential, HOMO/LUMO energies, chemical hardness and softness. It also describes different computational methods like classical molecular mechanics and molecular dynamics, as well as quantum chemistry methods including semi-empirical, ab initio and density functional theory approaches. Specific examples are given of calculating properties like dipole moment, polarizability, ionization potential using computational methods.
A comparison of molecular dynamics simulations using GROMACS with GPU and CPUAlex Camargo
This document compares the performance of molecular dynamics simulations using GROMACS run on a GPU versus a CPU. It finds that GPUs provide a significant speedup over CPUs for molecular dynamics simulations due to their highly parallel architecture. The document analyzes the performance of energy minimization, equilibration, and production molecular dynamics simulations of a protein-water system on a GPU and CPU. It shows that the GPU provides speedups of 4-8x for the different simulation steps compared to the CPU. The document concludes that GPUs are attractive for accelerating molecular dynamics simulations due to their superior parallel processing capabilities.
This document provides an overview of various molecular modeling software resources, including:
- Molecular mechanics programs like MM3, MM4, and CHARMM for modeling molecular structures and properties.
- Semi-empirical programs like MOPAC and Huckel-MO-calculator for electronic structure calculations.
- Ab initio programs like Gaussian for quantum mechanical modeling of molecules from first principles.
It briefly describes the capabilities and theoretical approaches of some of the major computational chemistry software options available.
The document discusses Cartesian coordinate systems and their use in molecular modeling. It describes how Cartesian coordinates are used to specify unique points in space using distances from perpendicular axes. Molecular graphics software uses Cartesian coordinates to visualize biological molecules by defining an coordinate frame of reference and assigning X, Y, Z coordinates. While Cartesian coordinates are used for modeling, other coordinate systems like cylindrical polar coordinates are sometimes used instead, especially for modeling helical molecules like DNA, and these first need transforming into Cartesian coordinates for visualization.
This thesis examines calculations of binding free energies between cucurbit[7]uril and small ligands using end-state molecular modeling methods. The author conducted molecular dynamics simulations using AMBER with implicit solvent models to calculate binding free energies, which were then compared to experimental values from the SAMPL4 challenge. Various error metrics including R2 correlation, root mean squared error, and linear regression slope were used to evaluate the results. The author found some improvement over previous methods, suggesting further refinement of conformational sampling could enhance the accuracy of binding free energy predictions.
Molecular mechanics uses classical mechanics to model molecular systems by calculating the potential energy. It can study small molecules as well as large biological systems with many thousands to millions of atoms. Molecular mechanics represents atoms as spheres and bonds as springs, with interactions described by classical potentials. It has been used to calculate properties like binding constants, protein folding kinetics, and to design binding sites.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
In photovoltaic (PV) systems, maximum power point tracking (MPPT) techniques are used to track the maximum power from the PV array under the change in irradiance and temperature conditions. The perturb and observe (P&O) is one of the most widely used MPPT techniques in recent times due to its simple implementation and improved performance. However, the P&O has limitations such as oscillation around the MPP during which time the P&O algorithm will become confused due to rapidly changing atmospheric conditions. To overcome the above limitation, this paper uses the fuzzy logic controller (FLC) to track the maximum power from the PV system under different irradiance, integrates it with a DC-DC boost converter as a tracker. The result of the FLC performance is compared with the traditional P&O method and shows the MPPT algorithm based on FLC ensures continuous tracking of the maximum power within a short period compared with the traditional P&O method. Besides that, the proposed method (FLC) has a faster dynamic response and low oscillations at the operating point around the MPP under steady-state conditions and dynamic change in irradiance.
This document discusses molecular mechanics force fields, specifically the Merck Molecular Force Field (MMFF). It provides details on the functional form and parameters of MMFF, including that it is a Class II force field designed to accurately model conformational energies and non-bonded interactions of pharmaceutical compounds. The total energy expression for MMFF is provided, including terms for internal interactions like bonds, angles, and torsions, as well as nonbonded van der Waals and electrostatic terms. Application of MMFF in the CHARMM program is also described.
This document discusses GROMACS, a software package for molecular dynamics simulations. GROMACS can simulate hundreds to millions of particles and is primarily used for biochemical molecules like proteins, lipids and nucleic acids. It contains tools like mdrun for basic molecular dynamics calculations and mpimdrun, which executes mdrun in parallel across multiple computers. Running GROMACS simulations can take 16-48 hours depending on the system, and using more computational cores allows faster simulations. The document proposes making GROMACS available on the GISELA e-infrastructure to allow researchers to perform molecular dynamics simulations without needing local computational resources.
Computational chemistry uses theoretical chemistry calculations incorporated into computer programs to calculate molecular structures and properties. It can calculate properties such as structure, energy, charge distribution, and spectroscopic quantities using methods that range from highly accurate ab initio methods to less accurate semi-empirical and molecular mechanics methods. Computational chemistry allows medicinal chemists to use computer power to measure molecular geometry, electron density, energies, and more for applications such as conformational analysis, docking ligands in receptor sites, and comparing ligands.
This document provides an overview of molecular dynamics (MD) simulations and their analysis. MD simulations calculate the time-dependent behavior of molecules and can be used to study conformational changes in proteins and nucleic acids. The document outlines various analyses that can be done on MD simulations including root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration, hydrogen bonding, secondary structure analysis using Ramachandran plots, free energy surfaces, and principal component analysis. It also provides examples of running MD simulations using VMD and applications of MD simulations such as understanding allostery and molecular docking.
This document discusses molecular mechanics and molecular dynamics simulations. It explains that molecular mechanics uses Newtonian mechanics to calculate energies and forces between atoms to model molecular motion. The potential energy is calculated based on contributions from bond lengths, bond angles, torsion angles, van der Waals interactions, and electrostatic interactions. Force fields are used to describe how potential energy depends on parameters. Energy minimization and molecular dynamics simulations are used to find low energy conformations and model molecular motion by overcoming energy barriers. Examples provided include simulations of benzene rings and modeling ATP and water in an enzyme active site.
Molecular modeling is a technique used to develop simplified models and simulations of molecular systems and chemical reactions. It allows scientists to investigate, interpret, and discover new phenomena that are difficult to study experimentally. Molecular modeling uses parameterized potential functions to describe molecular interactions and can be performed with specialized software. It has various applications including aiding drug design through direct and indirect methods, analyzing experimental data, and predicting molecular properties.
THE ENERGY MINIMIZATION, FOR THE STUDENTS OF M.PHARM, B.PHARM AND OTHERS USEFUL FOR ACADEMIC TOO. THE PRESENT DATA IS MOST USEFUL FOR PHARMACY PURPOSE.
Gaussian is a computational chemistry software package used to calculate the structures and properties of molecules. It uses quantum mechanics and density functional theory to solve chemical problems without experiments. Gaussian can optimize molecular geometries, calculate vibrational frequencies, and determine properties like infrared spectra. It provides information on molecular energies, structures, reaction pathways and more through simulation.
MPPT control of PV array based on PSO and adaptive controllerTELKOMNIKA JOURNAL
In general, Photovoltaic (PV) array is not able to generate maximum power automatically, because some partial shading caused by trees, clouds, or buildings. Irradiation imperfections received by the PV array are overcome by applying maximum power point tracking (MPPT) to the output of the PV array. In order to overcome these partial shading problems, this system is employing particle swarm optimization (PSO) as MPPT method. It optimizes the output power of the solar PV array by Zeta converter. Output voltage of MPPT has high rate such that it needs stepdown device to regulate certain voltage. Constant voltage will be the input voltage of buck converter and controlled using adaptive PID. Adaptive control based on model reference adaptive control (MRAC) has design that almost same as the conventional PID structure and it has better performance in several conditions. The proposed system is expected to have stable output and able to perfectly emulate the response of the reference model. From the simulation results, it appears that PSO have high tracking accuracy and high tracking speed to reach maximum power of PV array. In the output voltage regulation, adaptive control does not have a stable error status and consistently follows the set point value.
Advantages and applications of computational chemistrymanikanthaTumarada
The document discusses computational chemistry methods for calculating various thermodynamic and electronic properties of molecules. It provides an overview of computational chemistry and the properties that can be calculated, such as structure, energy, dipole moment, polarizability, ionization potential, HOMO/LUMO energies, chemical hardness and softness. It also describes different computational methods like classical molecular mechanics and molecular dynamics, as well as quantum chemistry methods including semi-empirical, ab initio and density functional theory approaches. Specific examples are given of calculating properties like dipole moment, polarizability, ionization potential using computational methods.
A comparison of molecular dynamics simulations using GROMACS with GPU and CPUAlex Camargo
This document compares the performance of molecular dynamics simulations using GROMACS run on a GPU versus a CPU. It finds that GPUs provide a significant speedup over CPUs for molecular dynamics simulations due to their highly parallel architecture. The document analyzes the performance of energy minimization, equilibration, and production molecular dynamics simulations of a protein-water system on a GPU and CPU. It shows that the GPU provides speedups of 4-8x for the different simulation steps compared to the CPU. The document concludes that GPUs are attractive for accelerating molecular dynamics simulations due to their superior parallel processing capabilities.
This document provides an overview of various molecular modeling software resources, including:
- Molecular mechanics programs like MM3, MM4, and CHARMM for modeling molecular structures and properties.
- Semi-empirical programs like MOPAC and Huckel-MO-calculator for electronic structure calculations.
- Ab initio programs like Gaussian for quantum mechanical modeling of molecules from first principles.
It briefly describes the capabilities and theoretical approaches of some of the major computational chemistry software options available.
The document discusses Cartesian coordinate systems and their use in molecular modeling. It describes how Cartesian coordinates are used to specify unique points in space using distances from perpendicular axes. Molecular graphics software uses Cartesian coordinates to visualize biological molecules by defining an coordinate frame of reference and assigning X, Y, Z coordinates. While Cartesian coordinates are used for modeling, other coordinate systems like cylindrical polar coordinates are sometimes used instead, especially for modeling helical molecules like DNA, and these first need transforming into Cartesian coordinates for visualization.
This thesis examines calculations of binding free energies between cucurbit[7]uril and small ligands using end-state molecular modeling methods. The author conducted molecular dynamics simulations using AMBER with implicit solvent models to calculate binding free energies, which were then compared to experimental values from the SAMPL4 challenge. Various error metrics including R2 correlation, root mean squared error, and linear regression slope were used to evaluate the results. The author found some improvement over previous methods, suggesting further refinement of conformational sampling could enhance the accuracy of binding free energy predictions.
Molecular mechanics uses classical mechanics to model molecular systems by calculating the potential energy. It can study small molecules as well as large biological systems with many thousands to millions of atoms. Molecular mechanics represents atoms as spheres and bonds as springs, with interactions described by classical potentials. It has been used to calculate properties like binding constants, protein folding kinetics, and to design binding sites.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Arm Robot Surveillance Using Dual Tone Multiple Frequency TechnologyIJERA Editor
Surveillance place a pivotal role in addressing a wide range of security challenges .In the present paper we propose a Dual Tone Multiple Frequency ( DTMF) based Robot with video surveillance. In the proposed model a DTMF based Robot with video surveillance with multiple key functions, Arm picker and security system was implemented. Master and slave concept using 3 Microcontroller and motor driver IC to drive motors was implemented and belt wheel platform was used to move the robot from one place to another. Multiple key functions were used to perform more functions and a camera for surveillance .The robot can navigate with the help of the user.
Evaluation of Euclidean and Manhanttan Metrics In Content Based Image Retriev...IJERA Editor
This document evaluates the performance of the Euclidean and Manhattan distance metrics in a content-based image retrieval system. It finds that the Manhattan distance metric showed better precision than the Euclidean distance metric. The system uses color histograms and Gabor texture features to represent images. Color is represented in HSV color space and histograms of hue, saturation and value are used. Gabor filters are applied to capture texture at different scales and orientations. Distance between feature vectors is calculated using Euclidean and Manhattan distance formulas to find similar images from the database. The system was tested on a dataset of 1000 Corel images and Manhattan distance produced more relevant search results.
Study and Analysis of Six Stroke EngineIJERA Editor
Six Stroke engine, the name itself indicates a cycle of six strokes out of which two are useful power strokes. According to its mechanical design, the six-stroke engine with external and internal combustion and double flow is similar to the actual internal reciprocating combustion engine. However, it differentiates itself entirely, due to its thermodynamic cycle and a modified cylinder head with two supplementary chambers: combustion and an air heating chamber, both independent from the cylinder. In this the cylinder and the combustion chamber are separated which gives more freedom for design analysis. In addition to the two valves in the four stroke engine two more valves are incorporated which are operated by a piston arrangement. The Six Stroke is thermodynamically more efficient because the change in volume of the power stroke is greater than the intake stroke and the compression stroke. The main advantages of six stroke engine includes reduction in fuel consumption by 40%, two power strokes in the six stroke cycle, dramatic reduction in pollution, adaptability to multi fuel operation. Six stroke engine’s adoption by the automobile industry would have a tremendous impact on the environment and world economy .
This document summarizes a research paper that proposes a method for converting images and video into portraits and animations using RGB color segmentation. The method involves several steps: edge detection using Sobel operator, blurring the image with Gaussian blur to reduce noise, color segmentation by comparing RGB pixel values to a threshold, and region filling to convert the image into a portrait. The overall goal is to automatically convert still images and video into animated portraits without requiring design of characters or additional software.
This document summarizes a research paper that proposes a microcontroller-based cryptosystem using the Tiny Encryption Algorithm (TEA) combined with a Key Generation Unit (KGU). The KGU uses timers in the microcontroller to generate random bits for encryption keys. The cryptosystem can operate in serial or wireless transmission modes. Performance analysis shows the cryptosystem has improved throughput and decreased execution time compared to TEA alone. Randomness testing of the generated keys indicates distinct random bits. In conclusion, the system provides moderate security and simplicity for applications requiring secured data transfer with low cost and memory constraints.
The document summarizes research on copper oxide (CuO) dispersed polyvinyl alcohol (PVA) polymer films. Five films were prepared with varying concentrations of CuO nanoparticles (0 wt%, 2.5 wt%, 5 wt%, 7.5 wt%, and 10 wt%). The films were characterized through various analyses. X-ray diffraction and scanning electron microscopy showed the inclusion of CuO nanoparticles in the PVA matrix. Optical band gap decreased from 3.47 eV to 1.63 eV with increasing CuO concentration. Photoluminescence spectra showed increased wavelength emission with higher CuO content. Electrical conductivity increased with rising temperature and CuO concentration, indicating improved electronic conduction in the composites.
The document summarizes a study that used numerical modeling and laboratory experiments to evaluate the effectiveness of steam injection for remediating soils contaminated with light non-aqueous phase liquids (LNAPLs) like kerosene. The numerical modeling was done using MATLAB and governing equations were developed. The experimental aspect involved injecting dry steam into sand columns containing saturated mixtures of kerosene and sand. As steam was introduced, the kerosene's viscosity decreased due to increased temperature, causing it to flow and be recovered over time. The study found that higher injection pressures and larger sand grain sizes increased kerosene flow rates and reduced treatment time, and that grain size affected recovery rates, efficiency, and treatment time needed for cleanup. Steam
Mariana se enoja cuando su amiga Julia rompe su juego de té nuevo que le habían regalado. Su madre le aconseja que deje secar su ira antes de tomar represalias o pedir explicaciones, recordándole un incidente pasado donde su abuela le dijo lo mismo. Más tarde, Julia viene a disculparse y explica que fue otro niño quien rompió el juego, no ella. Mariana acepta sus disculpas porque siguió el consejo de su madre de dejar que su ira se secara primero.
Proejto quer impedir concursos de Ensino Médio de cobrar conhecimento em DireitoPaulo Veras
Projeto do deputado Fernando Filho (PSB-PE) apresentou um projeto que impede concursos para cargos de Ensino Médio de exigirem conhecimento em Direito. O projeto de Lei 643 acaba com a exigência de conhecimentos jurídicos para cargos que não exijam formação superior.
O documento analisa as contas do governo de Pernambuco de 2013 e recomenda sua aprovação com algumas ressalvas e recomendações, como monitorar o déficit da previdência, controlar gastos com organizações sociais, e intensificar a fiscalização de parcerias público-privadas.
El documento habla sobre el lado técnico de la publicidad digital. Explica que los anuncios publicitarios en los sitios web son administrados por un servidor de anuncios (ad-server) y que cada medio tiene su propia plataforma de ad-serving. También describe el proceso operativo de una campaña publicitaria que incluye el envío del banner a cada medio, la subida al ad-server, la configuración de parámetros y la ejecución de la campaña.
Arquitecturas de Referencia para los Repositorios y Preservación de ArchivosRIBDA 2009
El documento presenta una arquitectura de referencia para repositorios y preservación de archivos digitales. Describe los desafíos de almacenamiento de contenido digital en crecimiento y la necesidad de una infraestructura flexible. Explica el modelo OAIS para depósitos y preservación de archivos digitales y las funciones y flujos de información. Proporciona recomendaciones para el desarrollo de arquitecturas de referencia replicables que minimizan los costos a través de la gestión automatizada de datos y migración entre niveles de al
Para crear un blog, primero se debe crear una cuenta en Blogger u otro servicio de blogs. Luego, al acceder a la cuenta, se debe hacer clic en "crear blog" para completar los detalles del blog y seleccionar una plantilla. Una vez creado el blog, se puede personalizar el diseño mediante la selección de una nueva plantilla o la descarga e inserción de una plantilla externa.
Este documento presenta el reglamento general de un instituto, el cual define los derechos y obligaciones de los alumnos. Entre los derechos se incluyen recibir formación académica, ser tratados con respeto, y presentar quejas. Las obligaciones incluyen cumplir con el reglamento institucional, asistir a clases, y comportarse de manera respetuosa. También se especifican los procedimientos para presentar quejas y solicitar revisiones de calificaciones.
Computational Chemistry aspects of Molecular Mechanics and Dynamics have been discussed in this presentation. Useful for the Undergraduate and Postgraduate students of Pharmacy, Drug Design and Computational Chemistry
Introduction to Computational chemistry-Javed Iqbal
Computational chemistry uses theoretical chemistry calculations incorporated into computer programs to calculate molecular structure and properties. It can calculate properties such as structure, energy, charge distribution, and spectroscopic quantities using methods ranging from highly accurate ab initio methods to less accurate semi-empirical and molecular mechanics methods. Computational chemistry allows medicinal chemists to use computer power to study molecular geometry, electron density, conformations, and energies.
1) Molecular modeling techniques such as molecular mechanics, quantum mechanics, and energy minimization methods are used in computer-aided drug design to understand drug-receptor interactions and design new drug molecules.
2) The goal of target-based drug design is to identify or create novel molecules that bind to a selected target and elicit a biological response through techniques like molecular docking, de novo design, and virtual screening.
3) Computer-aided drug design uses molecular modeling to represent molecules in 3D and relate their structure and conformation to energy through mathematical equations in order to optimize properties and design new drugs.
The document discusses various molecular modeling and computational chemistry techniques used to simulate molecular systems, including molecular dynamics, molecular mechanics, quantum mechanics methods, and molecular docking. It provides an overview of the different modeling strategies and computational tools used, such as determining receptor geometry from X-ray crystallography, energy minimization techniques, force field parameters, and quantum mechanical calculations. The goal of molecular modeling is to develop accurate models of molecular systems to predict properties and behavior without experimental testing.
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The calculation and results of simulation of the magnetic control system for the spacecraft momentum are presented in the paper. The simulation includes an assessment of the reliability of calculating the Earth's magnetic field parameters, as well as an assessment of the quality of object stabilization by resetting the total momentum with the aid of the system under review. The outcome of a comparative analysis of resource efficiency and energy efficiency are demonstrated in the implementation of the proposed hardware models of controllers on FPGA. The strengths and weaknesses of the programming models are shown. The developed models will allow to be modified and perform more complex operations in the future.
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1. Nulaka Srinivasu, M. Naresh Babu, Allam Appa Rao / International Journal of Engineering
Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1884-1887
Energy Minimization of CDK2 bound ligands: A Computational
Approach
Nulaka Srinivasu*, M. Naresh Babu**, Allam Appa Rao***
*(Department of Computer Science (MCA), KGRL College, Bhimavaram.)
** (Assistant Professor, C R Rao AIMSCS, UoH Campus, Hyderabad)
*** (Director, C R Rao AIMSCS, UoH Campus, Hyderabad)
ABSTRACT processes which affect functional properties of the
Cell proliferation is a consequence of biomolecule [3][4].
positive signals which promote cell division and
negative signals which suppress the process. Key However, long MD simulations are mathematically
factors in this signaling cascade are a series of ill-conditioned, generating cumulative errors in
cyclin dependent kinases (CDKs). It has been numerical integration that can be minimized with
identified experimentally that CDK enzymes are proper selection of algorithms and parameters, but
highly flexible and the ligand binding orientations not eliminated entirely.
are primarily influenced by side chain torsions of The term molecular mechanics (MM)
amino acids in active site region. Ligands internal refers to the use of Newtonian mechanics to model
energy needs to be minimized before performing molecular systems. The potential energy of all
docking experiments. Energy needs to be systems in molecular mechanics is calculated using
minimized for high stability. Energy can be force fields. Molecular mechanics can be used to
minimized efficiently by using molecular study small molecules as well as large biological
mechanics and molecular dynamics techniques. systems or material assemblies with many thousands
Two different co-crystallized ligands of 1H1S and to millions of atoms.
1OIT (CDK2 Proteins) are selected to find their The great computational speed of
minimum energy states using molecular molecular mechanics allows for its use in
mechanics and molecular dynamics algorithms procedures such as molecular dynamics,
reveals minimum energy state of these ligands can conformational energy searching, and docking that
obtained using fletcher reeves algorithm of MM+ require large numbers of energy evaluations.
force-field. Molecular mechanics methods are based on the
following principles:
Keywords: CDK, Molecular Mechanics, Nuclei and electrons are lumped into atom-like
Molecular Dynamics, Energy Minimization, particles.
computational drug discovery Atom-like particles are spherical (radii obtained
from measurements or theory) and have a net
I. INTRODUCTION charge (obtained from theory).
Molecular dynamics (MD) is a form of Interactions are based on springs and classical
computer simulation wherein atoms and molecules potentials.
are allowed to interact for a period of time under Interactions must be pre assigned to specific sets
known laws of physics, giving a view of the motion of atoms.
of the atoms. Because molecular systems generally Interactions determine the spatial distribution of
consist of a vast number of particles, it is impossible atom-like particles and their energies.[5]
to find the properties of such complex systems
analytically; MD simulation circumvents this II. MATERIALS AND METHODS
problem by using numerical methods. It represents HYPERCHEM SOFTWARE:
an interface between laboratory experiments and HyperChem (http://www.hyper.com/)
theory, and can be understood as a "virtual software is a molecular modeling and computational
experiment" [1] [2]. chemistry system for constructing molecular
Molecular dynamics is a multidisciplinary structures, computing their electronic energies,
method. Its laws and theories stem from optimum geometries and for simulating their
mathematics, physics, and chemistry, and it employs vibrational motion including chemical reactions.
algorithms from computer science and information Molecules can readily be built and displayed on the
theory. MD allows studying the dynamics of large computer's monitor by making selections from the
macromolecules, including biological systems such system's menus with the computer's mouse. When
as proteins, nucleic acids (DNA, RNA), membranes. constructing a molecule in this way the system
Dynamical events may play a key role in controlling checks that the normal valence of each element is
not exceeded, but the user may disable this checking
1984 | P a g e
2. Nulaka Srinivasu, M. Naresh Babu, Allam Appa Rao / International Journal of Engineering
Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1884-1887
in order to create other valence states or to build Energy Minimization using Molecular Mechanics
charged structures such as ionic complexes. After Therefore, hyperchem software was employed to
sketching the structure of the molecule, the user perform the task and the results are given below. In
selects "build" and the system adjusts the bond the given example, two bound ligands are selected
lengths and angles to standard values, and at the to analyze or test the ability of few algorithms to
same time converts the 2-dimensional sketch into a reduce the energy states of ligands under default
3-dimensional structure. conditions.
HyperChem has several alternative The geometry of these generated 3D
algorithms for finding the optimum geometry. This models are optimized to get minimum energy state
minimum-energy, equilibrium geometry is of using various molecular mechanics optimization
primary interest to the structure of stable molecules. algorithms like Steepest descent, Fletcher –Reeves
HyperChem offers several different quantum (conjugate gradient), Polak-Ribiere (conjugate
mechanical methods to characterize and predict the gradient) under molecular mechanics force fields
structure and stability of chemical systems, to like MM+, AMBER, BIOCHARMM and OPLS.
estimate energy differences between different states,
and to explain reaction pathways and mechanism
(nuclear motion) at the atomic level These
calculations require much CPU time, and in practice
the choice of method is usually a compromise
between the time required for the calculation and the
accuracy obtained.
Fig3: Image showing various molecular mechanics
force fields applied on ligands
Fig 1: Generation of 3dimensional structure of Energy minimization using Molecular Dynamics:
gemcitabine using HyperChem software. A file was opened in HyperChem software,
The geometry of these generated 3D which is the output of energy minimization using
models are optimized to get minimum energy state molecular mechanics methods, is considered as the
using various molecular mechanics optimization input for the molecular dynamics run. For example
algorithms like Steepest descent, Fletcher –Reeves all the ligands has shown the lowest energy value in
(conjugate gradient), Polak-Ribiere (conjugate the fletcher reeves algorithm of MM+ force-field
gradient) under molecular mechanics force fields and this was subjected to molecular dynamic run
like MM+, AMBER, BIOCHARMM and OPLS. providing the various parameters like Heat time -
0.2ps, Runtime- 1 ps, Cool time- 0.2ps, starting
temperature-0K, simulation time-500K, final
temperature-0K, temperature step-10K. The
averages of the potential energy, kinetic energy and
the total energy graph were obtained simultaneously
along with the energy value in molecular dynamics
by proceeding further. Thus the molecular dynamics
was performed likewise for all the 4 molecules,
changing the run time from 1-5 picoseconds and
keeping all the other parameters constant
III. RESULTS AND DISCUSSIONS
Ligands internal energy needs to be
Fig 2: Image showing various molecular mechanics minimized before docking experiments, such energy
algorithms applied on ligands minimization can be carried out efficiently by
employing molecular mechanics and molecular
1985 | P a g e
3. Nulaka Srinivasu, M. Naresh Babu, Allam Appa Rao / International Journal of Engineering
Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1884-1887
dynamics techniques using HyperChem software. Table 4: Molecular dynamics run of 1OIT_ligand
Two different co-crystallized ligands of 1H1S and using various run times.
1OIT (taken from PDB) are selected to find there Liagand Runtime (pS) Energy(kcal/
minimum energy states using molecular mechanics mol)
and molecular dynamics algorithms. 1 56.2851
Energy minimization using Molecular Mechanics: 2 53.6117
The minimum energies states obtained for 3 56.6788
the two selected ligands in molecular mechanics 1OIT_ligand
method are tabulated in Table 1and Table 2. 4 54.0676
Energy differences between various force-
fields and algorithms suggest that the minimum 5 55.1931
energy state of 1H1S_ligand can obtained using
fletcher reeves algorithm of MM+ force-field
(34.3235kcal/mol). Following the above analysis, remaining all
Energy differences between various force- ligands bound to CDK-2 are energy minimized
fields and algorithms suggest that the minimum using Flectcher-reeves algorithm and further taken
energy state of 1H1S_ligand can obtained using up for docking analysis.
fletcher reeves algorithm with MM+ force-field
(47.9043kcal/mol). IV. CONCLUSIONS AND FUTURE SCOPE
From the above data obtained by Ligands internal energy needs to be
performing energy minimization using various minimized before docking experiments. A
molecular mechanics optimization methods , we can molecular mechanics and dynamics approach was
infer that MM+ molecular mechanics force field employed to evaluate the importance of algorithms
with Fletcher reeves algorithm gives better in minimizing the energy of ligands (1H1S_ligand
optimization of ligands than others. and 1OIT_ligand). Energy optimization using
molecular mechanics approach resulted in Flecher-
Energy minimization using Molecular Dynamics: Revees algorithm under MM+ force field as better
1H1S_ligand: optimization method. Molecular dynamics run in
1H1S_ligand was subjected to molecular dynamics, vacuum conditions show lowest energies for
changing the run time from 1-5 picoseconds and gemcitabine at 3ps (16.74 kcal/mol), mitoxanthrona
keeping all the other parameters constant, the lowest at 2ps (23.22 kcal/mol), 1H1S_ligand at 5ps (35.89
energy value was obtained for the run time 5 ps kcal/mol) and 1OIT_ligand at 2ps (53.61 kcal/mol)
(35.8976 kcal/mol) as shown in Table 3. respectively. The minimized energy for
1H1S_ligand is 34.3235 kcal/mol and for
Table 3: Molecular dynamics run of 1H1S_ligand 1OIT_ligand is 47.9034 kcal/mol. Further remaining
using various run times all ligands bound to CDK-2 proteins are energy
liagand Runtime (pS) Energy(kcal/ minimized using Flectcher-reeves algorithm and
mol) further taken up for docking analysis.
1 38.9995
2 42.1432 V. ACKNOWLEDGMENTS
1H1S_ligand 3 39.7106 Dr. Allam Appa Rao and Dr. M. Naresh
4 40.9952 Babu would like to thank the Dept. of Science and
5 Technology for their financial support (DST-CMS
35.8976
GoI Project No.SR/S4/MS:516/07 Dated
21.04.2008)
1OIT_ligand:
1OIT_ligand was subjected to molecular
dynamics, changing the run time from 1-5 REFERENCES
picoseconds and keeping all the other parameters [1] D. Frenkel, et. al; “Understanding
constant, the lowest energy value was obtained for Molecular Simulation: From Algorithms to
the run time 2ps (53.6117 kcal/mol) as listed in Applications”(2001)
Table 4. [2] D. C. Rapaport; “The Art of Molecular
Dynamics Simulations” (2004)
[3] H. J. C. Berendsen, Molecular Dynamics
Simulation of Stadistical-Mechanical
Systems, p. 496. North-Holland, 1986. G.
Ciccotti and W. G. Hoover (Editors).
[4] H. J. C. Berendsen Comp. Phys. Commun.,
no. 44, p. 233, 1987
[5] http://biochem-vivek.tripod.com/id26.html
1986 | P a g e
4. Nulaka Srinivasu, M. Naresh Babu, Allam Appa Rao / International Journal of Engineering
Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1884-1887
ANNEXURE
1H1S_ligand: ( 4-[[6-(cyclohexylmethoxy)-9H-purin-2- yl] amino]benzenesulfonamide )
Table 1: Energy minimized data of 1H1S_ligand molecule using various Molecular Mechanics algorithms.
Force-field Geometry optimization Energy (kcal/mol)
MM+ STEEPEST DESCENT 35.8962
FLETCHER REEVES 34.3235
POLAK-RIBIERE 34.3631
NEWTON-RAPSON 34.0952
AMBER STEEPEST DESCENT 51.9762
FLETCHER REEVES 51.0968
POLAK RIBIERE 51.1408
BIOCHARMM STEEPEST DESCENT 100.5240
FLETCHER REEVES 99.5412
POLAK RIBIERE 99.4335
OPLS STEEPEST DESCENT 39.6702
FLETCHER REEVES 38.8010
POLK RIBIERE 38.7903
10IT_ligand: (4-[(4-imidazo[3,2-a]pyridin-3-ylpyrimidin-2-yl)amino]benzenesulfonamide)
Table 2: Energy minimized data of 1OIT_ligand molecule using various Molecular Mechanics algorithms.
Force-field Geometry optimization Energy (kcal/mol)
MM+ STEEPEST DESCENT 48.3266
MM+ FLETCHER REEVES 47.9034
POLAK RIBIERE 47.9652
AMBER STEEPEST DESCENT 65.1429
FLETCHER REEVES 63.2049
POLAK RIBIERE 63.2717
BIOCHARMM STEEPEST DESCENT 74.9808
FLETCHER REEVES 73.9558
POLAK RIBIERE 73.8895
OPLS STEEPEST DESCENT 50.0360
FLETCHER REEVES 48.9933
POLAK RIBIERE 48.8810
1987 | P a g e