This document provides an overview of computational chemistry and computational tools used in different fields. It defines computational chemistry and computational quantum chemistry. It discusses the concept of computational models, including ab initio quantum chemistry methods that do not include empirical parameters. It describes different computational models from most to least accurate, including ab initio, semi-empirical, and molecular mechanics methods. It provides details on molecular mechanics and how it estimates molecular energetics without using quantum mechanics. The document also discusses semi-empirical and ab initio methods and levels of theory. It states that high-speed supercomputers and suitable software programs are needed for computational chemistry. It provides examples of commonly used computational chemistry software.
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.
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
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.
Computational chemistry uses numerical simulations based on the laws of physics to model chemical structures and reactions. There are different types of computational models of varying accuracy and computational cost, including molecular mechanics, semi-empirical, ab initio, and density functional theory methods. The accuracy of calculations also depends on the basis set used to describe molecular orbitals. Computational chemistry has become an important tool for characterizing nanomaterials.
Introduction to Computational chemistry-Javed Iqbal
油
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.
Molecular Mechanics in Molecular ModelingAkshay Kank
油
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.
Computational chemistry uses computers to simulate chemical systems and solve equations that model their properties. It is considered a third pillar of scientific investigation, along with theory and experiment. There are several computational methodologies including quantum mechanics, molecular mechanics, and molecular dynamics. Computational chemistry software can be used to optimize molecular geometries, map potential energy surfaces, perform conformational analyses, and calculate many other molecular properties and reaction kinetics. These methods have improved significantly with increasing computer power over the past few decades.
molecular mechanics and quantum mechnicsRAKESH JAGTAP
油
This document discusses molecular modeling methods, including quantum mechanics and molecular mechanics approaches. It describes the differences between quantum mechanics methods like ab initio, semi-empirical, and density functional theory in terms of system size, accuracy, and computational cost. Molecular mechanics is described as using empirical parameters and energy terms for bonding and non-bonding interactions. The document also discusses the hybrid QM/MM approach and applications of molecular modeling like structure-based drug design.
This document discusses parameterization of force fields for molecular mechanics simulations. It describes how parameters are determined for force fields like AMBER and CHARMM from experimental data and quantum calculations. The parameters include values for bonds, angles, dihedrals, van der Waals interactions, and electrostatic terms that describe the energy landscape for molecular simulations. Both bonding and nonbonding terms are considered in the parameterization process.
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.
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.
Computational chemistry uses mathematical and computing methods to simulate chemical processes. It can predict molecular properties, structures, interactions and reaction pathways without expensive experiments. The main computational methods are ab initio, semi-empirical, density functional theory, molecular mechanics and molecular dynamics. Geometry optimization finds the lowest energy conformation of a molecule using algorithms to minimize the potential energy surface. It is important for understanding how structure influences properties and reactivity.
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
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 modelling-Needs and charcteristicssopma1
油
The term Molecular modeling expanded over the last decades from a tool to visualize three-dimensional structures and to simulate , predict and analyze the properties and the behavior of the molecules on an atomic level to data mining.
Overview combining ab initio with continuum theoryDierk Raabe
油
Multi-methodological approaches combining quantum-mechanical and/or atomistic simulations
with continuum methods have become increasingly important when addressing multi-scale phenomena in
computational materials science. A crucial aspect when applying these strategies is to carefully check,
and if possible to control, a variety of intrinsic errors and their propagation through a particular multimethodological
scheme. The first part of our paper critically reviews a few selected sources of errors
frequently occurring in quantum-mechanical approaches to materials science and their multi-scale propagation
when describing properties of multi-component and multi-phase polycrystalline metallic alloys.
Our analysis is illustrated in particular on the determination of i) thermodynamic materials properties at
finite temperatures and ii) integral elastic responses. The second part addresses methodological challenges
emerging at interfaces between electronic structure and/or atomistic modeling on the one side and selected
continuum methods, such as crystal elasticity and crystal plasticity finite element method (CEFEM and
CPFEM), new fast Fourier transforms (FFT) approach, and phase-field modeling, on the other side.
This document provides an overview of molecular modeling software and computational methods for modeling molecules, including molecular mechanics, semiempirical quantum mechanics modeling, and CaCHE modeling software. It discusses using molecular modeling to visualize molecules, match molecular structures, determine molecular properties using force fields, and correlate molecular properties with electronic structure calculations. Finally, it describes options for semiempirical quantum mechanics methods that can be used to compute properties like bond orders, dipole moments, and potential energy maps.
Molecular modelling for M.Pharm according to PCI syllabusShikha Popali
油
THE MOLECULAR MODELLING IS THE MOST IMPORTANT TOPIC FOR CHEMISTRY STUDENTS , HENCE THE THEORY OF MOLECULAR MODELLING IS COVER IN THIS PRESNTATION . HOPE THIS MATTER SAISFY ALL AS WE HAVE TRIED TO ATTEMPT ALL TH TOPICS OF IT.
This document provides a summary of computational organic chemistry methods for investigating molecular structures, properties, reactivities, and selectivities. It describes the basic concepts of molecular mechanics and quantum chemistry methods, including their advantages and limitations. Applications include determining molecular geometries and conformations, absolute configurations, electron distributions, acidities, and frontier molecular orbital energies to examine reactivity and selectivity. Combining computational methods with experiments allows more reliable investigations.
This document discusses the foundations of chemical kinetic modeling and reaction models. It outlines the key pillars of knowledge required, including general chemistry, thermodynamics, chemical kinetics, and quantum chemistry. It then describes the step-wise process for constructing detailed chemical kinetic models, including determining elementary reactions, estimating thermo-chemical data and rate coefficients, validating models experimentally, and applying the models to reactor scale-up and design. Reactor scale-up requires satisfying similarity parameters between small and large-scale systems. The goal is to develop accurate predictive models and design safe, commercial-scale chemical reactors.
The document describes AFMM, a program for parametrizing molecular mechanics force fields. AFMM iteratively optimizes force field parameters to fit normal modes from quantum chemical calculations. It minimizes a merit function considering both vibrational frequencies and eigenvector projections. The program uses a Monte Carlo algorithm to refine parameters and improve the fit to reference quantum data, replacing manual parametrization.
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.
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.
Quantum calculations and calculational chemistrynazanin25
油
This document discusses computational chemistry and different methods for calculating molecular structure and properties using computers. It describes two main approaches: molecular mechanics, which views molecules as collections of atoms and calculates potential energy based on bonding parameters; and quantum mechanics, which uses the Schrodinger equation and approximations like Born-Oppenheimer and molecular orbital theory. Specific quantum methods discussed include semi-empirical, ab initio, and density functional theory. Popular computational programs and visualization software are also listed.
Computational chemistry uses computers to simulate chemical systems and solve equations that model their properties. It is considered a third pillar of scientific investigation, along with theory and experiment. There are several computational methodologies including quantum mechanics, molecular mechanics, and molecular dynamics. Computational chemistry software can be used to optimize molecular geometries, map potential energy surfaces, perform conformational analyses, and calculate many other molecular properties and reaction kinetics. These methods have improved significantly with increasing computer power over the past few decades.
molecular mechanics and quantum mechnicsRAKESH JAGTAP
油
This document discusses molecular modeling methods, including quantum mechanics and molecular mechanics approaches. It describes the differences between quantum mechanics methods like ab initio, semi-empirical, and density functional theory in terms of system size, accuracy, and computational cost. Molecular mechanics is described as using empirical parameters and energy terms for bonding and non-bonding interactions. The document also discusses the hybrid QM/MM approach and applications of molecular modeling like structure-based drug design.
This document discusses parameterization of force fields for molecular mechanics simulations. It describes how parameters are determined for force fields like AMBER and CHARMM from experimental data and quantum calculations. The parameters include values for bonds, angles, dihedrals, van der Waals interactions, and electrostatic terms that describe the energy landscape for molecular simulations. Both bonding and nonbonding terms are considered in the parameterization process.
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.
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.
Computational chemistry uses mathematical and computing methods to simulate chemical processes. It can predict molecular properties, structures, interactions and reaction pathways without expensive experiments. The main computational methods are ab initio, semi-empirical, density functional theory, molecular mechanics and molecular dynamics. Geometry optimization finds the lowest energy conformation of a molecule using algorithms to minimize the potential energy surface. It is important for understanding how structure influences properties and reactivity.
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
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 modelling-Needs and charcteristicssopma1
油
The term Molecular modeling expanded over the last decades from a tool to visualize three-dimensional structures and to simulate , predict and analyze the properties and the behavior of the molecules on an atomic level to data mining.
Overview combining ab initio with continuum theoryDierk Raabe
油
Multi-methodological approaches combining quantum-mechanical and/or atomistic simulations
with continuum methods have become increasingly important when addressing multi-scale phenomena in
computational materials science. A crucial aspect when applying these strategies is to carefully check,
and if possible to control, a variety of intrinsic errors and their propagation through a particular multimethodological
scheme. The first part of our paper critically reviews a few selected sources of errors
frequently occurring in quantum-mechanical approaches to materials science and their multi-scale propagation
when describing properties of multi-component and multi-phase polycrystalline metallic alloys.
Our analysis is illustrated in particular on the determination of i) thermodynamic materials properties at
finite temperatures and ii) integral elastic responses. The second part addresses methodological challenges
emerging at interfaces between electronic structure and/or atomistic modeling on the one side and selected
continuum methods, such as crystal elasticity and crystal plasticity finite element method (CEFEM and
CPFEM), new fast Fourier transforms (FFT) approach, and phase-field modeling, on the other side.
This document provides an overview of molecular modeling software and computational methods for modeling molecules, including molecular mechanics, semiempirical quantum mechanics modeling, and CaCHE modeling software. It discusses using molecular modeling to visualize molecules, match molecular structures, determine molecular properties using force fields, and correlate molecular properties with electronic structure calculations. Finally, it describes options for semiempirical quantum mechanics methods that can be used to compute properties like bond orders, dipole moments, and potential energy maps.
Molecular modelling for M.Pharm according to PCI syllabusShikha Popali
油
THE MOLECULAR MODELLING IS THE MOST IMPORTANT TOPIC FOR CHEMISTRY STUDENTS , HENCE THE THEORY OF MOLECULAR MODELLING IS COVER IN THIS PRESNTATION . HOPE THIS MATTER SAISFY ALL AS WE HAVE TRIED TO ATTEMPT ALL TH TOPICS OF IT.
This document provides a summary of computational organic chemistry methods for investigating molecular structures, properties, reactivities, and selectivities. It describes the basic concepts of molecular mechanics and quantum chemistry methods, including their advantages and limitations. Applications include determining molecular geometries and conformations, absolute configurations, electron distributions, acidities, and frontier molecular orbital energies to examine reactivity and selectivity. Combining computational methods with experiments allows more reliable investigations.
This document discusses the foundations of chemical kinetic modeling and reaction models. It outlines the key pillars of knowledge required, including general chemistry, thermodynamics, chemical kinetics, and quantum chemistry. It then describes the step-wise process for constructing detailed chemical kinetic models, including determining elementary reactions, estimating thermo-chemical data and rate coefficients, validating models experimentally, and applying the models to reactor scale-up and design. Reactor scale-up requires satisfying similarity parameters between small and large-scale systems. The goal is to develop accurate predictive models and design safe, commercial-scale chemical reactors.
The document describes AFMM, a program for parametrizing molecular mechanics force fields. AFMM iteratively optimizes force field parameters to fit normal modes from quantum chemical calculations. It minimizes a merit function considering both vibrational frequencies and eigenvector projections. The program uses a Monte Carlo algorithm to refine parameters and improve the fit to reference quantum data, replacing manual parametrization.
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.
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.
Quantum calculations and calculational chemistrynazanin25
油
This document discusses computational chemistry and different methods for calculating molecular structure and properties using computers. It describes two main approaches: molecular mechanics, which views molecules as collections of atoms and calculates potential energy based on bonding parameters; and quantum mechanics, which uses the Schrodinger equation and approximations like Born-Oppenheimer and molecular orbital theory. Specific quantum methods discussed include semi-empirical, ab initio, and density functional theory. Popular computational programs and visualization software are also listed.
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The Business Administration Presentation provides a comprehensive exploration of the core concepts, functions, and importance of business administration in modern organizations. It highlights the key principles of managing business operations, strategic decision-making, and organizational leadership, offering a clear understanding of how businesses operate and thrive in competitive markets.
If I Miss This Putt I'll Kill Myself ShirtTeeFusion
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Golf is a game of precision, patience, andlet's be honestfrustration. If you've ever stood over a crucial putt with your heart pounding, you know the stakes feel higher than they should. Thats why the "If I Miss This Putt I'll Kill Myself" Shirt is the perfect way to add some humor to the game. This hilarious golf t-shirt is designed for golfers who take their putting game seriouslybut not too seriously. Whether you're playing for fun, competing in a tournament, or just hanging out at the clubhouse, this shirt will have everyone laughing.
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Nature Inspired Innovation : Designing The Future Using Lessons From The Pastjejchudley
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In an era dominated by technological revolution, design thinking's impact on economic and cultural success is undeniable.
However, its focus on 'designing for the user' often neglects the broader real-world implications of the complex systems within which the things we design are used.
In this talk, we will advocate for embracing evolutionary and ecological theories as a toolkit for understanding and designing for our dynamic and interconnected world.
By exploring questions about innovation speed, efficiency, and societal impacts through this lens, attendees will gain insights into enhancing UX design, fostering creative problem-solving, and developing impactful, innovative solutions.
From this presentation you will learn:
- How a better understanding of natural biological systems will help to improve their design practice
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L湛dica didactica (Report finale residenza Diego Alatorre Go_Innovation a Casa...Casa Netural
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Go_Innovation is a special residency for social innovator held by Netural Coop in Gorizia, European Capital of Culture 2025.
L炭dica did叩ctica / Play to Connect is a provocation to think outside the box, a methodology to board uncomfortable topics in a respectful and joyful manner and an excuse to discuss unconventional solutions to contemporary challenges, where play is seen as an attitude and game design as a metaphor of creativity by which to imagine, experiment and learn about our surroundings.
Casa Netural residency in Gorizia offered Diego an opportunity to test the ideas that he has been developing over the past years and to enrich them by looking at them from a different and complementary perspective. In other words to put theory into practice.
Along the 4 weeks that he lived in Gorizia he realized how mature and innovative his own understanding of the ludic phenomenon, as most people he connected with, found the value of his research, but what was amazing for him is how much his project was fed back from completely different and complementary perspectives.
Along these days he crafter four game ideas, with different levels of complexity and currently in different stages of development. These are described in the final report.
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Industrial Designer by CIDI UNAM and Master in Science of Design for Interaction by TU Delft, Diego ALatorre is currently doing a PhD in Contemporary Studies at the Center for Interdisciplinary Studies of Coimbra University.
His research explores the role of games in education: from a multimodal literacy perspective, he explores the creative process of writers, scientists, designers, artists, teachers and reflective players to learn how to critically read the world and creatively write.
Go_Innovation is a project designed and coordinated by Netural Coop Impresa Sociale within the framework of A THOUSAND YEARS OF HISTORY AT THE CENTER OF EUROPE: CASTLE BORGO CROCEVIA OF PEOPLES AND CULTURES, funded by PNRR - Next Generation EU, for the PNRR pilot project M1C3 Measure 2 Investment 2.1 line A - CUP F88F220000007
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Introduction to Storytelling Websites
Why storytelling matters in web design and how it enhances user engagement.
2. What Makes a Website a Storytelling Masterpiece?
Key elements like visuals, animations, and narrative flow.
3. Why Storytelling in Web Design is Effective
The psychology behind engaging users with stories.
4. The Power of Visual Storytelling
How images, videos, and illustrations create an immersive experience.
5. The Role of Animation in Storytelling Websites
Using motion effects to enhance engagement and interaction.
6. Typography as a Storytelling Element
How font choices affect mood and readability.
7. Color Theory in Storytelling Web Design
The impact of color schemes on emotions and brand identity.
8. Interactive Storytelling: Engaging the Audience
Examples of how interaction improves storytelling.
9. Parallax Scrolling for Narrative Depth
How this technique creates a dynamic storytelling experience.
Transform your space into a sanctuary with SPL Interiors where comfort meet...SPL Interiors
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1. Dr. Mazhar Amjad Gilani
COMSATS University Islamabad, Lahore Campus
05-10-2020
Computational Tools and
Applications of
Computational methods
in Different fields of
Chemistry
2. Topics to be covered..
1. Some more definitions of computational
chemistry
2. Concept of Computational Models
3. Knowledge about Hardware & Software
Topics to be covered..
3. Definition of Computational
Chemistry
Computational Chemistry: Use mathematical approximations
and computer programs to obtain results relative to chemical
problems.
Computational Quantum Chemistry: Focuses specifically on
equations and approximations derived from the postulates of
quantum mechanics. Solve the Schr旦dinger equation for
molecular systems.
Ab Initio Quantum Chemistry: Uses methods that do not include
any empirical parameters or experimental data.
4. Computational Models/Tools
A model is a system of equations, or computations used
to determine the energetics of a molecule
Different models use different approximations (or levels
of theory) to produce results of varying levels of
accuracy.
There is a trade off between accuracy and computational
time.
There are two main types of models; those that use
Schr旦dinger's equation (or simplifications of it) and
those that do not.
5. Computational Models/Tools
Types of Models
(Listed in order from most to least accurate)
Ab initio
uses Schr旦dinger's equation, but
with approximations
Semi Empirical
uses experimental parameters and
extensive simplifications of
Schr旦dinger's equation
Molecular Mechanics
does not use Schr旦dinger's
equation Simulated zigzag carbon
nanotube
6. Molecular Mechanics
Simplest type of calculation
Used when systems are very large and approaches that are more
accurate become to costly (in time and memory)
Does not use any quantum mechanics instead uses parameters derived
from experimental or ab initio data
Uses information like bond stretching, bond bending, torsions,
electrostatic interactions, van der Waals forces and hydrogen bonding
to predict the energetics of a system
The energy associated with a certain type of bond is applied throughout
the molecule. This leads to a great simplification of the equation
8. To predict the energy associated with a given conformation
Molecular mechanics energies have no meaning as absolute quantities
Only differences in energy between two/more conformations have
meaning
A simple molecular mechanics energy equation is given by:
Energy = Stretching Energy + Bending Energy +Torsion Energy + Non-Bonded
Interaction Energy
These equations together with the data (parameters) required to describe the
behavior of different kinds of atoms and bonds, is called a force-field.
9. Stretching Energy
The stretching energy equation is based on Hooke's law. The "kb" parameter controls
the stiffness of the bond spring, while "ro" defines its equilibrium length. Unique "kb"
and "ro" parameters are assigned to each pair of bonded atoms based on their types
(e.g. C-C, C-H, O-C, etc.). This equation estimates the energy associated with
vibration about the equilibrium bond length. This is the equation of a parabola, as can
be seen in the following plot:
11. Bending Energy
The bending energy equation is also based on Hooke's law. The "ktheta" parameter
controls the stiffness of the angle spring, while "thetao" defines its equilibrium angle.
This equation estimates the energy associated with vibration about the equilibrium
bond angle:
12. Unique parameters for angle bending are assigned to each bonded triplet of atoms
based on their types (e.g. C-C-C, C-O-C, C-C-H, etc.). The effect of the "kb" and "ktheta"
parameters is to broaden or steepen the slope of the parabola. The larger the value of
"k", the more energy is required to deform an angle (or bond) from its equilibrium value.
13. Semi Empirical
Semi empirical methods use experimental data to parameterize
equations
Like the ab initio methods, a Hamiltonian and wave function are used
much of the equation is approximated or eliminated
Less accurate than ab initio methods but also much faster
The equations are parameterized to reproduce specific results, usually
the geometry and heat of formation, but these methods can be used to
find other data.
Mixing of theory and experiment that makes the method semi-empirical
14. Ab Initio
Ab initio translated from Latin means from first principles. This
refers to the fact that no experimental data is used and computations
are based on quantum mechanics.
Different Levels of Ab Initio Calculations
Hartree-Fock (HF)
The simplest ab initio calculation
The major disadvantage of HF calculations is that electron
correlation is not taken into consideration.
The M淡ller-Plesset Perturbation Theory (MP)
Density Functional Theory (DFT)
Configuration Interaction (CI)
Take into consideration
electron correlation
19. *Abbreviated Profile of Drugs (APOD) is a web-based decision and prediction program
for drug discovery.
Software's
*ADMEWORKS DDI Simulator -- ADMEWORKS DDI Simulator is a software
application for assessing the risk of potential drug-drug interactions, allowing the user to
perform both quantitative simulations of Competitive and Mechanism-based inhibitions
*AMBER -- Molecular Dynamics Program
20. *AMSOL -- Semiempirical quantum chemistry program (gas phase and solvation)
*APBS: Adaptive Poisson-Boltzmann Solver -- Software for evaluating the
electrostatic properties of nanoscale biomolecular systems
*ArgusLab 3.0 -- Molecular Modeling Software
*BioSolveIT -- Software solutions for structure and ligand-based molecular design
Chemissian: quantum chemistry program for visualizing electron/spin density
distribution and UV-VIS spectra, plotting molecular orbital energy level diagrams,
calculating atomic orbital populations, contributions of atoms and fragments to MOs.
*COSMOlogic -- Software for Life Sciences, Chemical Engineering.
*GAMESS ab initio program.
21. *LiqCryst -- LiqCryst is a MS-Windows-based application, covers all aspects of liquid
crystal research: material properties, display technology, theory, basic research and
applications
*MDL QSAR - Comprehensive QSAR modeling system
*MOLCAS -- quantum chemistry software package
*Polar -- electrochemical simulation and data
analysis
Q-chem -- ab initio and DFT molecular modeling package
*Schrodinger, Computational Chemistry Software
*Gromacs MD Software
*SCIGRESS -- SCIGRESS is a unique desktop molecular modeling software package that can
apply a wide range of computational models to all types of molecular systems, from small
organic molecules.
22. References
Chem Viz at
http://www.shodor.org/chemviz/basis/students/introduction.html
D. YOUNG, in Computational Chemistry, A Practical Guide for
Applying Techniques to Real World Problems (Wiley-Interscience,
New York, 2001).
J. SIMMONS, in An Introduction to Theoretical Chemistry
(Cambridge Press, Cambridge, 2003).
J. B. FORESMAN AND . FRISCH, in Exploring Chemistry with
Electronic Structure Methods, 2nd Edition (Gaussian, Inc.,
Pittsburgh, PA, 1996).