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Computational Biology and Chemistry / / edited by Payam Behzadi and Nicola Bernabò
| Computational Biology and Chemistry / / edited by Payam Behzadi and Nicola Bernabò |
| Pubbl/distr/stampa | London, England : , : IntechOpen, , 2020 |
| Descrizione fisica | 1 online resource (150 pages) |
| Disciplina | 542 |
| Soggetto topico |
Computational biology
Cheminformatics Bioinformatics Computational chemistry |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910688336403321 |
| London, England : , : IntechOpen, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computational chemistry : applications and new technologies / / edited by Ponnadurai Ramasami
| Computational chemistry : applications and new technologies / / edited by Ponnadurai Ramasami |
| Pubbl/distr/stampa | Berlin, Germany ; ; Boston, Massachusetts : , : Walter de Gruyter GmbH, , [2021] |
| Descrizione fisica | 1 online resource (XIV, 260 p.) |
| Disciplina | 541.0285 |
| Soggetto topico |
Chemistry - Data processing
Computational chemistry |
| ISBN |
1-5231-5443-8
3-11-068204-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Preface of the Book of Proceedings of the Virtual Conference on Computational Science (VCCS-2019) -- Contents -- Corresponding authors -- 1 Structural and spectroscopic properties of 3-halogenobenzaldehydes: DFT and TDDFT simulations -- 2 Atomistic insight into the significantly enhanced photovoltaic cells of monolayer GaTe2 via two-dimensional van der Waals heterostructures engineering -- 3 Fluorescent styryl chromophores with rigid (pyrazole) donor and rigid (benzothiophenedioxide) acceptor – complete density functional theory (DFT), TDDFT and nonlinear optical study -- 4 Comparative studies of excited state intramolecular proton transfer (ESIPT) and azohydrazone tautomerism in naphthalene-based fluorescent acid azo dyes by computational study -- 5 Theoretical examination of efficiency of anthocyanidins as sensitizers in dye-sensitized solar cells -- 6 Selection of oxypeucedanin as a potential antagonist from molecular docking analysis of HSP90 -- 7 Mechanistic insight into the interactions between thiazolidinedione derivatives and PTP-1B combining 3D QSAR andmolecular docking in the treatment of type 2 diabetes -- 8 Review of research of nanocomposites based on graphene quantum dots -- 9 A computational study of the SNAr reaction of 2-ethoxy-3,5-dinitropyridine and 2-methoxy-3, 5-dinitropyridine with piperidine -- 10 Synthesis, characterization and computational studies of 1,3-bis[(E)-furan-2-yl)methylene]urea and 1,3-bis[(E)-furan-2-yl)methylene]thiourea -- 11 Computational studies of biologically active alkaloids of plant origin: an overview -- 12 Investigating the biological actions of some Schiff bases using density functional theory study -- 13 Molecular mechanics approaches for rational drug design: forcefields and solvation models -- Index |
| Record Nr. | UNINA-9910554256303321 |
| Berlin, Germany ; ; Boston, Massachusetts : , : Walter de Gruyter GmbH, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computational Drug Discovery : Methods and Applications
| Computational Drug Discovery : Methods and Applications |
| Autore | Poongavanam Vasanthanathan |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2024 |
| Descrizione fisica | 1 online resource (739 pages) |
| Disciplina | 615.190015118 |
| Altri autori (Persone) | RamaswamyVijayan |
| Soggetto topico |
Computational chemistry
Molecular dynamics Quimioinformàtica Dinàmica molecular |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783527840748
3527840745 9783527840724 3527840729 9783527840731 3527840737 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright -- Contents -- Preface -- Acknowledgments -- About the Editors -- Part I Molecular Dynamics and Related Methods in Drug Discovery -- Chapter 1 Binding Free Energy Calculations in Drug Discovery -- 1.1 Introduction -- 1.1.1 Free Energy and Thermodynamic Cycles -- 1.2 Endpoint Methods -- 1.2.1 MM/PBSA and MM/GBSA -- 1.2.2 Linear Response Approximations -- 1.3 Alchemical Methods -- 1.3.1 Free Energy Perturbation -- 1.3.2 Thermodynamic Integration -- 1.3.3 Bennett's Acceptance Ratio -- 1.3.4 Nonequilibrium Methods -- 1.3.5 Multiple Compounds -- 1.3.6 One‐Step Perturbation Approaches -- 1.3.7 Challenges in Alchemical Free Energy Calculations -- 1.4 Pathway Methods -- 1.5 Final Thoughts -- References -- Chapter 2 Gaussian Accelerated Molecular Dynamics in Drug Discovery -- 2.1 Introduction -- 2.2 Methods -- 2.2.1 Gaussian Accelerated Molecular Dynamics -- 2.2.2 Ligand Gaussian Accelerated Molecular Dynamics -- 2.2.3 Energetic Reweighting of GaMD for Free Energy Calculations -- 2.2.4 GLOW: A Workflow Integrating Gaussian Accelerated Molecular Dynamics and Deep Learning for Free Energy Profiling -- 2.2.5 Binding Kinetics Obtained from Reweighting of GaMD Simulations -- 2.2.6 Gaussian Accelerated Molecular Dynamics Implementations and Software -- 2.3 Applications -- 2.3.1 G‐Protein‐Coupled Receptors -- 2.3.1.1 Characterizing the Binding and Unbinding of Caffeine in Human Adenosine A2A Receptor -- 2.3.1.2 Unraveling the Allosteric Modulation of Human A1 Adenosine Receptor -- 2.3.1.3 Ensemble Based Virtual Screening of Allosteric Modulators of Human A1 Adenosine Receptor -- 2.3.2 Nucleic Acids -- 2.3.2.1 Exploring the Binding of Risdiplam Splicing Drug Analog to Single‐Stranded RNA -- 2.3.2.2 Uncovering the Binding of RNA to a Musashi RNA‐Binding Protein -- 2.3.3 Human Angiotensin‐Converting Enzyme 2 Receptor.
2.3.4 Discovery of Novel Small‐Molecule Calcium Sensitizers for Cardiac Troponin C -- 2.3.5 Binding Kinetics Prediction from GaMD Simulations -- 2.4 Conclusions -- References -- Chapter 3 MD Simulations for Drug‐Target (Un)binding Kinetics -- 3.1 Introduction -- 3.1.1 Preface -- 3.1.2 Motivation for Predicting (Un)binding Kinetics -- 3.1.3 The Time Scale Problem of MD Simulations -- 3.2 Theory of Molecular Kinetics Calculation -- 3.2.1 Nonequilibrium Statistical Mechanics in a Nutshell -- 3.2.2 Kramers Rate Theory -- 3.2.3 Biased MD Methods -- 3.2.3.1 Temperature‐ and Barrier‐Scaling -- 3.2.3.2 Bias Potential‐Based Methods -- 3.2.3.3 Bias Force‐Based Methods -- 3.2.3.4 Knowledge‐Biased Methods -- 3.2.3.5 Coarse‐graining and Master Equation Approaches -- 3.3 Challenges and Caveats in Rate Prediction -- 3.3.1 Finding Reaction Coordinates and Pathways -- 3.3.2 Error Ranges of Estimates -- 3.3.3 A Need for Reliable Benchmarking Systems -- 3.3.4 Problems with Force Fields -- 3.4 Methods for Rate Prediction -- 3.4.1 Unbinding Rate Prediction -- 3.4.1.1 Empirical Predictions -- 3.4.1.2 Prediction of Absolute Unbinding Rates -- 3.4.2 Binding Rate Prediction -- 3.5 State‐of‐the‐Art in Understanding Kinetics -- 3.6 Conclusion -- References -- Chapter 4 Solvation Thermodynamics and its Applications in Drug Discovery -- 4.1 Introduction -- 4.1.1 Protein Folding -- 4.1.2 Protein-Ligand Interactions -- 4.2 Tools to Assess the Solvation Thermodynamics -- 4.2.1 Watermap -- 4.2.2 GIST -- 4.2.3 3D‐RISM -- 4.3 Case Studies -- 4.3.1 Watermap -- 4.3.1.1 Background and Approach -- 4.3.1.2 Results and Discussion -- 4.3.2 Grid Inhomogeneous Solvation Theory (GIST) -- 4.3.2.1 Objective and Approach -- 4.3.2.2 Results and Discussion -- 4.3.3 Three‐Dimensional Reference Interaction‐Site Model (3D‐RISM) -- 4.3.3.1 Objective and Background -- 4.3.3.2 Results and Discussion. 4.4 Conclusion -- References -- Chapter 5 Site‐Identification by Ligand Competitive Saturation as a Paradigm of Co‐solvent MD Methods -- 5.1 Introduction -- 5.2 SILCS: Site Identification by Ligand Competitive Saturation -- 5.3 SILCS Case Studies: Bovine Serum Albumin and Pembrolizumab -- 5.3.1 SILCS Simulations -- 5.3.2 FragMap Construction -- 5.3.3 SILCS‐MC -- 5.3.4 SILCS‐Hotspots -- 5.3.5 SILCS‐PPI -- 5.3.6 SILCS‐Biologics -- 5.4 Conclusion -- Conflict of Interest -- Acknowledgments -- References -- Part II Quantum Mechanics Application for Drug Discovery -- Chapter 6 QM/MM for Structure‐Based Drug Design: Techniques and Applications -- 6.1 Introduction -- 6.2 QM/MM Approaches -- 6.2.1 Combined Quantum Mechanical/Molecular Mechanical Energy Calculations -- 6.2.2 QM/MM Methods for the Evaluation of Non‐Covalent Inhibitor Binding -- 6.2.3 QM/MM Reaction Modeling -- 6.3 Applications of QM/MM for Covalent Drug Design and Evaluation -- 6.3.1 Covalent Tyrosine Kinase Inhibitors for Cancer Treatment -- 6.3.2 Evaluation of Antibiotic Resistance Conferred by β‐Lactamases -- 6.3.3 Covalent SARS‐CoV‐2 Inhibitors: Mechanism and Insights for Design -- 6.4 Conclusions and Outlook -- References -- Chapter 7 Recent Advances in Practical Quantum Mechanics and Mixed‐QM/MM‐Driven X‐Ray Crystallography and Cryogenic Electron Microscopy (Cryo‐EM) and Their Impact on Structure‐Based Drug Discovery -- 7.1 Introduction -- 7.2 Feasibility of Routine and Fast QM‐Driven X‐Ray Refinement -- 7.3 Metrics to Measure Improvement -- 7.3.1 Ligand Strain Energy -- 7.3.2 ZDD of Difference Density -- 7.3.3 Overall Crystallographic Structure Quality Metrics: MolProbity Score and Clashscore -- 7.4 QM Region Refinement -- 7.5 ONIOM Refinement -- 7.6 XModeScore: Distinguish Protomers, Tautomers, Flip States, and Docked Ligand Poses. 7.7 Impact of the QM‐Driven Refinement on Protein-Ligand Affinity Prediction -- 7.7.1 Impact of Structure Inspection and Modification -- 7.7.2 Impact of Selecting Protomer States: Implications of XModeScore on SBDD -- 7.8 Conclusion -- Acknowledgments -- References -- Chapter 8 Quantum‐Chemical Analyses of Interactions for Biochemical Applications -- 8.1 Introduction -- 8.2 Introduction to FMO -- 8.3 Pair Energy Decomposition Analysis (PIEDA) -- 8.3.1 Formulation of PIEDA -- 8.3.2 Applications of PIEs and PIEDA -- 8.3.3 Example of PIEDA -- 8.4 Partition Analysis (PA) -- 8.4.1 Formulation of PA -- 8.4.2 Applications and an Example of PA -- 8.5 Partition Analysis of Vibrational Energy (PAVE) -- 8.5.1 Formulation of PAVE -- 8.5.2 Applications of PAVE -- 8.6 Subsystem Analysis (SA) -- 8.6.1 Formulation of SA -- 8.6.2 Examples of SA and PAVE -- 8.7 Fluctuation Analysis (FA) -- 8.8 Free Energy Decomposition Analysis (FEDA) -- 8.9 Other Analyses of Chemical Reactions -- 8.10 Conclusions -- References -- Part III Artificial Intelligence in Pre‐clinical Drug Discovery -- Chapter 9 The Role of Computer‐Aided Drug Design in Drug Discovery -- 9.1 Introduction to Drug-Target Interactions, Hit Identification -- 9.2 Lead Identification and Optimization: QSAR and Docking‐Based Approaches -- 9.3 DTI Machine Learning Methods -- 9.4 Supervised, Non‐supervised and Semi‐supervised Learning Methods -- 9.5 Graph‐Based Methods to Label Data for DTI Prediction -- 9.6 The Importance of Explainable ML Methods: Linking Molecular Properties to Effects -- 9.7 Predicting Therapeutic Responses -- 9.8 ADMET‐tox Prediction -- 9.9 Challenging Aspects of Using Computational Methods in Drug Discovery -- 9.9.1 What are Those Limitations? -- References -- Chapter 10 AI‐Based Protein Structure Predictions and Their Implications in Drug Discovery -- 10.1 Introduction. 10.2 Impact of AI‐Based Protein Models in Structural Biology -- 10.2.1 Combination of AI‐Based Predictions with Cryo‐EM and X‐Ray Crystallography -- 10.2.2 Combination of AI‐Based Predictions with NMR Structures -- 10.2.3 Combination of AI‐Based Predictions with Other Experimental Restraints -- 10.2.4 Impact of Deep Learning Models in Other Areas of Structural Biology -- 10.3 Combination of AI‐Based Methods with Computational Approaches -- 10.3.1 Combination of Structure Prediction with Other Computational Approaches -- 10.4 Current Challenges and Opportunities -- 10.5 Conclusions -- References -- Chapter 11 Deep Learning for the Structure‐Based Binding Free Energy Prediction of Small Molecule Ligands -- 11.1 Introduction -- 11.2 Deep Learning Models for Reasoning About Protein-Ligand Complexes -- 11.2.1 Datasets -- 11.2.2 Convolutional Neural Networks -- 11.2.2.1 Background -- 11.2.2.2 Voxelized Grid Representation -- 11.2.2.3 Descriptors -- 11.2.2.4 Applications -- 11.2.3 Graph Neural Networks -- 11.2.3.1 Background -- 11.2.3.2 Graph Representation -- 11.2.3.3 Descriptors -- 11.2.3.4 Applications -- 11.2.3.5 Extension to Attention Based Models -- 11.2.3.6 Geometric Deep Learning and Other Approaches -- 11.3 Deep Learning Approaches Around Molecular Dynamics Simulations -- 11.3.1 Enhanced Sampling -- 11.3.2 Physics‐inspired Neural Networks -- 11.3.3 Modeling Dynamics -- 11.3.3.1 Applications -- 11.4 Modifying AlphaFold2 for Binding Affinity Prediction -- 11.4.1 Modifying AlphaFold2 Input Protein Database for Accurate Free Energy Predictions -- 11.4.2 Modifying Multiple Sequence Alignment for AlphaFold2‐Based Docking -- 11.5 Conclusion -- 11.5.1 New Models for Binding Affinity Prediction -- 11.5.2 Retrospective from the Compute Industry -- 11.5.2.1 Future DL‐Based Binding Affinity Computation will Require Massive Scalability. 11.5.2.2 Single GPU Optimizations for DL. |
| Record Nr. | UNINA-9910877239103321 |
Poongavanam Vasanthanathan
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| Newark : , : John Wiley & Sons, Incorporated, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Computed structures of polyimides model compounds / / H. Tai and D. H. Phillips
| Computed structures of polyimides model compounds / / H. Tai and D. H. Phillips |
| Autore | Tai H (Hsiang) |
| Pubbl/distr/stampa | Hampton, Virginia. : , : National Aeronautics and Space Administration, Langley Research Center, , June 1990 |
| Descrizione fisica | 1 online resource (97 pages) : illustrations |
| Collana | NASA technical memorandum |
| Soggetto topico |
Computational chemistry
Molecular structure Polyimides Synthesis (chemistry) |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910706229103321 |
|
Tai H (Hsiang)
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| Hampton, Virginia. : , : National Aeronautics and Space Administration, Langley Research Center, , June 1990 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Exploring Chemical Concepts Through Theory and Computation
| Exploring Chemical Concepts Through Theory and Computation |
| Autore | Liu Shubin |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2024 |
| Descrizione fisica | 1 online resource (594 pages) |
| Disciplina | 542.8 |
| Soggetto topico |
Computational chemistry
Quantum chemistry |
| ISBN |
9783527843411
3527843418 9783527843435 3527843434 9783527843428 3527843426 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright -- Contents -- Preface -- Foreword -- 10 Questions About Exploring Chemical Concepts Through Theory and Computation -- Chapter 1 Chemical Concepts from Molecular Orbital Theory -- 1.1 Introduction -- 1.2 Molecular Orbital Theory -- 1.3 Canonical Molecular Orbitals -- 1.4 Frontier Molecular Orbital Theory -- 1.5 Localized Molecular Orbitals -- 1.5.1 Orthogonal Localized Molecular Orbitals -- 1.6 Regularized Nonorthogonal Localized Molecular Orbitals -- 1.7 Molecular Orbitalets -- Acknowledgment -- References -- Chapter 2 Chemical Concepts from Ab Initio Valence Bond Theory -- 2.1 Introduction -- 2.2 Ab Initio Valence Bond Theory -- 2.2.1 Valence Bond Self‐Consistent Field Method -- 2.2.2 Rumer Structures -- 2.2.3 Orbitals in VB Wave Function -- 2.2.4 VB Methods Involving Dynamic Correlation -- 2.3 Chemical Concepts in VB Theory -- 2.3.1 Resonance Theory -- 2.3.2 Conjugation, Hyperconjugation, and Aromaticity -- 2.3.3 Electron‐Pair Bonding in Valence Bond Theory -- 2.3.4 Diabatic States in Valence Bond Theory -- 2.4 A Brief Guide to Perform VB Calculations -- 2.4.1 Preparing XMVB Input Files -- 2.4.2 Reading XMVB Output Files -- 2.5 Concluding Remarks -- References -- Chapter 3 Chemical Concepts from Conceptual Density Functional Theory -- 3.1 Introduction -- 3.2 The Fundamentals: Density Functional Theory (DFT) and Kohn-Sham DFT -- 3.3 The First Derivatives: The Electronic Chemical Potential and the Electron Density -- 3.4 The Second Derivatives: Chemical Hardness, Fukui Function, Linear Response Function, and Related Quantities -- 3.4.1 Chemical Hardness and Softness -- 3.4.2 The Fukui Function and the Dual Descriptor -- 3.4.3 Local Softness and Hardness -- 3.4.4 The Linear Response Function, Softness and Hardness Kernels -- 3.5 Perturbational Perspective of Chemical Reactivity -- 3.6 Conclusions -- Acknowledgment.
References -- Chapter 4 Chemical Concepts from Density‐Based Approaches in Density Functional Theory -- 4.1 Introduction -- 4.2 Four Density‐Based Frameworks -- 4.2.1 Orbital‐Free DFT (OF‐DFT) -- 4.2.2 Conceptual DFT (CDFT) -- 4.2.3 Density‐Associated Quantities (DAQs) -- 4.2.4 Information‐Theoretic Approach (ITA) -- 4.3 Applications of Density‐Based Approaches -- 4.3.1 Molecular Isomeric and Conformational Stability -- 4.3.2 Bonding and Noncovalent Interactions -- 4.3.3 Cooperation and Frustration -- 4.3.4 Homochirality and Principle of Chirality Hierarchy -- 4.3.5 Electrophilicity and Nucleophilicity -- 4.3.6 Regioselectivity and Stereoselectivity -- 4.3.7 Brønsted-Lowry Acidity and Basicity -- 4.3.8 Aromaticity and Antiaromaticity -- 4.3.9 Molecular Properties (Frontier Orbitals, HOMO/LUMO Gap, Oxidation States, Polarizability) -- 4.4 Concluding Remarks -- Acknowledgments -- References -- Chapter 5 Chemical Bonding -- 5.1 Introduction -- 5.2 The Physical Mechanism of the Chemical Bond -- 5.3 Bonding Models -- 5.4 Bond Length and Bond Strength -- 5.5 Dative and Electron‐Sharing Bonds -- 5.6 Polar Bonds -- 5.7 Atomic Partial Charges and Atomic Electronegativity -- 5.8 Chemical Bonding in Main‐Group Compounds: N2, CO, BF, LiF -- 5.9 Chemical Bonding of the Heavier Main‐Group Atoms -- 5.10 Chemical Bonding in Transition Metal Complexes: M(CO)n (M & -- equals -- Ni, Fe, Cr, Ti, Ca -- n & -- equals -- 4 - 8) -- 5.11 Summary -- Acknowledgments -- References -- Chapter 6 Partial Charges -- 6.1 Concept of Partial Charge -- 6.1.1 What is Partial Charge? -- 6.1.2 Theoretical Significances and Practical Applications of Partial Charge -- 6.1.3 Limitations of Partial Charge -- 6.1.4 What Is a Good Method of Calculating Partial Charges? -- 6.1.5 Classification of Partial Charge Calculation Methods -- 6.2 Methods of Calculating Partial Charges. 6.2.1 Partial Charges Based on Wavefunction -- 6.2.1.1 Mulliken Method -- 6.2.1.2 MMPA Methods -- 6.2.1.3 Löwdin Method -- 6.2.1.4 NPA Method -- 6.2.2 Partial Charges Based on Real Space Partition of Electron Density -- 6.2.2.1 AIM Method -- 6.2.2.2 Voronoi and VDD Methods -- 6.2.2.3 Hirshfeld Method -- 6.2.2.4 Hirshfeld‐I Method -- 6.2.3 Partial Charges Based on Fitting Electrostatic Potential -- 6.2.3.1 Common ESP Fitting Methods -- 6.2.3.2 RESP and Relevant Methods -- 6.2.4 Partial Charges Based on Equalization of Electronegativity -- 6.2.5 Partial Charges Based on Other Ideas -- 6.3 Partial Charges of Typical Molecules -- 6.4 Computer Codes for Evaluating Partial Charges -- 6.5 Concluding Remarks -- References -- Chapter 7 Atoms in Molecules -- 7.1 Introduction -- 7.2 The Quantum Theory of Atoms in Molecules (QTAIM) -- 7.3 QTAIM Atoms as Open Quantum Systems -- 7.3.1 Sector Density Operators of Quantum Atoms in Molecules -- 7.3.2 RDMs of Atoms in Molecules -- 7.4 Interacting Quantum Atoms (IQA) -- References -- Chapter 8 Effective Oxidation States Analysis -- 8.1 The Concept of Oxidation State -- 8.2 Oxidation State is Not Related to the Partial Charge -- 8.3 The Molecular Orbital Picture of the Ionic Approximation -- 8.4 Spin‐Resolved Effective Fragment Orbitals and Effective Oxidation States (EOS) Analysis -- 8.5 EOS Analysis from Different AIM Schemes -- 8.6 Summary -- References -- Chapter 9 Aromaticity and Antiaromaticity -- 9.1 Definition of Aromaticity -- 9.2 Physical Foundation -- 9.3 Measures of Aromaticity -- 9.3.1 Geometric Descriptors of Aromaticity -- 9.3.2 Energetic Descriptors of Aromaticity -- 9.3.3 Electronic Descriptors of Aromaticity -- 9.3.4 Magnetic Descriptors of Aromaticity -- 9.4 Rules of Aromaticity -- 9.4.1 Rules for Two‐Dimensional Aromaticity -- 9.4.2 Rules for Three‐Dimensional Aromaticity. 9.5 Metallabenzenes and Related Compounds as an Example -- References -- Chapter 10 Acidity and Basicity -- 10.1 Introduction -- 10.2 Definitions and Theories -- 10.2.1 Arrhenius Theory -- 10.2.2 Brønsted-Lowry Theory -- 10.2.3 Lewis Theory -- 10.2.4 Usanovich Definition -- 10.2.5 Lux-Flood Definition -- 10.2.6 Solvent System Definition -- 10.3 CDFT‐Based Reactivity Descriptors -- 10.4 CDFT‐Based Electronic Structure Principles -- 10.4.1 Equalization Principles -- 10.4.2 Hard-Soft Acid-Base (HSAB) Principle -- 10.4.3 Maximum Hardness (MHP), Minimum Polarizability (MPP), and Minimum Electrophilicity (MEP) Principles -- 10.5 Systemics of Lewis Acid-Base Reactions: Drago-Wayland Equation -- 10.6 Strengths of Acid and Bases -- 10.6.1 Ionic Product -- 10.6.2 pH Scale -- 10.6.3 Ionization Constants -- 10.6.4 Proton Affinity -- 10.6.5 Electronegativity -- 10.6.6 Hardness -- 10.6.7 Electrophilicity -- 10.7 Effect of External Perturbation -- 10.7.1 Steric Effects -- 10.7.2 Solvent Effects -- 10.7.3 Periodicity -- 10.7.4 Inductive Effect -- 10.7.5 Resonance Effect -- 10.8 CDFT and Acidity -- 10.9 CDFT and ITA -- 10.10 Are Strong Brønsted Acids Necessarily Strong Lewis Acids? -- 10.11 Summary -- Acknowledgment -- Conflict of Interest -- References -- Chapter 11 Sigma Hole Supported Interactions: Qualitative Features, Various Incarnations, and Disputations -- 11.1 Introduction -- 11.1.1 What's in a Name - The Sigma Hole Terminology and Concept -- 11.1.2 Donor-Acceptor Interaction Continuum -- 11.2 Many Incarnations and Roles of a Single Phenomenon -- 11.2.1 Hydrogen Bonding -- 11.2.2 Halogen Bonding and Sigma Holes on Group 17 Atoms -- 11.2.2.1 Common Origins -- 11.2.2.2 Cases of Halogen Bonding -- 11.2.2.3 The Sigma Hole and the Whole Story -- 11.2.3 Chalcogens -- 11.2.4 Pnictogens -- 11.2.5 Tetrels -- 11.2.6 Triels. 11.3 Related Interactions Elsewhere in the Main Group -- 11.3.1 Group 2 -- 11.3.2 Group 1 -- 11.3.3 Group 18 -- 11.4 Contested Interpretations -- 11.5 Conclusions -- Acknowledgment -- References -- Chapter 12 On the Generalization of Marcus Theory for Two‐State Photophysical Processes -- 12.1 Introduction -- 12.2 The Golden Rule Rate Expression -- 12.2.1 The Marcus Theory: The Classical Treatment -- 12.2.2 The Marcus-Levich-Jortner Expression: A Quantum Expression for High‐Frequency Modes -- 12.2.3 The Föster Theory: Separating Donor and Acceptor Parts in FCWD -- 12.3 Application -- 12.3.1 Electron Transfer -- 12.3.2 SET: Using Spectra for FCWD -- 12.3.3 TET and Other Energy Transfer Process with Spin Exchange -- 12.4 Conclusion -- Acknowledgments -- References -- Chapter 13 Computational Modeling of CO2 Reduction and Conversion via Heterogeneous and Homogeneous Catalysis -- 13.1 Introduction -- 13.2 Computational Methods -- 13.3 Activation and Reduction of CO2 -- 13.3.1 Computational Catalyst Design -- 13.3.1.1 Doping of Metal and Nonmetal Atoms -- 13.3.1.2 Structural Modification -- 13.3.1.3 Application of an External Electric Field -- 13.3.2 Electrocatalytic Reduction of CO2 -- 13.3.3 Hydrogenation Reduction of CO2 -- 13.4 Catalytic Coupling of CO2 with CH4 -- 13.5 Homogeneous Catalytic Conversion of CO2 -- 13.5.1 Catalytic CO2 Fixation into Cyclic Carbonates -- 13.5.2 CO2 Hydrogenation Catalyzed by Metal PNP‐Pincer Complexes -- 13.6 Conclusion and Outlook -- Acknowledgments -- References -- Chapter 14 Excited States in Conceptual DFT -- 14.1 Introduction -- 14.2 Exploring Ground State Properties Thanks to Excited States -- 14.2.1 Context and Justification -- 14.2.2 Chemical Hardness Revisited -- 14.2.3 State‐Specific Dual Descriptors -- 14.2.4 Polarization Interaction -- 14.3 Exploring the Reactivity of Excited States with Excited States. 14.3.1 Local Chemical Potential. |
| Record Nr. | UNINA-9911019420803321 |
|
Liu Shubin
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| Newark : , : John Wiley & Sons, Incorporated, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Frontiers in computational chemistry . Volume 5 / / edited by Zaheer Ul-Haq & Angela K. Wilson
| Frontiers in computational chemistry . Volume 5 / / edited by Zaheer Ul-Haq & Angela K. Wilson |
| Pubbl/distr/stampa | Singapore : , : Bentham Books, , [2020] |
| Descrizione fisica | 1 online resource (273 pages) |
| Disciplina | 540 |
| Soggetto topico |
Chemistry
Computational chemistry |
| ISBN | 981-14-5779-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910794318503321 |
| Singapore : , : Bentham Books, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Frontiers in computational chemistry . Volume 5 / / edited by Zaheer Ul-Haq & Angela K. Wilson
| Frontiers in computational chemistry . Volume 5 / / edited by Zaheer Ul-Haq & Angela K. Wilson |
| Pubbl/distr/stampa | Singapore : , : Bentham Books, , [2020] |
| Descrizione fisica | 1 online resource (273 pages) |
| Disciplina | 540 |
| Soggetto topico |
Chemistry
Computational chemistry |
| ISBN | 981-14-5779-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910820685703321 |
| Singapore : , : Bentham Books, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Journal of computational chemistry
| Journal of computational chemistry |
| Pubbl/distr/stampa | New York, NY, : John Wiley & Sons |
| Descrizione fisica | 1 online resource |
| Disciplina | 542 |
| Soggetto topico |
Chemistry - Data processing
Chemical models Chemistry - methods Computer Simulation Models, Chemical Chimio-informatique Simulation par ordinateur Modèles chimiques simulation Chemistry Biology Chemie Datenverarbeitung Zeitschrift Online-Ressource Computational chemistry |
| Soggetto genere / forma |
Fulltext
Internet Resources. Periodicals. |
| ISSN | 1096-987X |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910146513103321 |
| New York, NY, : John Wiley & Sons | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Molecular Simulations : Fundamentals and Practice
| Molecular Simulations : Fundamentals and Practice |
| Autore | Alavi Saman |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2020 |
| Descrizione fisica | 1 online resource (345 pages) |
| Disciplina | 541.22 |
| Soggetto topico |
Molecular dynamics
Computational chemistry |
| ISBN |
3-527-69946-5
3-527-69953-8 3-527-69945-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Cover -- Title Page -- Copyright -- Contents -- Preface -- Chapter 1 Introduction – Studying Systems from Two Viewpoints -- Chapter 2 Classical Mechanics and Numerical Methods -- 2.1 Mechanics – The Study of Motion -- 2.2 Classical Newtonian Mechanics -- 2.3 Analytical Solutions of Newton's Equations and Phase Space -- 2.3.1 Motion of an Object Under Constant Gravitational Force -- 2.3.2 One‐Dimensional Harmonic Oscillator -- 2.3.3 Radial Force Functions in Three Dimensions -- 2.3.4 Motion Under the Influence of a Drag Force -- 2.4 Numerical Solution of Newton's Equations: The Euler Method -- 2.5 More Efficient Numerical Algorithms for Solving Newton's Equations -- 2.5.1 The Verlet Algorithm -- 2.5.2 The Leapfrog Algorithm -- 2.5.3 The Velocity Verlet Algorithm -- 2.5.4 Considerations for Numerical Solution of the Equations of Motion -- 2.6 Examples of Using Numerical Methods for Solving Newton's Equations of Motion -- 2.6.1 Motion Near the Earth's Surface Under Constant Gravitational Force -- 2.6.2 One‐Dimensional Harmonic Oscillator -- 2.7 Numerical Solution of the Equations of Motion for Many‐Atom Systems -- 2.8 The Lagrangian and Hamiltonian Formulations of Classical Mechanics -- Chapter 2 Appendices -- 2.A.1 Separation of Motion in Two‐Particle Systems with Radial Forces -- 2.A.2 Motion Under Spherically Symmetric Forces -- Chapter 3 Intra- and Intermolecular Potentials in Simulations -- 3.1 Introduction – Electrostatic Forces Between Atoms |
| Altri titoli varianti | Molecular Simulations |
| Record Nr. | UNINA-9911019853303321 |
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Alavi Saman
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| Newark : , : John Wiley & Sons, Incorporated, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Special Protein Molecules Computational Identification / / edited by Quan Zou
| Special Protein Molecules Computational Identification / / edited by Quan Zou |
| Pubbl/distr/stampa | Basel, Switzerland : , : MDPI - Multidisciplinary Digital Publishing Institute, , 2018 |
| Descrizione fisica | 1 online resource (308 pages) |
| Disciplina | 547.75 |
| Soggetto topico |
Computational chemistry
Proteins |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910597905503321 |
| Basel, Switzerland : , : MDPI - Multidisciplinary Digital Publishing Institute, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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