“Multi-scale Quantum Models for Biocatalysis” explores various molecular modelling techniques and their applications in providing an understanding of the detailed mechanisms at play during biocatalysis in enzyme and ribozyme systems. These areas are reviewed by an international team of experts in theoretical, computational chemistry, and biophysics. This book presents detailed reviews concerning the development of various techniques, including ab initio molecular dynamics, density functional theory, combined QM/MM methods, solvation models, force field methods, and free-energy estimation techniques, as well as successful applications of multi-scale methods in the biocatalysis systems including several protein enzymes and ribozymes. This book is an excellent source of information for research professionals involved in computational chemistry and physics, material science, nanotechnology, rational drug design and molecular biology and for students exposed to these research areas.

First-Principles-Based Multiscale, Multiparadigm Molecular Mechanics and Dynamics Methods for Describing Complex Chemical Processes, by A. Jaramillo-Botero, R. Nielsen, R. Abrol, J. Su, T. Pascal, J. Mueller and W. A. Goddard.- Dynamic QM/MM: A Hybrid Approach to Simulating Gas–Liquid Interactions, by S. Yockel and G. C. Schatz.- Multiscale Modelling in Computational Heterogeneous Catalysis, by F. J. Keil.- Real-World Predictions from Ab Initio Molecular Dynamics Simulations, by B. Kirchner, P. J. di Dio and J. Hutter.- Nanoscale Wetting Under Electric Field from Molecular Simulations, by C. D. Daub, D. Bratko and A. Luzar.- Molecular Simulations of Retention in Chromatographic Systems: Use of Biased Monte Carlo Techniques to Access Multiple Time and Length Scales, by J. L. Rafferty, J. I. Siepmann, M. R. Schure.- Thermodynamic Properties for Applications in Chemical Industry via Classical Force Fields, by G. Guevara-Carrion, H. Hasse and J. Vrabec.- Multiscale Approaches and Perspectives to Modeling Aqueous Electrolytes and Polyelectrolytes, by L. Delle Site, C. Holm and N. F. A. van der Vegt.- Coarse-Grained Modeling for Macromolecular Chemistry, by H. A. Karimi-Varzaneh and F. Müller-Plathe.-

This special volume of Progress in Molecular Biology and Translational Science focuses on catalytic RNA. Written by experts in the field, the reviews cover a range of topics, from hammerhead ribozymes to spliceosome catalysis to Varkud satellite and hairpin ribozymes. - Contributions from leading authorities - Informs and updates on all the latest developments in the field

The proposed volume provides both fundamental and detailed information about the computational and computational-experimental studies which improve our knowledge of how leaving matter functions, the different properties of drugs (including the calculation and the design of new ones), and the creation of completely new ways of treating numerical diseases. Whenever it is possible, the interplay between theory and experiment is provided. The book features computational techniques such as quantum-chemical and molecular dynamic approaches and quantitative structure–activity relationships. The initial chapters describe the state-of-the art research on the computational investigations in molecular biology, molecular pharmacy, and molecular medicine performed with the use of pure quantum-chemical techniques. The central part of the book illustrates the status of computational techniques that utilize hybrid, so called QM/MM approximations as well as the results of the QSAR studies which now are the most popular in predicting drugs’ efficiency. The last chapters describe combined computational and experimental investigations.

The first book of its kind to show the potential of quantum computing in drug delivery. Drug delivery systems (DDS) are defined as methods by which drugs are delivered to desired tissues, organs, cells, and subcellular organs for drug release and absorption through a variety of drug carriers. By controlling the precise level and/or location of a given drug in the body, side effects are reduced, doses are lowered, and new therapies are possible. Nevertheless, there are still significant obstacles to delivering certain medications to particular cells. Drug delivery methods change pharmacokinetic, pharmacodynamic, and drug release patterns to enhance product efficacy and safety, as well as patient convenience and compliance. Computational approaches in drug development enable quick screening of a vast chemical library and identification of possible binders by using modeling, simulation, and visualization tools. Quantum computing (QC) is a fundamentally new computing paradigm based on quantum mechanics rules that enables certain computations to be conducted significantly more rapidly and effectively than regular computing, and hence this has huge promise for the pharmaceutical sector. Significant advances in computational simulation are making it easier to comprehend the process of drug delivery. This book explores an important biophysical component of DDSs, and how computer modeling may help with the logical design of DDSs with enhanced and optimized characteristics. The book concentrates on computational research for various important types of nanocarriers, including dendrimers and dendrons, polymers, peptides, nucleic acids, lipids, carbon-based DDSs, and gold nanoparticles. Audience Researchers and industry scientists working in clinical research and disease management; pharmacists, formulation and pharmaceutical scientists working in R&D; computer science engineers applying deep learning and quantum computing in healthcare.

Both strategies for investigation (computational and experimental) in structural and mechanistic Enzymology have developed to some extent independently. However, over the last few years a trend has emerged for strengthening their integration. This combination not only brings together computations and experiments focused on the same enzymatic problems, but also provides complementary insights into the investigated properties and has a powerful synergy effect. This thematic volume of Advances in Protein Chemistry and Structural Biology focuses on the recent success in structural and mechanistic enzymology and has its main emphasis on explaining the enzyme phenomena by using both the experimental and computational approaches. The selected contributions demonstrate how the application of a variety of experimental techniques and modeling methods helps further the understanding of enzyme dynamics, mechanism, inhibition, and drug design. - Focuses on the recent success in structural and mechanistic enzymology - Has its main emphasis on explaining the enzyme phenomena by using both the experimental and computational approaches - Demonstrates how the application of a variety of experimental techniques and modeling methods helps further the understanding of enzyme dynamics, mechanism, inhibition, and drug design

In this volume, a detailed description of cutting-edge computational methods applied to protein modeling as well as specific applications are presented. Chapters include: the application of Car-Parrinello techniques to enzyme mechanisms, the outline and application of QM/MM methods, polarizable force fields, recent methods of ligand docking, molecular dynamics related to NMR spectroscopy, computer optimization of absorption, distribution, metabolism and excretion extended by toxicity for drugs, enzyme design and bioinformatics applied to protein structure prediction. A keen emphasis is laid on the clear presentation of complex concepts, since the book is primarily aimed at Ph.D. students, who need an insight in up-to-date protein modeling. The inclusion of descriptive, color figures will allow the reader to get a pictorial representation of complicated structural issues.

"Kinetics and Dynamics" on molecular modeling of dynamic processes opens with an introductory overview before discussing approaches to reactivity of small systems in the gas phase. Then it examines studies of systems of increasing complexity up to the dynamics of DNA. This title has interdisciplinary character presenting wherever possible an interplay between the theory and the experiment. It provides basic information as well as the details of theory and examples of its application to experimentalists and theoreticians interested in modeling of dynamic processes in chemical and biochemical systems. All contributing authors are renowned experts in their fields and topics covered in this volume represent the forefront of today’s science.

The Reviews in Computational Chemistry series brings together leading authorities in the field to teach the newcomer and update the expert on topics centered around molecular modeling, such as computer-assisted molecular design (CAMD), quantum chemistry, molecular mechanics and dynamics, and quantitative structure-activity relationships (QSAR). This volume, like those prior to it, features chapters by experts in various fields of computational chemistry. Topics in Volume 28 include: Free-energy Calculations with Metadynamics Polarizable Force Fields for Biomolecular Modeling Modeling Protein Folding Pathways Assessing Structural Predictions of Protein-Protein Recognition Kinetic Monte Carlo Simulation of Electrochemical Systems Reactivity and Dynamics at Liquid Interfaces

Epigenetic Technological Applications is a compilation of state-of-the-art technologies involved in epigenetic research. Epigenetics is an exciting new field of biology research, and many technologies are invented and developed specifically for epigenetics study. With chapters covering the latest developments in crystallography, computational modeling, the uses of histones, and more, Epigenetic Technological Applications addresses the question of how these new ideas, procedures, and innovations can be applied to current epigenetics research, and how they can keep pushing discovery forward and beyond the epigenetic realm. - Discusses technologies that are critical for epigenetic research and application - Includes epigenetic applications for state-of-the-art technologies - Contains a global perspective on the future of epigenetics