Innovative and forward-looking, this volume focuses on recent achievements in this rapidly progressing field and looks at future potential for development. The first part provides a basic understanding of the factors governing protein-ligand interactions, followed by a comparison of key experimental methods (calorimetry, surface plasmon resonance, NMR) used in generating interaction data. The second half of the book is devoted to insilico methods of modeling and predicting molecular recognition and binding, ranging from first principles-based to approximate ones. Here, as elsewhere in the book, emphasis is placed on novel approaches and recent improvements to established methods. The final part looks at unresolved challenges, and the strategies to address them. With the content relevant for all drug classes and therapeutic fields, this is an inspiring and often-consulted guide to the complexity of protein-ligand interaction modeling and analysis for both novices and experts.
Chemical modelling covers a wide range of disciplines, and this book is the first stop for any chemist, materials scientist, biochemist, or molecular physicist wishing to acquaint themselves with major developments in the applications and theory of chemical modelling. Containing both comprehensive and critical reviews, it is a convenient reference to the current literature. Coverage includes, but is not limited to, considerations towards rigorous foundations for the natural-orbital representation of molecular electronic transitions, quantum and classical embedding schemes for optical properties, machine learning for excited states, ultrafast and wave function-based electron dynamics, and attosecond chemistry.
All set to become the standard reference on the topic, this book covers the most important procedures for chemical functionalization, making it an indispensable resource for all chemists, physicists, materials scientists and engineers entering or already working in the field. Expert authors share their knowledge on a wide range of different functional groups, including organic functional groups, hydrogen, halogen, nanoparticles and polymers.
Reviewing statistical mechanics concepts for analysis of macromolecular structure formation processes, for graduate students and researchers in physics and biology.
This book introduces recent progress in biological energetics from ATP hydrolysis to molecular machineries. The role of water is now recognized to be essential in biological molecular energetics. Although energetics is a rather distant field to many biologists, any working models for protein machineries such as protein motors, transporters, and other enzymes must be consistent with their energetics. Therefore, the book is intended to help scientists build systematic models of biomolecular functions based on three categories: (1) ATP hydrolysis reactions including ionic hydration and protonation–deprotonation of biomolecules, (2) protein–ligand/protein–protein interactions including hydration–dehydration processes, and (3) functioning mechanisms of protein machineries based on water functions.
Covering theoretical methods and computational techniques in biomolecular research, this book focuses on approaches for the treatment of macromolecules, including proteins, nucleic acids, and bilayer membranes. It uses concepts in free energy calculations, conformational analysis, reaction rates, and transition pathways to calculate and interpret b
Over the past several decades there have been major advances in our ability to computationally evaluate the electronic structure of inorganic molecules, particularly transition metal systems. This advancement is due to the Moore’s Law increase in computing power as well as the impact of density functional theory (DFT) and its implementation in commercial and freeware programs for quantum chemical calculations. Improved pure and hybrid density functionals are allowing DFT calculations with accuracy comparable to high-level Hartree-Fock treatments, and the results of these calculations can now be evaluated by experiment. When calculations are correlated to, and supported by, experimental data they can provide fundamental insight into electronic structure and its contributions to physical properties and chemical reactivity. This interplay continues to expand and contributes to both improved value of experimental results and improved accuracy of computational predictions. The purpose of this EIC Book is to provide state-of-the-art presentations of quantum mechanical and related methods and their applications, written by many of the leaders in the field. Part 1 of this volume focuses on methods, their background and implementation, and their use in describing bonding properties, energies, transition states and spectroscopic features. Part 2 focuses on applications in bioinorganic chemistry and Part 3 discusses inorganic chemistry, where electronic structure calculations have already had a major impact. This addition to the EIC Book series is of significant value to both experimentalists and theoreticians, and we anticipate that it will stimulate both further development of the methodology and its applications in the many interdisciplinary fields that comprise modern inorganic and bioinorganic chemistry. This volume is also available as part of Encyclopedia of Inorganic Chemistry, 5 Volume Set. This set combines all volumes published as EIC Books from 2007 to 2010, representing areas of key developments in the field of inorganic chemistry published in the Encyclopedia of Inorganic Chemistry. Find out more.
A comprehensive view of the current methods for modeling solvent environments with contributions from the leading researchers in the field. Throughout, the emphasis is placed on the application of such models in simulation studies of biological processes, although the coverage is sufficiently broad to extend to other systems as well. As such, this monograph treats a full range of topics, from statistical mechanics-based approaches to popular mean field formalisms, coarse-grained solvent models, more established explicit, fully atomic solvent models, and recent advances in applying ab initio methods for modeling solvent properties.
Computer-Aided Drug Discovery Methods: A Brief Introduction explores the cutting-edge field at the intersection of computational science and medicinal chemistry. This comprehensive volume navigates from foundational concepts to advanced methodologies, illuminating how computational tools accelerate the discovery of new therapeutics. Beginning with an overview of drug discovery principles, the book explains topics such as pharmacophore modeling, molecular dynamics simulations, and molecular docking. It discusses the application of density functional theory and the role of artificial intelligence in therapeutic development, showcasing successful case studies and innovations in COVID-19 research. Ideal for undergraduate and graduate students, as well as researchers in academia and industry, this book serves as a vital resource in understanding the complex landscape of modern drug discovery. It emphasizes the synergy between computational methods and experimental validation, shaping the future of pharmaceutical sciences toward more effective and targeted therapies.
