An Introduction To Markov State Models And Their Application To Long Timescale Molecular Simulation
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An Introduction To Markov State Models And Their Application To Long Timescale Molecular Simulation
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Author : Gregory R. Bowman
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-02
An Introduction To Markov State Models And Their Application To Long Timescale Molecular Simulation written by Gregory R. Bowman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-02 with Science categories.
The aim of this book volume is to explain the importance of Markov state models to molecular simulation, how they work, and how they can be applied to a range of problems. The Markov state model (MSM) approach aims to address two key challenges of molecular simulation: 1) How to reach long timescales using short simulations of detailed molecular models. 2) How to systematically gain insight from the resulting sea of data. MSMs do this by providing a compact representation of the vast conformational space available to biomolecules by decomposing it into states sets of rapidly interconverting conformations and the rates of transitioning between states. This kinetic definition allows one to easily vary the temporal and spatial resolution of an MSM from high-resolution models capable of quantitative agreement with (or prediction of) experiment to low-resolution models that facilitate understanding. Additionally, MSMs facilitate the calculation of quantities that are difficult to obtain from more direct MD analyses, such as the ensemble of transition pathways. This book introduces the mathematical foundations of Markov models, how they can be used to analyze simulations and drive efficient simulations, and some of the insights these models have yielded in a variety of applications of molecular simulation.
Computational Approaches For Understanding Dynamical Systems Protein Folding And Assembly
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Author :
language : en
Publisher: Academic Press
Release Date : 2020-03-05
Computational Approaches For Understanding Dynamical Systems Protein Folding And Assembly written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-05 with Science categories.
Computational Approaches for Understanding Dynamical Systems: Protein Folding and Assembly, Volume 170 in the Progress in Molecular Biology and Translational Science series, provides the most topical, informative and exciting monographs available on a wide variety of research topics. The series includes in-depth knowledge on the molecular biological aspects of organismal physiology, with this release including chapters on Pairwise-Additive and Polarizable Atomistic Force Fields for Molecular Dynamics Simulations of Proteins, Scale-consistent approach to the derivation of coarse-grained force fields for simulating structure, dynamics, and thermodynamics of biopolymers, Enhanced sampling and free energy methods, and much more. - Includes comprehensive coverage on molecular biology - Presents ample use of tables, diagrams, schemata and color figures to enhance the reader's ability to rapidly grasp the information provided - Contains contributions from renowned experts in the field
Supramolecular Nanotechnology
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Author : Omar Azzaroni
language : en
Publisher: John Wiley & Sons
Release Date : 2023-04-25
Supramolecular Nanotechnology written by Omar Azzaroni and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-25 with Technology & Engineering categories.
Supramolecular Nanotechnology Provides up-to-date coverage of both current knowledge and new developments in the dynamic and interdisciplinary field of supramolecular nanotechnology In recent years, supramolecular nanotechnology has revolutionized research in chemistry, physics, and materials science. These easily manipulated molecular units enable the synthesis of novel nanomaterials for use in a wide range of current and potential applications including electronics, sensors, drug delivery, and imaging. Supramolecular Nanotechnology presents a state-of-the-art overview of functional self-assembling nanomaterials based on organic and polymeric molecules. Featuring contributions by an international panel of experts in the field, this comprehensive volume covers the design of self-assembled materials, their synthesis and diverse fabrication methods, the characterization of supramolecular architectures, and current and emerging applications in chemistry, biology, and medicine. Detailed chapters discuss the synthesis of peptide-based supramolecular structures and polymeric self-assembling materials, their characterization, advanced microscopy techniques, nanostructures made of porphyrins, polyelectrolytes, silica, their application in catalysis and cancer, atomistic and coarse-grained simulations, and more. Presents cutting-edge research on rationally designed, self-assembled supramolecular structures Discusses the impact of supramolecular nanotechnology on current and future research and technology Highlights applications of self-assembled supramolecular systems in catalysis, biomedical imaging, cancer therapies, and regenerative medicine Provides synthetic strategies for preparing the molecular assemblies and various characterization techniques for assessing the supramolecular morphology Describes theoretical modeling and simulation techniques for analyzing supramolecular nanostructures Supramolecular Nanotechnology: Advanced Design of Self-Assembled Functional Materials is essential reading for materials scientists and engineers, polymer and organic chemists, pharmaceutical scientists, molecular physicists and biologists, and chemical engineers.
Computer Aided And Machine Learning Driven Drug Design
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Author : Vinícius Gonçalves Maltarollo
language : en
Publisher: Springer Nature
Release Date : 2025-02-27
Computer Aided And Machine Learning Driven Drug Design written by Vinícius Gonçalves Maltarollo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-27 with Science categories.
The computer-aided drug design research field comprises several different knowledge areas, and often, researchers are only familiar or experienced with a small fraction of them. Indeed, pharmaceutical industries and large academic groups rely on a broad range of professionals, including chemists, biologists, pharmacists, and computer scientists. In this sense, it is difficult to be an expert in every single CADD approach. Furthermore, there are well-established methods that are constantly revisited, and novel approaches are introduced, such as machine-learning based scoring functions for molecular docking. This book provides an organized update of the most commonly employed CADD techniques, as well as successful examples of actual applications to develop bioactive compounds/drug candidates. Also includes is a section of case studies that cover certain pharmacological/target classes, focusing on the applications of the previously described methods. This part will especially appeal to professionals who are not as interested in the theoretical aspects of CADD. This is an ideal book for students, researchers, and industry professionals in the fields of pharmacy, chemistry, biology, bioinformatics, computer sciences, and medicine who are seeking a go-to reference on drug design and medicinal chemistry.
Protein Interactions
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Author : Volkhard Helms
language : en
Publisher: John Wiley & Sons
Release Date : 2022-11-15
Protein Interactions written by Volkhard Helms and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-15 with Science categories.
Protein Interactions A fundamental guide to the burgeoning field of protein interactions From enzymes to transcription factors to cell membrane receptors, proteins are at the heart of biological cell function. Virtually all cellular processes are governed by their interactions, with one another, with cell bodies, with DNA, or with small molecules. The systematic study of these interactions is called Interactomics, and research within this new field promises to shape the future of molecular cell biology. Protein Interactions goes beyond any existing guide to protein interactions, presenting the first truly comprehensive overview of the field. Edited by two leading scholars in the field of protein bioinformatics, this book covers all known categories of protein interaction, stable as well as transient, as well as the effect of mutations and post-translational modifications on the interaction behavior. Protein Interactions readers will also find: Introductory chapters on protein structure, conformational dynamics, and protein-protein binding interfaces A data-driven approach incorporating machine learning and integrating experimental data into computational models An outlook on the current challenges in the field and suggestions for future research Protein Interactions will serve as a fundamental resource for novice researchers who want a systematic introduction to interactomics, as well as for experienced cell biologists and bioinformaticians who want to gain an edge in this exciting new field.
Machine Learning Meets Quantum Physics
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Author : Kristof T. Schütt
language : en
Publisher: Springer Nature
Release Date : 2020-06-03
Machine Learning Meets Quantum Physics written by Kristof T. Schütt and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-03 with Science categories.
Designing molecules and materials with desired properties is an important prerequisite for advancing technology in our modern societies. This requires both the ability to calculate accurate microscopic properties, such as energies, forces and electrostatic multipoles of specific configurations, as well as efficient sampling of potential energy surfaces to obtain corresponding macroscopic properties. Tools that can provide this are accurate first-principles calculations rooted in quantum mechanics, and statistical mechanics, respectively. Unfortunately, they come at a high computational cost that prohibits calculations for large systems and long time-scales, thus presenting a severe bottleneck both for searching the vast chemical compound space and the stupendously many dynamical configurations that a molecule can assume. To overcome this challenge, recently there have been increased efforts to accelerate quantum simulations with machine learning (ML). This emerging interdisciplinary community encompasses chemists, material scientists, physicists, mathematicians and computer scientists, joining forces to contribute to the exciting hot topic of progressing machine learning and AI for molecules and materials. The book that has emerged from a series of workshops provides a snapshot of this rapidly developing field. It contains tutorial material explaining the relevant foundations needed in chemistry, physics as well as machine learning to give an easy starting point for interested readers. In addition, a number of research papers defining the current state-of-the-art are included. The book has five parts (Fundamentals, Incorporating Prior Knowledge, Deep Learning of Atomistic Representations, Atomistic Simulations and Discovery and Design), each prefaced by editorial commentary that puts the respective parts into a broader scientific context.
Computational Techniques For Analytical Chemistry And Bioanalysis
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Author : Philippe B Wilson
language : en
Publisher: Royal Society of Chemistry
Release Date : 2020-12-08
Computational Techniques For Analytical Chemistry And Bioanalysis written by Philippe B Wilson and has been published by Royal Society of Chemistry this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-08 with Science categories.
As analysis, in terms of detection limits and technological innovation, in chemical and biological fields has developed so computational techniques have advanced enabling greater understanding of the data. Indeed, it is now possible to simulate spectral data to an excellent level of accuracy, allowing chemists and biologists access to robust and reliable analytical methodologies both experimentally and theoretically. This work will serve as a definitive overview of the field of computational simulation as applied to analytical chemistry and biology, drawing on recent advances as well as describing essential, established theory. Computational approaches provide additional depth to biochemical problems, as well as offering alternative explanations to atomic scale phenomena. Highlighting the innovative and wide-ranging breakthroughs made by leaders in computational spectrum prediction and the application of computational methodologies to analytical science, this book is for graduates and postgraduate researchers showing how computational analytical methods have become accessible across disciplines. Contributed chapters originate from a group of internationally-recognised leaders in the field, each applying computational techniques to develop our understanding of and supplement the data obtained from experimental analytical science.
Computational Approaches For Studying Enzyme Mechanism Part B
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Author :
language : en
Publisher: Academic Press
Release Date : 2016-08-03
Computational Approaches For Studying Enzyme Mechanism Part B written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-03 with Science categories.
Computational Approaches for Studying Enzyme Mechanism, Part B is the first of two volumes in the Methods in Enzymology series that focuses on computational approaches for studying enzyme mechanism. The serial achieves the critically acclaimed gold standard of laboratory practices and remains one of the most highly respected publications in the molecular biosciences. Each volume is eagerly awaited, frequently consulted, and praised by researchers and reviewers alike. Now with over 550 volumes, the series remains a prominent and essential publication for researchers in all fields of the life sciences and biotechnology, including biochemistry, chemical biology, microbiology, synthetic biology, cancer research, genetics, and other fields of study. - Focuses on computational approaches for studying enzyme mechanism - Continues the legacy of this premier serial with quality chapters authored by leaders in the field - Covers research methods in intermediate filament associated proteins, and contains sections on such topics as lamin-associated proteins, intermediate filament-associated proteins and plakin, and other cytoskeletal cross-linkers
Combining Simulations Theory And Experiments Into Multiscale Models Of Biological Events
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Author : Fabio Trovato
language : en
Publisher: Frontiers Media SA
Release Date : 2022-01-11
Combining Simulations Theory And Experiments Into Multiscale Models Of Biological Events written by Fabio Trovato and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-11 with Science categories.
Cheminformatics Qsar And Machine Learning Applications For Novel Drug Development
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Author : Kunal Roy
language : en
Publisher: Elsevier
Release Date : 2023-05-23
Cheminformatics Qsar And Machine Learning Applications For Novel Drug Development written by Kunal Roy and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-23 with Medical categories.
Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development aims at showcasing different structure-based, ligand-based, and machine learning tools currently used in drug design. It also highlights special topics of computational drug design together with the available tools and databases. The integrated presentation of chemometrics, cheminformatics, and machine learning methods under is one of the strengths of the book.The first part of the content is devoted to establishing the foundations of the area. Here recent trends in computational modeling of drugs are presented. Other topics present in this part include QSAR in medicinal chemistry, structure-based methods, chemoinformatics and chemometric approaches, and machine learning methods in drug design. The second part focuses on methods and case studies including molecular descriptors, molecular similarity, structure-based based screening, homology modeling in protein structure predictions, molecular docking, stability of drug receptor interactions, deep learning and support vector machine in drug design. The third part of the book is dedicated to special topics, including dedicated chapters on topics ranging from de design of green pharmaceuticals to computational toxicology. The final part is dedicated to present the available tools and databases, including QSAR databases, free tools and databases in ligand and structure-based drug design, and machine learning resources for drug design. The final chapters discuss different web servers used for identification of various drug candidates. - Presents chemometrics, cheminformatics and machine learning methods under a single reference - Showcases the different structure-based, ligand-based and machine learning tools currently used in drug design - Highlights special topics of computational drug design and available tools and databases