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Machine Learning in Biomolecular Simulations by Gennady Verkhivker,Vojtech Spiwok,Francesco L. Gervasio Pdf
Machine learning methods such as neural networks, non-linear dimensionality reduction techniques, random forests and others meet in this research topic with biomolecular simulations. The authors of eight articles applied these methods to analyze simulation results, accelerate simulations or to make molecular mechanics force fields more accurate.
Molecular Dynamics and Machine Learning in Drug Discovery by Sergio Decherchi,Andrea Cavalli,Pratyush Tiwary,Francesca Grisoni Pdf
Dr. Sergio Decherchi and Dr. Andrea Cavalli are co-founders of BiKi Technologies s.r.l. - a company that commercializes a Molecular Dynamics-based software suite for drug discovery. All other Topic Editors declare no competing interests with regards to the Research Topic subject.
Biomolecular Simulations in Structure-Based Drug Discovery by Francesco L. Gervasio,Vojtech Spiwok,Raimund Mannhold Pdf
A guide to applying the power of modern simulation tools to better drug design Biomolecular Simulations in Structure-based Drug Discovery offers an up-to-date and comprehensive review of modern simulation tools and their applications in real-life drug discovery, for better and quicker results in structure-based drug design. The authors describe common tools used in the biomolecular simulation of drugs and their targets and offer an analysis of the accuracy of the predictions. They also show how to integrate modeling with other experimental data. Filled with numerous case studies from different therapeutic fields, the book helps professionals to quickly adopt these new methods for their current projects. Experts from the pharmaceutical industry and academic institutions present real-life examples for important target classes such as GPCRs, ion channels and amyloids as well as for common challenges in structure-based drug discovery. Biomolecular Simulations in Structure-based Drug Discovery is an important resource that: -Contains a review of the current generation of biomolecular simulation tools that have the robustness and speed that allows them to be used as routine tools by non-specialists -Includes information on the novel methods and strategies for the modeling of drug-target interactions within the framework of real-life drug discovery and development -Offers numerous illustrative case studies from a wide-range of therapeutic fields -Presents an application-oriented reference that is ideal for those working in the various fields Written for medicinal chemists, professionals in the pharmaceutical industry, and pharmaceutical chemists, Biomolecular Simulations in Structure-based Drug Discovery is a comprehensive resource to modern simulation tools that complement and have the potential to complement or replace laboratory assays for better results in drug design.
Biomanufacturing for Sustainable Production of Biomolecules by Vijai Singh,Pau Loke Show Pdf
This book elucidates the sustainable production of commercially important biomolecules in medicines, food, and beverage processing, through biological systems, including microorganisms, animal cells, plant cells, tissues, enzymes, and in vitro. It discusses promising technologies for the manipulation of cells including, genetic engineering, synthetic biology, genome editing, and metabolic engineering. The initial chapters of the book introduce topics on biomanufacturing, circular economy, strain design and improvement, upstream and downstream processing. The subsequent chapters cover artificial intelligence-assisted production, designer cell factories, biosensors for monitoring biomolecules, different cells factories, biosynthetic pathways, and genome editing approaches for scale-up biomanufacturing. Lastly, the book discusses the opportunities and challenges of implementing biological systems for the production of biomolecules. This book is a valuable source for students, researchers, scientists, clinicians, stakeholders, policymakers, and practitioners to understand biomanufacturing for the sustainable production of biomolecules.
Chemical Theory and Multiscale Simulation in Biomolecules by Guohui Li Pdf
Chemical Theory and Multiscale Simulation in Biomolecules: From Principles to Case Studies helps readers understand what simulation is, what information modeling of biomolecules can provide, and how to compare this information with experiments. Beginning with an introduction to computational theory for modeling, the book goes on to describe how to control the conditions of modeling systems and possible strategies for time-cost savings in computation. Part Two further outlines key methods, with step-by-step guidance supporting readers in studying and practicing simulation processes. Part Three then shows how these theories are controlled and applied in practice, through examples and case studies on varied applications. This book is a practical guide for new learners, supporting them in learning and applying molecular modeling in practice, whilst also providing more experienced readers with the knowledge needed to gain a deep understanding of the theoretical background behind key methods. Presents computational theory alongside case studies to help readers understand the use of simulation in practice Includes extensive examples of different types of simulation methods and approaches to result analysis Provides an overview of the current academic frontier and research challenges, encouraging creativity and directing attention to current problems
Introduction to Modern Biophysics by Mohammad Ashrafuzzaman Pdf
This textbook provides an introduction to the fundamental and applied aspects of biophysics for advanced undergraduate and graduate students of physics, chemistry, and biology. The application of physics principles and techniques in exploring biological systems has long been a tradition in scientific research. Biological systems hold naturally inbuilt physical principles and processes which are popularly explored. Systematic discoveries help us understand the structures and functions of individual biomolecules, biomolecular systems, cells, organelles, tissues, and even the physiological systems of animals and plants. Utilizing a physics- based scientific understanding of biological systems to explore disease is at the forefront of applied scientific research. This textbook covers key breakthroughs in biophysics whilst looking ahead to future horizons and directions of research. It contains models based on both classical and quantum mechanical treatments of biological systems. It explores diseases related to physical alterations in biomolecular structures and organizations alongside drug discovery strategies. It also discusses the cutting- edge applications of nanotechnologies in manipulating nanoprocesses in biological systems. Key Features: • Presents an accessible introduction to how physics principles and techniques can be used to understand biological and biochemical systems. • Addresses natural processes, mutations, and their purposeful manipulation. • Lays the groundwork for vitally important natural scientific, technological, and medical advances. Mohammad Ashrafuzzaman, a biophysicist and condensed matter scientist, is passionate about investigating biological and biochemical processes utilizing physics principles and techniques. He is a professor of biophysics at King Saud University’s Biochemistry Department in the College of Science, Riyadh, Saudi Arabia; the co- founder of MDT Canada Inc., and the founder of Child Life Development Institute, Edmonton, Canada. He has authored Biophysics and Nanotechnology of Ion Channels, Nanoscale Biophysics of the Cell, and Membrane Biophysics. He has also published about 50 peer- reviewed articles and several patents, edited two books, and has been serving on the editorial boards of Elsevier and Bentham Science journals. Dr. Ashrafuzzaman has held research and academic ranks at Bangladesh University of Engineering & Technology, University of Neuchatel (Switzerland), Helsinki University of Technology (Finland), Weill Medical College of Cornell University (USA), and University of Alberta (Canada). During 2013– 2018 he also served as a Visiting Professor at the Departments of Oncology, and Medical Microbiology and Immunology, of the University of Alberta. Dr. Ashrafuzzaman earned his highest academic degree, Doctor of Science (D.Sc.) in condensed matter physics from the University of Neuchatel, Switzerland in 2004.
Handbook of Biomolecules by Chandrabhan Verma,Dakeshwar Kumar Verma Pdf
Handbook of Biomolecules: Fundamentals, Properties and Applications is a comprehensive resource covering new developments in biomolecules and biomaterials and their industrial applications in the fields of bioengineering, biomedical engineering, biotechnology, biochemistry, and their detection methods using biosensors. This book covers the fundamentals of biomolecules, their roll in living organism, structure, sources, important characteristics, and the industrial applications of these biomaterials. Sections explore amino acids, carbohydrates, nucleic acids, proteins, lipids, metabolites and natural products, then go on to discuss purification techniques and detection methods. Applications in biomolecular engineering, biochemistry and biomedical engineering, among others, are discussed before concluding with coverage of biomolecules as anticorrosion materials. Provides the chronological advancement of biomolecules, their biochemical reaction, and many modern industrial applications in engineering and science Serves as a valuable source for researchers interested in the fundamentals, basics and modern applications of biomolecules Covers both synthetic and natural biomolecule synthesis and purification processes and their modern applications Bridges the gap between the fundamental science of biomolecular chemistry and the relevant technology and industrial applications
Biomolecular Simulations by Massimiliano Bonomi,Carlo Camilloni Pdf
This volume explores the recent advancements in biomolecular simulations of proteins, small molecules, and nucleic acids, with a primary focus on classical molecular dynamics (MD) simulations at atomistic, coarse-grained, and quantum/ab-initio levels. The chapters in this book are divided into four parts: Part One looks at recent techniques used in the development of physic-chemical models of proteins, small molecules, nucleic acids, and lipids; Part Two discusses enhanced sampling and free-energy calculations; Part Three talks about integrative computational and experimental approaches for biomolecular simulations; and Part Four focuses on analyzing, visualizing, and comparing biomolecular simulations. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and comprehensive, Biomolecular Simulations: Methods and Protocols is a valuable resource for both novice and expert researchers who are interested in studying different areas of biomolecular simulations, and discovering new tools to progress their future projects.
Machine Learning Meets Quantum Physics by Kristof T. Schütt,Stefan Chmiela,O. Anatole von Lilienfeld,Alexandre Tkatchenko,Koji Tsuda,Klaus-Robert Müller Pdf
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.
Functional Properties of Advanced Engineering Materials and Biomolecules by Felipe A. La Porta,Carlton A. Taft Pdf
This book shows how a small toolbox of experimental techniques, physical chemistry concepts as well as quantum/classical mechanics and statistical methods can be used to understand, explain and even predict extraordinary applications of these advanced engineering materials and biomolecules. It highlights how improving the material foresight by design, including the fundamental understanding of their physical and chemical properties, can provide new technological levels in the future.
Recent advances in computational modelling of biomolecular complexes by Zhongjie Liang,Adolfo Poma,Kurt Kremer,Kei-ichi Okazaki,Sergio Pantano,Simón Poblete Pdf
Virtual Screening and Drug Docking, Volume 59 in the Annual Reports on Medicinal Chemistry series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Can docking scoring functions guarantee success in virtual screening?, No dance, no partner! A tale of flexibility in docking and virtual screening, Handling Imbalance Data in Virtual Screening, Rational computational approaches to predict novel drug candidates against leishmaniasis, Virtual screening against Mtb DNA gyrase: Applications and success stories, Using Filters in Virtual Screening: A Brief Guide to Minimize Errors and Maximize Efficiency, and more. Additional chapters in the new release include Machine Learning and Deep Learning Strategies for Virtual Screening, Applications of the Virtual Screening to find the novel HIV-1 therapeutic agents, and Large-scale screening of small molecules with docking strategies and its impact on drug discovery. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Annual Reports on Medicinal Chemistry series Updated release includes the latest information on Virtual Screening and Drug Docking
Machine Learning and Its Application to Reacting Flows by Nedunchezhian Swaminathan,Alessandro Parente Pdf
This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows. These two fields, ML and turbulent combustion, have large body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the world’s total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. Whether this is practical or not is entirely a different question, and an answer to this question depends on the respondent. However, a pragmatic analysis suggests that the combustion share to TPES is likely to be more than 70% even by 2070. Hence, it will be prudent to take advantage of ML techniques to improve combustion sciences and technologies so that efficient and “greener” combustion systems that are friendlier to the environment can be designed. The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges. The required mathematical equations and backgrounds are discussed with ample references for readers to find further detail if they wish. This book is unique since there is not any book with similar coverage of topics, ranging from big data analysis and machine learning algorithm to their applications for combustion science and system design for energy generation.
Molecular Modeling and Simulation by Tamar Schlick Pdf
Very broad overview of the field intended for an interdisciplinary audience; Lively discussion of current challenges written in a colloquial style; Author is a rising star in this discipline; Suitably accessible for beginners and suitably rigorous for experts; Features extensive four-color illustrations; Appendices featuring homework assignments and reading lists complement the material in the main text
Computational Approaches for Understanding Dynamical Systems: Protein Folding and Assembly by Anonim Pdf
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
