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Author: Eudenilson L. Albuquerque
Publisher: Elsevier
ISBN: 0443155313
Category : Science
Languages : en
Pages : 304
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Book Description
Quantum Chemistry Methods for Oncological Drugs provides a comprehensive reference text for student, researchers, and academic staff across disciplines working in the field of Nanobiotechnology, who need to grasp the unique inter-relationship of the physical, chemical, and biological properties of oncological drugs and their interactions. It provides a theoretical/computational framework based on quantum chemistry and addresses key questions in which detailed analysis and precise predictions are always required. The sophisticated molecular recognition of various natural biological materials has been used in the formation of a complex network of structures potentially useful for a variety of pharmaceutical applications. They offer solutions to many of the obstacles that need to be overcome, with accuracy not feasible with the technologies usually available in materials science. Important common challenges presented in this book are aspects related to the biology of cancer using our immunological checking points, specialized proteins that act as brakes in the immune system, allowing it to recognize and attack more efficiently only the cancer cells, avoiding the destruction of healthy cells as in conventional chemotherapy and radiotherapy treatments. This book is devoted to this burgeoning area of Nanobiotechnology for oncological drugs and will be valuable in covering the new developments that have occurred in the last decade or so. It is aimed at graduate students, faculty members and other researchers in physics, chemistry, biology, pharmacology, and medicine. - Comprehensive and up-to-date account of the main physical, chemical, biological, and pharmaceutical properties of oncological drugs and their interactions, using a theoretical/computational framework based on quantum chemistry - Focuses on an exciting and dynamic area of research, not only in the academic world but also in the Nanobiotechnology industry - Strong multidisciplinary content: the immediate future of pure and applied scientific research undoubtedly points to the interconnection and complementarity between different areas
Author: Eudenilson L. Albuquerque
Publisher: Elsevier
ISBN: 0443155313
Category : Science
Languages : en
Pages : 304
Get Book Here
Book Description
Quantum Chemistry Methods for Oncological Drugs provides a comprehensive reference text for student, researchers, and academic staff across disciplines working in the field of Nanobiotechnology, who need to grasp the unique inter-relationship of the physical, chemical, and biological properties of oncological drugs and their interactions. It provides a theoretical/computational framework based on quantum chemistry and addresses key questions in which detailed analysis and precise predictions are always required. The sophisticated molecular recognition of various natural biological materials has been used in the formation of a complex network of structures potentially useful for a variety of pharmaceutical applications. They offer solutions to many of the obstacles that need to be overcome, with accuracy not feasible with the technologies usually available in materials science. Important common challenges presented in this book are aspects related to the biology of cancer using our immunological checking points, specialized proteins that act as brakes in the immune system, allowing it to recognize and attack more efficiently only the cancer cells, avoiding the destruction of healthy cells as in conventional chemotherapy and radiotherapy treatments. This book is devoted to this burgeoning area of Nanobiotechnology for oncological drugs and will be valuable in covering the new developments that have occurred in the last decade or so. It is aimed at graduate students, faculty members and other researchers in physics, chemistry, biology, pharmacology, and medicine. - Comprehensive and up-to-date account of the main physical, chemical, biological, and pharmaceutical properties of oncological drugs and their interactions, using a theoretical/computational framework based on quantum chemistry - Focuses on an exciting and dynamic area of research, not only in the academic world but also in the Nanobiotechnology industry - Strong multidisciplinary content: the immediate future of pure and applied scientific research undoubtedly points to the interconnection and complementarity between different areas
Author: Eudenilson L. Albuquerque
Publisher: Cambridge University Press
ISBN: 1108803849
Category : Science
Languages : en
Pages : 435
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Book Description
Nano-biotechnology crosses the boundaries between physics, biochemistry and bioengineering, and has profound implications for the biomedical engineering industry. This book describes the quantum chemical simulation of a wide variety of molecular systems, with detailed analysis of their quantum chemical properties, individual molecular configurations, and cutting-edge biomedical applications. Topics covered include the basic properties of quantum chemistry and its conceptual foundations, the nanoelectronics and thermodynamics of DNA, the optoelectronic properties of the five DNA/RNA nucleobase anhydrous crystals, and key examples of molecular diode prototypes. A wide range of important applications are described, including protein binding of drugs such as cholesterol-lowering, anti-Parkinson and anti-migraine drugs, and recent developments in cancer biology are also discussed. This modern and comprehensive text is essential reading for graduate students and researchers in multidisciplinary areas of biological physics, chemical physics, chemical engineering, biochemistry and bioengineering.
Author: Vasanthanathan Poongavanam
Publisher: John Wiley & Sons
ISBN: 3527840737
Category : Science
Languages : en
Pages : 882
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Book Description
Computational Drug Discovery A comprehensive resource that explains a wide array of computational technologies and methods driving innovation in drug discovery Computational Drug Discovery: Methods and Applications (2 volume set) covers a wide range of cutting-edge computational technologies and computational chemistry methods that are transforming drug discovery. The book delves into recent advances, particularly focusing on artificial intelligence (AI) and its application for protein structure prediction, AI-enabled virtual screening, and generative modeling for compound design. Additionally, it covers key technological advancements in computing such as quantum and cloud computing that are driving innovations in drug discovery. Furthermore, dedicated chapters that addresses the recent trends in the field of computer aided drug design, including ultra-large-scale virtual screening for hit identification, computational strategies for designing new therapeutic modalities like PROTACs and covalent inhibitors that target residues beyond cysteine are also presented. To offer the most up-to-date information on computational methods utilized in computational drug discovery, it covers chapters highlighting the use of molecular dynamics and other related methods, application of QM and QM/MM methods in computational drug design, and techniques for navigating and visualizing the chemical space, as well as leveraging big data to drive drug discovery efforts. The book is thoughtfully organized into eight thematic sections, each focusing on a specific computational method or technology applied to drug discovery. Authored by renowned experts from academia, pharmaceutical industry, and major drug discovery software providers, it offers an overview of the latest advances in computational drug discovery. Key topics covered in the book include: Application of molecular dynamics simulations and related approaches in drug discovery The application of QM, hybrid approaches such as QM/MM, and fragment molecular orbital framework for understanding protein-ligand interactions Adoption of artificial intelligence in pre-clinical drug discovery, encompassing protein structure prediction, generative modeling for de novo design, and virtual screening. Techniques for navigating and visualizing the chemical space, along with harnessing big data to drive drug discovery efforts. Methods for performing ultra-large-scale virtual screening for hit identification. Computational strategies for designing new therapeutic models, including PROTACs and molecular glues. In silico ADMET approaches for predicting a variety of pharmacokinetic and physicochemical endpoints. The role of computing technologies like quantum computing and cloud computing in accelerating drug discovery This book will provide readers an overview of the latest advancements in computational drug discovery and serve as a valuable resource for professionals engaged in drug discovery.
Author: Ganji Purnachandra Nagaraju
Publisher: Elsevier
ISBN: 0443152810
Category : Computers
Languages : en
Pages : 460
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Book Description
Computational Methods in Drug Discovery and Repurposing for Cancer Therapy provides knowledge about ongoing research as well as computational approaches for drug discovery and repurposing for cancer therapy. The book also provides detailed descriptions about target molecules, pathways, and their inhibitors for easy understanding and applicability. The book discusses tools and techniques such as integrated bioinformatics approaches, systems biology tools, molecular docking, computational chemistry, artificial intelligence, machine learning, structure-based virtual screening, biomarkers, and transcriptome; those are discussed in the context of different cancer types, such as colon, pancreatic, glioblastoma, endometrial, and retinoblastoma, among others. This book is a valuable resource for researchers, students, and members of the biomedical and medical fields who want to learn more about the use of computational modeling to better tailor the treatment for cancer patients. - Discusses in silico remodeling of effective phytochemical compounds for discovering improved anticancer agents for substantial/significant cancer therapy - Covers potential tools of bioinformatics that are applied toward discovering new targets by drug repurposing and strategies to cure different types of cancers - Demonstrates the significance of computational and artificial intelligence approaches in anticancer drug discovery - Explores how these various advances can be integrated into a precision and personalized medicine approach that can eventually enhance patient care
Author:
Publisher:
ISBN:
Category : Cancer
Languages : en
Pages : 1080
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Book Description
Author: Graham A. Colditz
Publisher: SAGE
ISBN: 1412949890
Category : Medical
Languages : en
Pages : 1622
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Book Description
This encyclopedia will define the issues that surround cancer and its effects on society.
Author: Francesco L. Gervasio
Publisher: John Wiley & Sons
ISBN: 3527806857
Category : Medical
Languages : en
Pages : 420
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Book Description
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.
Author: Alessandro Laganà
Publisher: Springer Nature
ISBN: 303091836X
Category : Medical
Languages : en
Pages : 341
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Book Description
Precision medicine holds great promise for the treatment of cancer and represents a unique opportunity for accelerated development and application of novel and repurposed therapeutic approaches. Current studies and clinical trials demonstrate the benefits of genomic profiling for patients whose cancer is driven by specific, targetable alterations. However, precision oncologists continue to be challenged by the widespread heterogeneity of cancer genomes and drug responses in designing personalized treatments. Chapters provide a comprehensive overview of the computational approaches, methods, and tools that enable precision oncology, as well as related biological concepts. Covered topics include genome sequencing, the architecture of a precision oncology workflow, and introduces cutting-edge research topics in the field of precision oncology. This book is intended for computational biologists, bioinformaticians, biostatisticians and computational pathologists working in precision oncology and related fields, including cancer genomics, systems biology, and immuno-oncology.
Author: Sibhghatulla Shaikh
Publisher: Frontiers Media SA
ISBN: 2832541801
Category : Science
Languages : en
Pages : 235
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Book Description
Cancer is still a major public health concern, and it is regarded as one of the leading causes of mortality globally. Despite significant advances in biotechnologies, developing practical and innovative small molecule drugs remains a difficult, time-consuming, and expensive task that necessitates collaborations from many experts in multidisciplinary fields such as computational biology, drug metabolism, and clinical research, among others. Therefore, new drug development procedures that save time and cost while increasing efficiency are in high demand. In silico screening in combination with molecular simulations, has become an increasingly important aspect of modern drug development processes. Understanding ligand-protein interaction is critical in all areas of drug design and discovery. Computational approaches, such as molecular docking, molecular dynamics simulations, pharmacophore modeling, and QSAR, etc. are efficient tools for obtaining insights on structure-function relationships for small molecules and/or medicinal compounds with target proteins, and are widely used in the identification and optimization of leads. The goal of the drug discovery process is to predict a drug candidate's metabolic fate in order to build a link between pharmacodynamics and pharmacokinetics and to identify the drug candidate's possible toxicity. The advancement of in silico techniques in recent years has enabled researchers to collect more trustworthy data. This Research Topic will focus on the use and application of computational methods that can aid in the drug design of medicinal compounds targeting various proteins for cancer management, which is a critical requirement in the pharmaceutical sectors.
Author: Leonid Gorb
Publisher: Springer
ISBN: 9401792577
Category : Science
Languages : en
Pages : 556
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Book Description
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.
