Current Advances in Computational Strategies for Drug Discovery in Leishmaniasis PDF Download
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Author: Andrés F. Flórez
Publisher:
ISBN: 9789535102748
Category :
Languages : en
Pages :
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Book Description
Author: Andrés F. Flórez
Publisher:
ISBN: 9789535102748
Category :
Languages : en
Pages :
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Book Description
Author: Luis Rivas
Publisher: Royal Society of Chemistry
ISBN: 1788012585
Category : Science
Languages : en
Pages : 422
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Book Description
For human health, leishmaniasis is among the most important protozoan diseases, superseded only by malaria. Globally, 10 to 12 million people are infected with 1.5 million new cases every year. The development of cheaper new drugs is urgently needed for this neglected disease that is developing resistance to current treatments. Chemotherapy remains the only treatment option for the bulk of patients. However, this is largely unaffordable for most. In the past three years numerous advances in drug discovery have been made for treating this disease by exploiting diverging metabolic pathways between the Leishmania enzymes and their hosts, using nanotechnology to target the immune cell phagolysosomes where Leishmania resides. Drug Discovery for Leishmaniasis aims to provide a perspective of the current treatments and their challenges, blended with the emerging strategies and methodologies that will drive new target appraisals and drug developments, as well as addressing the molecular basis of resistance in Leishmania. Recent studies have shown that leishmaniasis affects some of the poorest people in the world, with 95% of fatal cases occurring in only 6 countries. With the WHO goal of eliminating this public health problem in the South-east Asia Region by 2020, this book will be important for anyone who is interested in neglected tropical diseases.
Author: Javier Luque
Publisher: Royal Society of Chemistry
ISBN: 1849733538
Category : Medical
Languages : en
Pages : 443
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Book Description
This title covers a wide range of topics relevant to the development of drugs. It provides a comprehensive description of the major methodological strategies available for rational drug discovery.
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:
Publisher: Academic Press
ISBN: 0128151447
Category : Medical
Languages : en
Pages : 240
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Book Description
"Neglected diseases: extensive space for modern drug discovery" provides in-depth reviews on the last progresses about neglected tropical diseases research. Topics covered in this volume include Leishmaniasis, Tripanosomiasis, Onchocerciasis and Ebolavirus infections, with insights on the future of the research on them. Part of the volume is devoted to recent contributions this field received from X-Ray crystallography. Provides accurate reviews from selected experts on the topic of Neglected Tropical Diseases Each chapter of the volume provides useful graphic material for ease of reading of the audience provides the latest insights and future perspectives on the covered neglected diseases
Author: Vasanthanathan Poongavanam
Publisher: Wiley-VCH
ISBN: 9783527351664
Category : Science
Languages : en
Pages : 0
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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:
Publisher:
ISBN: 9783527353750
Category :
Languages : en
Pages : 0
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Book Description
Author: Mukesh Samant
Publisher: Academic Press
ISBN: 0128227982
Category : Medical
Languages : en
Pages : 281
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Book Description
Leishmaniasis is a neglected tropical disease that is known to be transmitted by 90 different species of sandflies which carry 20 Leishmania species that cause human infection particularly in endemic countries. Pathogenesis, Treatment, and Prevention of Leishmaniasis aims to provide information on this vector-borne disease and explore strategies for diagnosis and treatment. The book begins with an overview of leishmaniasis which includes historical and future perspectives of the disease. It also discusses the clinical manifestation of the disease, mechanisms of infection, therapeutic strategies, diagnostics, prevention, and cure of Leishmania parasite. The book goes on to explain new insights and challenges in the development of promising drug targets, biomarkers identification and advance vaccination strategies against leishmaniasis. Chapter contributions brings together diverse areas of expertise making Pathogenesis, Treatment, and Prevention of Leishmaniasis aims to bring together elements of leishmaniasis into one place and be a valuable resource for researchers, health care professionals, and graduate students, working in the field of leishmaniasis. Provides an overview Leishmania and leishmanisis which include its history, transmission, clinical picture, and treatment Discusses novel approaches to study parasite infection and treatment Explores recent advances in the development of diagnostic kits, drug development and various vaccination strategies
Author: Mithun Rudrapal
Publisher:
ISBN: 9781003347705
Category :
Languages : en
Pages : 0
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Book Description
Author: Mithun Rudrapal
Publisher: Springer Nature
ISBN: 9819913160
Category : Science
Languages : en
Pages : 370
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Book Description
This book updates knowledge on recent advances in computational, biophysical and bioinformatics tools/techniques and their practical applications in modern drug design and discovery paradigm. It also encompasses fundamental principles, advanced methodologies and applications of various CADD approaches including several cutting-edge areas; presenting recent developments covering ongoing trends in the field of computer-aided drug discovery. Having contributions by a global team of experts, the book is expected to be an ideal resource for drug discovery scientists, medicinal chemists, pharmacologists, toxicologists, phytochemists, biochemists, biologists, R&D personnel, researchers, students, teachers and those working in the field of drug discovery. It will fill the knowledge gaps that exist in the current CADD approaches and methodologies/ protocols being widely used in both academic and research practices. Further, a special focus on current status of various computational drug design approaches (SBDD, LBDD, de novo drug design, pharmacophore-based search), bioinformatics tools and databases, computational screening and modeling of phytochemicals/natural products, artificial intelligence and machine learning, and network pharmacology and systems biology would certainly guide researchers, students or readers to conduct their research in the emerging area(s) of interest. It is also expected to be highly beneficial to various stakeholders working in the pharmaceutical and biotechnology industries (R&D), the academic as well as research sectors.
