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Drug repositioning is the process of identifying new indications for existing drugs. At present, the conventional de novo drug discovery process requires an average of about 14 years and US$2.5 billion to approve and launch a drug. Drug repositioning can reduce the time and cost of this process because it takes advantage of drugs already in clinical use for other indications or drugs that have cleared phase I safety trials but have failed to show efficacy in the intended diseases. Historically, drug repositioning has been realized through serendipitous clinical observations or improved understanding of disease mechanisms. However, recent technological advances have enabled a more systematic approach to drug repositioning. This eBook collects 16 articles from 112 authors, providing readers with current advances and future perspectives of drug repositioning.

database --- Integrative strategies --- molecular docking --- polypharmacology --- multi-omics --- computational analysis --- Drug Repositioning --- data sharing --- Patenting

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Drug repositioning is the process of identifying new indications for existing drugs. At present, the conventional de novo drug discovery process requires an average of about 14 years and US$2.5 billion to approve and launch a drug. Drug repositioning can reduce the time and cost of this process because it takes advantage of drugs already in clinical use for other indications or drugs that have cleared phase I safety trials but have failed to show efficacy in the intended diseases. Historically, drug repositioning has been realized through serendipitous clinical observations or improved understanding of disease mechanisms. However, recent technological advances have enabled a more systematic approach to drug repositioning. This eBook collects 16 articles from 112 authors, providing readers with current advances and future perspectives of drug repositioning.

database --- Integrative strategies --- molecular docking --- polypharmacology --- multi-omics --- computational analysis --- Drug Repositioning --- data sharing --- Patenting

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"Drug development can be time-consuming and expensive. Recent estimates suggest that, on average, it takes 10 years and at least $1 billion to bring a drug to market. Given the time and expense of developing drugs de novo, pharmaceutical companies have become increasingly interested in finding new uses for existing drugs--a process referred to as drug repurposing or repositioning. Historically, drug repurposing has been largely an unintentional, serendipitous process that took place when a drug was found to have an offtarget effect or a previously unrecognized on-target effect that could be used for identifying a new indication. Perhaps the most recognizable example of such a successful repositioning effort is sildenafil. Originally developed as an anti-hypertensive, sildenafil, marketed as Viagra and under other trade names, has been repurposed for the treatment of erectile dysfunction and pulmonary arterial hypertension. Viagra generated more than $2 billion worldwide in 2012 and has recently been studied for the treatment of heart failure. Given the widespread interest in drug repurposing, the Roundtable on Translating Genomic-Based Research for Health of the Institute of Medicine hosted a workshop on June 24, 2013, in Washington, DC, to assess the current landscape of drug repurposing activities in industry, academia, and government. Stakeholders, including government officials, pharmaceutical company representatives, academic researchers, regulators, funders, and patients, were invited to present their perspectives and to participate in workshop discussions. Drug Repurposing and Repositioning is the summary of that workshop. This report examines enabling tools and technology for drug repurposing; evaluates the business models and economic incentives for pursuing a repurposing approach; and discusses how genomic and genetic research could be positioned to better enable a drug repurposing paradigm"--Publisher's description. --

Drug Discovery -- Methods. --- Drug development --- Drugs --- Pharmaceutical industry --- Chemicals and Drugs --- Drug Prescriptions --- Investigative Techniques --- North America --- Social Sciences --- Chemistry, Pharmaceutical --- Publication Formats --- Publication Characteristics --- Anthropology, Education, Sociology and Social Phenomena --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Chemistry --- Drug Therapy --- Pharmacology --- Americas --- Prescriptions --- Natural Science Disciplines --- Geographic Locations --- Biological Science Disciplines --- Pharmaceutical Services --- Therapeutics --- Disciplines and Occupations --- Geographicals --- Health Services --- Health Care Facilities, Manpower, and Services --- Health Care --- Congresses --- Pharmaceutical Preparations --- United States --- Drug Repositioning --- Economics --- Drug Discovery --- Methods --- Health & Biological Sciences --- Pharmacy, Therapeutics, & Pharmacology --- Design --- Economic aspects --- United States.

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This book is a collection of original research articles in the field of computer-aided drug design. It reports the use of current and validated computational approaches applied to drug discovery as well as the development of new computational tools to identify new and more potent drugs.

Research & information: general --- Chemistry --- 3D-QSAR --- pharmacophore modeling --- ligand-based model --- HDACs --- isoform-selective histone deacetylase inhibitors --- aminophenylbenzamide --- hERG toxicity --- drug discovery --- fingerprints --- machine learning --- deep learning --- gene expression signature --- drug repositioning approaches --- RNA expression regulation --- high-throughput virtual screening --- dual-target lead discovery --- neurodegenerative disorders --- Alzheimer’s disease --- dual mode of action --- multi-modal --- nicotinic acetylcholine receptor --- acetylcholinesterase --- molecular docking --- methotrexate --- drug resistance --- human dihydrofolate reductase --- virtual screening --- molecular dynamics simulation. --- epitope binning --- epitope mapping --- epitope prediction --- antibody:antigen interactions --- protein docking --- glycoprotein D (gD) --- herpes simplex virus fusion proteins --- Src inhibitors --- pharmacophore model --- molecular dynamics simulations --- in silico --- COX-2 inhibitors --- molecular modeling --- sodium–glucose co-transporters 2 --- FimH --- uropathogenic bacteria --- urinary tract infections --- diabetes --- drug-resistance mutations --- HIV-2 protease --- structural characterization --- induced structural deformations --- SARS-CoV-2 --- COVID-19 --- multiprotein inhibiting natural compounds --- MD simulation --- 3CL-Pro --- antivirals --- docking simulations --- drug repurposing --- consensus models --- binding space --- isomeric space --- MRP4 --- SNPs --- variants --- protein threading modeling --- molecular dynamics --- binding site --- hTSPO --- PK11195 --- cholesterol --- homology modeling --- molecular dynamics (MD) simulation --- carbon nanotubes --- Stone–Wales defects --- haeckelite defects --- doxorubicin encapsulation --- drug delivery system --- binding free energies --- noncovalent interactions --- main protease --- mutants --- inhibitors --- PF-00835231 --- Mycobacterium tuberculosis --- tuberculosis --- proteasome --- natural compounds --- multiscale --- multitargeting --- polypharmacology --- computational biology --- drug repositioning --- structural bioinformatics --- proteomic signature --- skin aging --- oxidative stress --- aging progression mechanism --- genome-wide genetic and epigenetic network (GWGEN) --- systems medicine design --- multiple-molecule drug --- immunoproteasome --- non-covalent inhibitors --- MD binding --- metadynamics --- induced-fit docking --- n/a --- Alzheimer's disease --- sodium-glucose co-transporters 2 --- Stone-Wales defects

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• Reference Manager
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This book is a collection of original research articles in the field of computer-aided drug design. It reports the use of current and validated computational approaches applied to drug discovery as well as the development of new computational tools to identify new and more potent drugs.

Research & information: general --- Chemistry --- 3D-QSAR --- pharmacophore modeling --- ligand-based model --- HDACs --- isoform-selective histone deacetylase inhibitors --- aminophenylbenzamide --- hERG toxicity --- drug discovery --- fingerprints --- machine learning --- deep learning --- gene expression signature --- drug repositioning approaches --- RNA expression regulation --- high-throughput virtual screening --- dual-target lead discovery --- neurodegenerative disorders --- Alzheimer's disease --- dual mode of action --- multi-modal --- nicotinic acetylcholine receptor --- acetylcholinesterase --- molecular docking --- methotrexate --- drug resistance --- human dihydrofolate reductase --- virtual screening --- molecular dynamics simulation. --- epitope binning --- epitope mapping --- epitope prediction --- antibody:antigen interactions --- protein docking --- glycoprotein D (gD) --- herpes simplex virus fusion proteins --- Src inhibitors --- pharmacophore model --- molecular dynamics simulations --- in silico --- COX-2 inhibitors --- molecular modeling --- sodium-glucose co-transporters 2 --- FimH --- uropathogenic bacteria --- urinary tract infections --- diabetes --- drug-resistance mutations --- HIV-2 protease --- structural characterization --- induced structural deformations --- SARS-CoV-2 --- COVID-19 --- multiprotein inhibiting natural compounds --- MD simulation --- 3CL-Pro --- antivirals --- docking simulations --- drug repurposing --- consensus models --- binding space --- isomeric space --- MRP4 --- SNPs --- variants --- protein threading modeling --- molecular dynamics --- binding site --- hTSPO --- PK11195 --- cholesterol --- homology modeling --- molecular dynamics (MD) simulation --- carbon nanotubes --- Stone-Wales defects --- haeckelite defects --- doxorubicin encapsulation --- drug delivery system --- binding free energies --- noncovalent interactions --- main protease --- mutants --- inhibitors --- PF-00835231 --- Mycobacterium tuberculosis --- tuberculosis --- proteasome --- natural compounds --- multiscale --- multitargeting --- polypharmacology --- computational biology --- drug repositioning --- structural bioinformatics --- proteomic signature --- skin aging --- oxidative stress --- aging progression mechanism --- genome-wide genetic and epigenetic network (GWGEN) --- systems medicine design --- multiple-molecule drug --- immunoproteasome --- non-covalent inhibitors --- MD binding --- metadynamics --- induced-fit docking