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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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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.

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