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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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The discovery of new drugs is one of pharmaceutical research's most exciting and challenging tasks. Unfortunately, the conventional drug discovery procedure is chronophagous and seldom successful; furthermore, new drugs are needed to address our clinical challenges (e.g., new antibiotics, new anticancer drugs, new antivirals).Within this framework, drug repositioning—finding new pharmacodynamic properties for already approved drugs—becomes a worthy drug discovery strategy.Recent drug discovery techniques combine traditional tools with in silico strategies to identify previously unaccounted properties for drugs already in use. Indeed, big data exploration techniques capitalize on the ever-growing knowledge of drugs' structural and physicochemical properties, drug–target and drug–drug interactions, advances in human biochemistry, and the latest molecular and cellular biology discoveries.Following this new and exciting trend, this book is a collection of papers introducing innovative computational methods to identify potential candidates for drug repositioning. Thus, the papers in the Special Issue In Silico Strategies for Prospective Drug Repositionings introduce a wide array of in silico strategies such as complex network analysis, big data, machine learning, molecular docking, molecular dynamics simulation, and QSAR; these strategies target diverse diseases and medical conditions: COVID-19 and post-COVID-19 pulmonary fibrosis, non-small lung cancer, multiple sclerosis, toxoplasmosis, psychiatric disorders, or skin conditions.

Medicine --- Pharmaceutical industries --- COVID-19 --- drug repurposing --- topological data analysis --- persistent Betti function --- SARS-CoV-2 --- network-based pharmacology --- combination therapy --- nucleoside GS-441524 --- fluoxetine --- synergy --- antidepressant --- natural compounds --- QSAR --- molecular docking --- drug repositioning --- UK Biobank --- vaccine --- LC-2/ad cell line --- drug discovery --- docking --- MM-GBSA calculation --- molecular dynamics --- cytotoxicity assay --- GWAS --- multiple sclerosis --- oxidative stress --- repurposing --- ADME-Tox --- bioinformatics --- complex network analysis --- modularity clustering --- ATC code --- hidradenitis suppurativa --- acne inversa --- transcriptome --- proteome --- comorbid disorder --- biomarker --- signaling pathway --- druggable gene --- drug-repositioning --- MEK inhibitor --- MM/GBSA --- Glide docking --- MD simulation --- MM/PBSA --- single-cell RNA sequencing --- pulmonary fibrosis --- biological networks --- p38α MAPK --- allosteric inhibitors --- in silico screening --- computer-aided drug discovery --- network analysis --- psychiatric disorders --- medications --- psychiatry --- mental disorders --- toxoplasmosis --- Toxoplasma gondii --- in vitro screening --- drug targets --- drug-disease interaction --- target-disease interaction --- DPP4 inhibitors --- lipid rafts

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This book describes the recent advances in natural product chemistry and biodiversity in the Red Sea. All previous marine natural products isolated from different Red Sea organisms and microbes were collected in a comprehensive review. Additionally, newly discovered marine natural products and their biological activities are described.

Aspergillus falconensis --- OSMAC --- azaphilones --- X-ray diffraction --- NF-κB inhibition --- LC-HRESIMS --- Stylissa carteri --- ceramide --- cerebroside --- docking --- cytotoxic activity --- co-cultivation --- phenazine --- sponge-associated actinomycetes --- antibacterial --- antibiofilm --- DNA gyrase --- pyruvate kinase --- ergosterol derivative --- metabolic analysis --- docking studies --- seagrass --- Thalassodendron ciliatum --- Red Sea sponges --- marine actinomycetes --- Streptomyces coelicolor LY001 --- halogenated 3-phenylpropanoic acid derivatives --- diketopiperazine alkaloids --- structural determinations --- antimicrobial activities --- Red Sea --- marine natural products --- marine organisms --- biodiversity --- marine metagenomics --- bioactivity --- Sinularia polydactyla --- soft coral --- steroids --- cytotoxic --- anti-inflammatory --- neuroprotective --- androgen receptor --- Actinokineospora --- Rhodococcus --- co-culture --- metabolomics --- antimalarial --- epicotripeptin --- phragamide --- Epicoccum --- Alternaria --- antimicrobial --- n/a

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Protein–ligand interactions play a fundamental role in most major biological functions. The number and diversity of small molecules that interact with proteins, whether naturally or not, can quickly become overwhelming. They are as essential as amino acids, nucleic acids or membrane lipids, enabling a large number of essential functions. One need only think of carbohydrates or even just ATP to be certain. They are also essential in drug discovery. With the increasing structural information of proteins and protein–ligand complexes, molecular modelling, molecular dynamics, and chemoinformatics approaches are often required for the efficient analysis of a large number of such complexes and to provide insights. Similarly, numerous computational approaches have been developed to characterize and use the knowledge of such interactions, which can lead to drug candidates. "Recent Developments on Protein–Ligand Interactions: From Structure, Function to Applications" was dedicated to the different aspect of protein–ligand analysis and/or prediction using computational approaches, as well as new developments dedicated to these tasks. It will interest both specialists and non-specialists, as the presented studies cover a very large spectra in terms of methodologies and applications. It underlined the variety of scientific area linked to these questions, i.e., chemistry, biology, physics, informatics, bioinformatics, structural bioinformatics and chemoinformatics.

pimaricin thioesterase --- protein-substrate interaction --- macrocyclization --- molecular dynamics (MD) simulation --- pre-reaction state --- folate --- folate receptor --- peptide conjugation --- click reaction --- biolayer interferometry --- acetylcholinesterase --- resistance --- organophosphorus --- pesticides --- molecular modeling --- lepidopterous --- insects --- conserved patterns --- similarity --- 3D-patterns --- epigenetics --- protein-RNA interaction --- RRM domain inhibitor --- NMR fragment-based screening --- TDP-43 --- galectin-1 --- gulopyranosides --- fluorescence polarization --- benzamide --- selective --- phospholipase C gamma 1 --- SLP76 --- virtual screening --- pharmacophore mapping --- molecular docking --- molecular dynamics --- caspase inhibition --- protein-ligand binding free energy --- Monte Carlo sampling --- docking and scoring --- molecular conformational sampling --- procollagen C-proteinase enhancer-1 --- glycosaminoglycans --- computational analysis of protein-glycosaminoglycan interactions --- calcium ions --- fragment-based docking --- protein–ligand analysis --- drug discovery and design --- structure–activity relationships --- bioremediation --- High Energy Molecules --- HMX --- protein design --- nitroreductase --- flavoprotein --- substrate specificity --- pharmacophore --- secretoglobin --- odorant-binding protein --- chemical communication --- pheromone --- N-phenyl-1-naphthylamine --- in silico docking --- protein–ligand interactions --- 2D interaction maps --- ligand-binding assays --- protein-ligand complexes --- dataset --- clustering --- structural alignment --- refinement --- PD-1/PD-L1 --- immune checkpoint inhibitors --- biphenyl-conjugated bromotyrosine --- amino acid conjugation --- amino-X --- in silico simulation --- IC50

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This book is a printed edition of the Special Issue Molecular Modeling in Drug Design that was published in Molecules

metadynamics --- natural compounds --- virtual screening --- probe energies --- molecular dynamics simulation --- human ecto-5?-nucleotidase --- neural networks --- quantitative structure-activity relationship (QSAR) --- artificial intelligence --- allosterism --- in silico screening --- drug discovery --- amyloid fibrils --- mechanical stability --- adenosine receptors --- adenosine receptor --- ligand binding --- promiscuous mechanism --- AutoGrid --- dynamic light scattering --- resultant dipole moment --- density-based clustering --- Alzheimer’s disease --- drug design --- biophenols --- enzymatic assays --- all-atom molecular dynamics simulation --- fragment screening --- adenosine --- docking --- molecular docking --- cosolvent molecular dynamics --- turbidimetry --- squalene synthase (SQS) --- molecular recognition --- protein-peptide interactions --- extracellular loops --- FimH --- binding affinity --- rational drug design --- de novo design --- hyperlipidemia --- AR ligands --- aggregation --- property prediction --- PPI inhibition --- deep learning --- proteins --- quantitative structure-property prediction (QSPR) --- protein protein interactions --- boron cluster --- target-focused pharmacophore modeling --- ligand–protofiber interactions --- structure-based drug design --- scoring function --- grid maps --- solvent effect --- adhesion --- molecular dynamics --- Traditional Chinese Medicine --- steered molecular dynamics --- interaction energy --- EphA2-ephrin A1 --- molecular modeling --- method development