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Molecular Modeling in Drug Design

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ISBN: 9783038976141 Year: Pages: 220 DOI: 10.3390/books978-3-03897-615-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Chemistry (General) --- Science (General)
Added to DOAB on : 2019-04-05 10:34:31
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Abstract

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

Keywords

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

Research of Pathogenesis and Novel Therapeutics in Arthritis

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ISBN: 9783038970651 / 9783038970668 Year: Pages: 366 DOI: 10.3390/books978-3-03897-066-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Medicine (General) --- Therapeutics
Added to DOAB on : 2019-06-26 08:44:06
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Abstract

Arthritis has a high prevalence globally and includes over 100 different types, the most common of which are rheumatoid arthritis, osteoarthritis, psoriatic arthritis, and inflammatory arthritis. The exact etiology of arthritis remains unclear and no cure exists. Anti-inflammatory drugs are commonly used in the treatment of arthritis but are associated with significant side effects. Novel modes of therapy and additional prognostic biomarkers are urgently needed for arthritis patients. This book summarizes and discusses the global picture of the current understanding of arthritis.

Keywords

biosimilars --- Th9 lymphocytes --- rheumatoid arthritis --- infliximab --- rheumatoid arthritis --- bone erosion --- osteoblasts --- next-generation sequencing --- bioinformatics --- microRNA --- messenger RNA --- osteoarthritis --- cell signaling --- IL1? --- WNT --- antagonists --- computational modeling --- nitric oxide --- clodronate --- gene expression --- osteoarthritis --- progenitor cells --- SOX9 --- spondyloarthropathies --- inflammation --- mesenchymal stem cells --- visfatin --- IL-6 --- TNF-? --- osteoarthritis --- miR-199a-5p --- Epstein-Barr virus --- glycoprotein 42 --- rheumatoid arthritis --- shared epitope --- triptolide --- rheumatoid arthritis --- basic research --- clinical translation --- osteoarthritis (OA) --- articular cartilage --- molecular pathology --- therapeutics --- rheumatoid arthritis --- antibodies --- collagen --- glycosylation --- disease pathways --- therapy --- experimental arthritis --- TNF? --- etanercept --- infliximab --- adalimumab --- certolizumab pegol --- golimumab --- rheumatoid arthritis --- therapeutic antibody --- structure --- fraxinellone --- collagen-induced arthritis --- rheumatoid arthritis --- inflammatory arthritis --- osteoclastogenesis --- sclareol --- rheumatoid arthritis --- synovial cell --- collagen --- mice --- cytokines --- Th17 --- MAPK --- arthritis --- osteoarthritis --- rheumatoid arthritis --- small-molecule inhibitor --- chondrocytes --- tumor necrosis factor-alpha --- inflammation --- rheumatoid arthritis --- osteoarthritis --- angiogenesis --- cytokines --- chemokines --- early osteoarthritis --- articular cartilage --- proliferation --- fibroblast growth factor 2 --- mitogen activated protein kinase --- transforming growth factor ? --- SMA- and MAD-related protein --- interleukin --- nuclear factor kappa B --- miRNA --- adjuvant arthritis --- arthritis --- biomarkers --- celastrol --- inflammation --- microRNA --- miRNA --- rat --- rheumatoid arthritis --- Traditional Chinese medicine --- tripterine --- triterpenoid --- spinal fusion --- biological --- osteoblast --- osteoclast --- bisphosphonate --- parathyroid hormone --- bone morphogenetic protein --- receptor activator of nuclear factor ?B --- stem cell --- drug delivery system --- anticitrullinated peptide antibodies --- antirheumatic drug --- autoimmune --- disease-modifying --- immunology --- pathology --- rheumatoid factor --- rheumatoid arthritis --- osteoarthritis --- adipokines --- obesity --- rheumatoid arthritis --- osteoarthritis --- anti-arthritis --- biomarkers

Qualitative and Quantitative Analysis of Bioactive Natural Products 2018

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ISBN: 9783038977889 Year: Pages: 374 DOI: 10.3390/books978-3-03897-789-6 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Biology --- Science (General)
Added to DOAB on : 2019-04-05 10:34:31
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Throughout most of history, medicinal plants and their active metabolites have represented a valuable source of compounds used to prevent and to cure several diseases. Interest in natural compounds is still high as they represent a source of novel biologically/pharmacologically active compounds. Due to their high structural diversity and complexity, they are interesting structural scaffolds that can offer promising candidates for the study of new drugs, functional foods, and food additives.Plant extracts are a highly complex mixture of compounds and qualitative and quantitative analyses are necessary to ensure their quality. Furthermore, greener methods of extraction and analysis are needed today.This book is based on articles submitted for publication in the Special Issue entitled “Qualitative and Quantitative Analysis of Bioactive Natural Products” that collected original research and reviews on these topics.

Keywords

Talaromyces pinophilus --- talarodiolide --- macrodiolides --- GC/MS --- secondary metabolites --- anthocyanins --- red cabbage --- recycling preparative high performance liquid chromatography --- stability --- UHPLC-MS/MS --- decursin --- decursinol angelate --- nodakenin --- decursinol --- Ginkgo biloba Extract (GBE) --- chromatogram-bioactivity correlation --- bioactive compounds --- endothelial function --- wine --- volatile compounds --- terrain conditions --- odor-activity values --- SPME-GC/MS --- Bolbostemma paniculatum --- identification --- LTQ-Orbitrap --- UPLC --- multivariate statistical analysis --- cannabidiol --- CBD oil --- terpenes --- hemp seed oil --- GC-MS --- HPLC-Q-Exactive-Orbitrap-MS --- Rossa da inverno sel. Rojo Duro onion cultivar --- geographical origin --- amino acids content --- HPLC analysis --- statistical evaluations --- food traceability --- aleuritolic acid --- autophagy --- apoptosis --- HPLC --- Curcuma longa --- turmeric --- curcuminoids --- turmerone --- quantification --- Quercus acuta leaf --- antioxidant --- antibacterial activity --- Staphylococcus aureus --- Erigeron breviscapus extract --- UPLC-ESI-MS/MS --- cerebral ischemia reperfusion injury --- scutellarin --- scutellarein --- HPLC --- Podospermum --- Scorzonera --- triterpenes --- ginseng berry extract --- ginsenosides --- stereoselective and simultaneous analysis --- pharmacokinetics --- oral administration --- saffron --- crocins --- UHPLC analysis --- separation optimisation --- artificial neural network --- response surface methodology --- bioactive natural compounds --- secondary metabolites --- Alzheimer’s disease --- Olea europaea L. --- liquid chromatography --- gas chromatography --- mass spectrometry --- secondary metabolites --- olive leaves --- Moroccan region --- phenolic compounds --- liquid chromatography-mass spectrometry --- chemometrics --- metabolic profiling --- Sorbus --- fruit powders --- phenolic compounds --- carotenoids --- sugars --- organic acids --- chili --- capsaicinoids --- phenolics --- free radical-scavenging --- geographical variation --- 1-triacontanol --- HPLC-ELSD --- biostimulant --- method validation --- Myristica fragrans --- nutmeg --- essential oil --- ionic liquids --- hydrodistillation --- MODDE experimental design --- rice --- phenolic compounds --- phenolic acids --- flavonoids --- anthocyanins --- proanthocyanidins --- antioxidant activity --- extraction --- HPLC methods --- phenolic compounds --- Spondias spp. --- UPLC-MS --- antioxidant capacity --- Iris lactea Pall. var. chinensis (Fisch.) Koidz. --- HPLC-Q-TOF-MS/MS --- qualitative analysis --- quantitative analysis --- C-glycosylflavone --- traditional Chinese medicine decoction --- quality evaluation --- UPLC-QTOF-MS --- UFLC-QQQ-MS --- ShenFu prescription decoction

Application of Bioinformatics in Cancers

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ISBN: 9783039217885 / 9783039217892 Year: Pages: 418 DOI: 10.3390/books978-3-03921-789-2 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Biotechnology
Added to DOAB on : 2019-12-09 11:49:16
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Abstract

This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible.

Keywords

comorbidity score --- mortality --- locoregionally advanced --- HNSCC --- curative surgery --- traditional Chinese medicine --- health strengthening herb --- cancer treatment --- network pharmacology --- network target --- high-throughput analysis --- brain metastases --- colorectal cancer --- KRAS mutation --- PD-L1 --- tumor infiltrating lymphocytes --- drug resistance --- gefitinib --- erlotinib --- biostatistics --- bioinformatics --- Bufadienolide-like chemicals --- molecular mechanism --- anti-cancer --- bioinformatics --- cancer --- brain --- pathophysiology --- imaging --- machine learning --- extreme learning --- deep learning --- neurological disorders --- pancreatic cancer --- TCGA --- curation --- DNA --- RNA --- protein --- single-biomarkers --- multiple-biomarkers --- cancer-related pathways --- colorectal cancer --- DNA sequence profile --- Monte Carlo --- mixture of normal distributions --- somatic mutation --- tumor --- mutable motif --- activation induced deaminase --- AID/APOBEC --- transcriptional signatures --- copy number variation --- copy number aberration --- TCGA mining --- cancer CRISPR --- firehose --- gene signature extraction --- gene loss biomarkers --- gene inactivation biomarkers --- biomarker discovery --- chemotherapy --- microarray --- ovarian cancer --- predictive model --- machine learning --- overall survival --- observed survival interval --- skin cutaneous melanoma --- The Cancer Genome Atlas --- omics --- breast cancer prognosis --- artificial intelligence --- machine learning --- decision support systems --- cancer prognosis --- independent prognostic power --- omics profiles --- histopathological imaging features --- cancer --- intratumor heterogeneity --- genomic instability --- epigenetics --- mitochondrial metabolism --- miRNAs --- cancer biomarkers --- breast cancer detection --- machine learning --- feature selection --- classification --- denoising autoencoders --- breast cancer --- feature extraction and interpretation --- concatenated deep feature --- cancer modeling --- interaction --- histopathological imaging --- clinical/environmental factors --- oral cancer --- miRNA --- bioinformatics --- datasets --- biomarkers --- TCGA --- GEO DataSets --- hormone sensitive cancers --- breast cancer --- StAR --- estrogen --- steroidogenic enzymes --- hTERT --- telomerase --- telomeres --- alternative splicing --- network analysis --- hierarchical clustering analysis --- differential gene expression analysis --- cancer biomarker --- diseases genes --- variable selection --- false discovery rate --- knockoffs --- bioinformatics --- copy number variation --- cell-free DNA --- methylation --- mutation --- next generation sequencing --- self-organizing map --- head and neck cancer --- treatment de-escalation --- HP --- molecular subtypes --- tumor microenvironment --- Bioinformatics tool --- R package --- machine learning --- meta-analysis --- biomarker signature --- gene expression analysis --- survival analysis --- functional analysis --- bioinformatics --- machine learning --- artificial intelligence --- Network Analysis --- single-cell sequencing --- circulating tumor DNA (ctDNA) --- Neoantigen Prediction --- precision medicine --- Computational Immunology

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MDPI - Multidisciplinary Digital Publishing Institute (4)


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CC by-nc-nd (4)


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eng (4)


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2019 (4)