In Silico Approaches in Drug Design

• Muut tekijät: Santos-Filho, Osvaldo (Toimittaja)
• Aineistotyyppi: Elektroninen Kirjan osa
• Kieli: englanti
• Julkaistu: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
• Aiheet: Research & information: general; Chemistry; T-type calcium channel blocker; homology modeling; computer-aid drug design; virtual drug screening; L-type calcium channel; mTOR kinase; marine natural products; ATP-competitive inhibitors; structure-based pharmacophore modeling; virtual screening; molecular docking; molecular dynamics simulations; binding free energy; in silico ADMET; α-Glucosidase; QSAR modeling; ADMET profiling; cervical cancer management; computer-aided drug design; E6 inhibitors; in silico studies; human papillomavirus; manifold learning; machine learning; rdkit; embeddings; Tox21; principal component analysis; autoencoder; skin sensitization; toxicity prediction; in silico prediction; random forest; conformal prediction; bioactivity descriptors; SARS coronavirus; SARS-CoV-2 main protease; structure-based virtual screening; molecular dynamic simulation; hit identification; Alzheimer's disease; multitarget; natural-like compounds; library of integrated network-based cellular signatures (LINCS); longevity; gene regulating effects; gene descriptors; molecular fingerprints; deep neural network; drug repurposing; Variola virus; thymidylate kinase; smallpox; docking; molecular dynamics; molecular modeling; permeability; membrane disruption; membrane proteins; drugs; antimicrobial peptides; Ras; RasGRF1; hydrogen-bond surrogate; computational residue scanning; MM-GBSA; protein-protein interaction; ERK signalling; cocaine addiction; intellectual disability (ID); autism spectrum disorder (ASD); gated recurrent unit; recurrent neural network; transfer learning; caspase-6; inhibitor; molecular design; computational drug design; deep learning; multiscale; polypharmacology; Mycobacterium tuberculosis; mycolic acid methyltransferases; fragment-based ligand discovery; binding energies; molecular modelling; heat shock protein; HSP70; nucleotide-binding domain; piperlongumine; fluorescence spectroscopy; circular dichroism; molecular mechanics Poisson-Boltzmann surface area; Parkinson's disease; catechol-O-methyltransferase; inhibitors; bioinformatics; pharmacophore modeling; cytotoxicity; computational drug discovery; chemical space; parallelization; high-performance computers and accelerators; sulfonamides; arylsulfonamide; anticancer compounds; telomerase inhibitors; structure-based drug design; computer drug design; MolAr; DNA intercalating agents; SARS-CoV-2; main protease, Mpro; docking benchmark; non-steroidal anti-inflammatory drugs; drug discovery; lipoxygenase; cyclooxygenase; Hsp90; cancer; QSAR; pharmacophores; in-silico drug design; AlphaFold; anti-CRISPR proteins; prokaryotic defence mechanisms; bacteriophages; structural biology; protein drug; Merkel cell polyomavirus; Merkel cell carcinomas; drug design; ADMET; MD simulation; antimicrobial peptide database; antiviral peptides; database filtering technology; Ebola virus; peptide design; G-quadruplex DNA; TERRA; mass spectrometry; biological assays; mangrove natural products; KRASG12C; ligand-based pharmacophore modeling; computational biology; RVFV; RdRp; structural modeling; GlyT1; schizophrenia; DAT; MD; chagas; leishmaniasis; naphthoquinones; antiprotozoal evaluation; ADME; COVID-19; NSP3; TCM; MD simulations; mutagenesis; artificial intelligence; biased signaling; G protein-coupled receptor; immunology; flavonoids; IDO1; free energy
• Linkit: DOAB: download the publication; DOAB: description of the publication

Yhteenveto

This reprint is a collection of 31 original papers and four reviews, published from 2021 to 2022, focused on the application of a wide range of computational tools in medicinal chemistry projects: from molecular docking to artificial intelligence approaches. Applications of in silico tools are crucial in the early stages of drug design, such as planning more efficient and economic synthetic routes for chemical administration, screening of huge databases, as well as proposing hypotheses for probable mechanisms of action of drugs in macromolecular targets. Such endeavors are extremely complex and require the usage of modern and sophisticated approaches, such as artificial intelligence, data mining, computational molecular simulations through classical mechanics and quantum mechanics, molecular docking, chemoinformatics, applied mathematics, and biostatistics.

Ulkoasu

1 electronic resource (754 p.)

ISBN

books978-3-0365-5383-2
9783036553832
9783036553849

Pääsy

Open Access