In Silico Approaches in Drug Design

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 cruci...

Olles dieđut

Furkejuvvon:

Bibliográfalaš dieđut
Materiálatiipa:	Online
Giella:	eaŋgalasgiella
Almmustuhtton:	MDPI - Multidisciplinary Digital Publishing Institute 2022
Fáttát:	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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PN Chemistry
Liŋkkat:	ONIX_20221117_9783036553832_80
Fáddágilkorat:	Lasit fáddágilkoriid Eai fáddágilkorat, Lasit vuosttaš fáddágilkora!

Govvádus
Čoahkkáigeassu:	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.

In Silico Approaches in Drug Design

Geahča maid