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07564namaa2202509ui 4500 |
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20221228154815.0 |
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DE-2553 |
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m o d |
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cr|mn|---annan |
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20221117s2022 xx |||||o ||| 0|eng d |
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|a books978-3-0365-5383-2
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|a 9783036553832
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|a 9783036553849
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|a oapen
|c oapen
|b eng
|d DE-2553
|e rda
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| 024 |
7 |
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|a 10.3390/books978-3-0365-5383-2
|c doi
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| 041 |
0 |
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|a eng
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| 042 |
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|a dc
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| 072 |
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7 |
|a GP
|2 bicssc
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| 072 |
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7 |
|a PN
|2 bicssc
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| 100 |
1 |
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|a Santos-Filho, Osvaldo
|e editor
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| 264 |
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|b MDPI - Multidisciplinary Digital Publishing Institute,
|c 2022.
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| 700 |
1 |
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|a Santos-Filho, Osvaldo
|e other
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| 245 |
1 |
0 |
|a In Silico Approaches in Drug Design
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| 300 |
|
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|a 1 online resource (754 pages).
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 506 |
0 |
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|a Open Access
|2 star
|f Unrestricted online access
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| 540 |
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|a Creative Commons
|f https://creativecommons.org/licenses/by/4.0/
|2 cc
|4 https://creativecommons.org/licenses/by/4.0/
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| 546 |
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|a English
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| 650 |
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7 |
|a Research & information: general
|2 bicssc
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| 650 |
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7 |
|a Chemistry
|2 bicssc
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| 653 |
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|a T-type calcium channel blocker
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| 653 |
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|a homology modeling
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| 653 |
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|a computer-aid drug design
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| 653 |
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|a virtual drug screening
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| 653 |
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|a L-type calcium channel
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| 653 |
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|a mTOR kinase
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| 653 |
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|a marine natural products
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| 653 |
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|a ATP-competitive inhibitors
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| 653 |
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|a structure-based pharmacophore modeling
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| 653 |
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|a virtual screening
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| 653 |
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|a molecular docking
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| 653 |
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|a molecular dynamics simulations
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| 653 |
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|a binding free energy
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| 653 |
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|a in silico ADMET
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| 653 |
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|a α-Glucosidase
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| 653 |
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|a QSAR modeling
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| 653 |
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|a ADMET profiling
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| 653 |
|
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|a cervical cancer management
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| 653 |
|
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|a computer-aided drug design
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| 653 |
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|a E6 inhibitors
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| 653 |
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|a in silico studies
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| 653 |
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|a human papillomavirus
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| 653 |
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|a manifold learning
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| 653 |
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|a machine learning
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| 653 |
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|a rdkit
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| 653 |
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|a embeddings
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| 653 |
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|a Tox21
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| 653 |
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|a principal component analysis
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| 653 |
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|a autoencoder
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| 653 |
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|a skin sensitization
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| 653 |
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|a toxicity prediction
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| 653 |
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|a in silico prediction
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| 653 |
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|a random forest
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| 653 |
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|a conformal prediction
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| 653 |
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|a bioactivity descriptors
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| 653 |
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|a SARS coronavirus
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| 653 |
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|a SARS-CoV-2 main protease
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| 653 |
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|a structure-based virtual screening
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| 653 |
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|a molecular dynamic simulation
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| 653 |
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|a hit identification
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| 653 |
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|a Alzheimer's disease
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| 653 |
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|a multitarget
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| 653 |
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|a natural-like compounds
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| 653 |
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|a library of integrated network-based cellular signatures (LINCS)
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| 653 |
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|a longevity
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| 653 |
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|a gene regulating effects
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| 653 |
|
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|a gene descriptors
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| 653 |
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|a molecular fingerprints
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| 653 |
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|a deep neural network
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| 653 |
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|a drug repurposing
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| 653 |
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|a Variola virus
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| 653 |
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|a thymidylate kinase
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| 653 |
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|a smallpox
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| 653 |
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|a docking
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| 653 |
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|a molecular dynamics
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| 653 |
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|a molecular modeling
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| 653 |
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|a permeability
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| 653 |
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|a membrane disruption
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| 653 |
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|a membrane proteins
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| 653 |
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|a drugs
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| 653 |
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|a antimicrobial peptides
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| 653 |
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|a Ras
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| 653 |
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|a RasGRF1
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| 653 |
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|a hydrogen-bond surrogate
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| 653 |
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|a computational residue scanning
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| 653 |
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|a MM-GBSA
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| 653 |
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|a protein-protein interaction
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| 653 |
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|a ERK signalling
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| 653 |
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|a cocaine addiction
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| 653 |
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|a intellectual disability (ID)
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| 653 |
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|a autism spectrum disorder (ASD)
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| 653 |
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|a gated recurrent unit
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| 653 |
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|a recurrent neural network
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| 653 |
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|a transfer learning
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| 653 |
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|a caspase-6
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| 653 |
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|a inhibitor
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| 653 |
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|a molecular design
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| 653 |
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|a computational drug design
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| 653 |
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|a deep learning
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| 653 |
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|a multiscale
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| 653 |
|
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|a polypharmacology
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| 653 |
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|a Mycobacterium tuberculosis
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| 653 |
|
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|a mycolic acid methyltransferases
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| 653 |
|
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|a fragment-based ligand discovery
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| 653 |
|
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|a binding energies
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| 653 |
|
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|a molecular modelling
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| 653 |
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|a heat shock protein
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| 653 |
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|a HSP70
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| 653 |
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|a nucleotide-binding domain
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| 653 |
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|a piperlongumine
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| 653 |
|
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|a fluorescence spectroscopy
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| 653 |
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|a circular dichroism
|
| 653 |
|
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|a molecular mechanics Poisson-Boltzmann surface area
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| 653 |
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|a Parkinson's disease
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| 653 |
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|a catechol-O-methyltransferase
|
| 653 |
|
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|a inhibitors
|
| 653 |
|
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|a bioinformatics
|
| 653 |
|
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|a pharmacophore modeling
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| 653 |
|
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|a cytotoxicity
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| 653 |
|
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|a computational drug discovery
|
| 653 |
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|a chemical space
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| 653 |
|
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|a parallelization
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| 653 |
|
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|a high-performance computers and accelerators
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| 653 |
|
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|a sulfonamides
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| 653 |
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|a arylsulfonamide
|
| 653 |
|
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|a anticancer compounds
|
| 653 |
|
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|a telomerase inhibitors
|
| 653 |
|
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|a structure-based drug design
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| 653 |
|
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|a computer drug design
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| 653 |
|
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|a MolAr
|
| 653 |
|
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|a DNA intercalating agents
|
| 653 |
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|a SARS-CoV-2
|
| 653 |
|
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|a main protease, Mpro
|
| 653 |
|
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|a docking benchmark
|
| 653 |
|
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|a non-steroidal anti-inflammatory drugs
|
| 653 |
|
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|a drug discovery
|
| 653 |
|
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|a lipoxygenase
|
| 653 |
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|a cyclooxygenase
|
| 653 |
|
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|a Hsp90
|
| 653 |
|
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|a cancer
|
| 653 |
|
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|a QSAR
|
| 653 |
|
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|a pharmacophores
|
| 653 |
|
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|a in-silico drug design
|
| 653 |
|
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|a AlphaFold
|
| 653 |
|
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|a anti-CRISPR proteins
|
| 653 |
|
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|a prokaryotic defence mechanisms
|
| 653 |
|
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|a bacteriophages
|
| 653 |
|
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|a structural biology
|
| 653 |
|
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|a protein drug
|
| 653 |
|
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|a Merkel cell polyomavirus
|
| 653 |
|
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|a Merkel cell carcinomas
|
| 653 |
|
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|a drug design
|
| 653 |
|
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|a ADMET
|
| 653 |
|
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|a MD simulation
|
| 653 |
|
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|a antimicrobial peptide database
|
| 653 |
|
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|a antiviral peptides
|
| 653 |
|
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|a database filtering technology
|
| 653 |
|
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|a Ebola virus
|
| 653 |
|
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|a peptide design
|
| 653 |
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|a G-quadruplex DNA
|
| 653 |
|
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|a TERRA
|
| 653 |
|
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|a mass spectrometry
|
| 653 |
|
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|a biological assays
|
| 653 |
|
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|a mangrove natural products
|
| 653 |
|
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|a KRASG12C
|
| 653 |
|
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|a ligand-based pharmacophore modeling
|
| 653 |
|
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|a computational biology
|
| 653 |
|
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|a RVFV
|
| 653 |
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|a RdRp
|
| 653 |
|
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|a structural modeling
|
| 653 |
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|a GlyT1
|
| 653 |
|
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|a schizophrenia
|
| 653 |
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|a DAT
|
| 653 |
|
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|a MD
|
| 653 |
|
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|a chagas
|
| 653 |
|
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|a leishmaniasis
|
| 653 |
|
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|a naphthoquinones
|
| 653 |
|
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|a antiprotozoal evaluation
|
| 653 |
|
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|a ADME
|
| 653 |
|
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|a COVID-19
|
| 653 |
|
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|a NSP3
|
| 653 |
|
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|a TCM
|
| 653 |
|
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|a MD simulations
|
| 653 |
|
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|a mutagenesis
|
| 653 |
|
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|a artificial intelligence
|
| 653 |
|
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|a biased signaling
|
| 653 |
|
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|a G protein-coupled receptor
|
| 653 |
|
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|a immunology
|
| 653 |
|
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|a flavonoids
|
| 653 |
|
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|a IDO1
|
| 653 |
|
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|a free energy
|
| 856 |
4 |
0 |
|a www.oapen.org
|u https://mdpi.com/books/pdfview/book/6252
|7 0
|z DOAB: download the publication
|
| 856 |
4 |
0 |
|a www.oapen.org
|u https://directory.doabooks.org/handle/20.500.12854/93823
|7 0
|z DOAB: description of the publication
|
| 590 |
|
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|a Online publication
|
| 590 |
|
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|a ebookoa1222
|
| 590 |
|
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|a doab
|
| 942 |
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|2 z
|c EB
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|c 3028776
|d 1432531
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|0 0
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|6 ONLINE
|7 1
|9 974415
|R 2022-12-28 14:48:15
|a DAIG
|b DAIG
|l 0
|o Online
|r 2022-12-28
|y EB
|
