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Applications of 2D descriptors in drug design: a DRAGON tale
AM Helguera, RD Combes… - Current topics in …, 2008 - ingentaconnect.com
In order to minimize expensive drug failures, is essential to determine potential activity,
toxicity and ADME problems as early as possible. In view of the large libraries of compounds …
toxicity and ADME problems as early as possible. In view of the large libraries of compounds …
Biological activity and toxicity: A conceptual DFT approach
Quantitative structure–activity relationship (QSAR) models are generated for biological
activity and toxicity in terms of global and local reactivity descriptors within a conceptual …
activity and toxicity in terms of global and local reactivity descriptors within a conceptual …
Highly efficient Suzuki–Miyaura coupling of heterocyclic substrates through rational reaction design
CA Fleckenstein, H Plenio - Chemistry–A European Journal, 2008 - Wiley Online Library
Abstract A dicyclohexyl (2‐sulfo‐9‐(3‐(4‐sulfophenyl) propyl)‐9H‐fluoren‐9‐yl)
phosphonium salt was synthesized in 64% overall yield in three steps from simple …
phosphonium salt was synthesized in 64% overall yield in three steps from simple …
MIND-BEST: Web Server for Drugs and Target Discovery; Design, Synthesis, and Assay of MAO-B Inhibitors and Theoretical− Experimental Study of G3PDH Protein …
Many drugs with very different affinity to a large number of receptors are described. Thus, in
this work, we selected drug− target pairs (DTPs/nDTPs) of drugs with high affinity/nonaffinity …
this work, we selected drug− target pairs (DTPs/nDTPs) of drugs with high affinity/nonaffinity …
Alignment-free prediction of a drug− target complex network based on parameters of drug connectivity and protein sequence of receptors
D Vina, E Uriarte, F Orallo… - Molecular …, 2009 - ACS Publications
There are many drugs described with very different affinity to a large number of receptors. In
this work, we selected drug− receptor pairs (DRPs) of affinity/nonaffinity drugs to …
this work, we selected drug− receptor pairs (DRPs) of affinity/nonaffinity drugs to …
Using entropy of drug and protein graphs to predict FDA drug-target network: theoretic-experimental study of MAO inhibitors and hemoglobin peptides from Fasciola …
There are many drugs described with very different affinity to a large number of receptors. In
this work, we selected Drug-Target pairs (DTPs/nDTPs) of drugs with high affinity/non-affinity …
this work, we selected Drug-Target pairs (DTPs/nDTPs) of drugs with high affinity/non-affinity …
Drug development to protozoan diseases
The diseases caused by protozoan parasite are responsible for considerable mortality and
morbidity, affecting more than 500 million of people in the world. The epidemiological control …
morbidity, affecting more than 500 million of people in the world. The epidemiological control …
2D MI-DRAGON: a new predictor for protein–ligands interactions and theoretic-experimental studies of US FDA drug-target network, oxoisoaporphine inhibitors for …
There are many pairs of possible Drug–Proteins Interactions that may take place or not
(DPIs/nDPIs) between drugs with high affinity/non-affinity for different proteins. This fact …
(DPIs/nDPIs) between drugs with high affinity/non-affinity for different proteins. This fact …
First report on development of quantitative interspecies structure–carcinogenicity relationship models and exploring discriminatory features for rodent carcinogenicity …
S Kar, K Roy - Chemosphere, 2012 - Elsevier
Different regulatory agencies in food and drug administration and environmental protection
worldwide are employing quantitative structure–activity relationship (QSAR) models to fill the …
worldwide are employing quantitative structure–activity relationship (QSAR) models to fill the …
Natural/random protein classification models based on star network topological indices
The development of the complex network graphs permits us to describe any real system
such as social, neural, computer or genetic networks by transforming real properties in …
such as social, neural, computer or genetic networks by transforming real properties in …