Results 11 to 20 of about 2,040,439 (323)
AdapTor: Adaptive Topological Regression for quantitative structure–activity relationship modeling [PDF]
Journal of CheminformaticsQuantitative structure–activity relationship (QSAR) modeling has become a critical tool in drug design. Recently proposed Topological Regression (TR), a computationally efficient and highly interpretable QSAR model that maps distances in the chemical ...
Yixiang Mao, Souparno Ghosh, Ranadip Pal
doaj +2 more sources
Frontiers in Microbiology, 2019 Besides their established antioxidant activity, many phenolic compounds may exhibit significant antibacterial activity. Here, the effect of a large dataset of 35 polyphenols on the growth of 6 foodborne pathogenic or food-spoiling bacterial strains ...
Lynda Bouarab-Chibane +8 more
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Platinum(IV) compounds as potential drugs: a quantitative structure-activity relationship study [PDF]
BioImpacts, 2023 Introduction: Machine learning methods, coupled with a tremendous increase in computer power in recent years, are promising tools in modern drug design and drug repurposing.
Jurica Novak +4 more
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QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS IN COMPUTER AIDED MOLECULAR DESIGN [PDF]
, 2016 The drug development process requires the complete evaluation and identification of the chosen substance as well as its properties. It involves extensive chemical examination to achieve the best therapeutic effects which demands huge expenditure both in ...
Hentabli Hamza +2 more
openalex +3 more sources
ACI Avances en Ciencias e Ingenierías, 2014 The aim of this work was the comparison between κ-Nearest Neighbors (κ-NN) and Counterpropagation Artificial Neural network (CP-ANN) classification methods for modeling the toxicity of a set of 192 organochlorinated, organophosphates ...
Fernando Cárdenas +2 more
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Design and Synthesis of Pleuromutilin Derivatives as Antibacterial Agents Using Quantitative Structure-Activity Relationship Model. [PDF]
Int J Mol SciZhang J +5 more
europepmc +3 more sources
Infolitika Journal of Data Science, 2023 This comprehensive review explores the pivotal role of ensemble machine learning techniques in Quantitative Structure-Activity Relationship (QSAR) modeling for drug discovery.
T. R. Noviandy +6 more
semanticscholar +1 more source
International Journal of Molecular Sciences, 2021 Nitroaromatic compounds (NACs) are ubiquitous in the environment due to their extensive industrial applications. The recalcitrance of NACs causes their arduous degradation, subsequently bringing about potential threats to human health and environmental ...
Tao Huang +5 more
semanticscholar +1 more source
3D-QSAR-based pharmacophore determination and design of novel DPP-4 inhibitors [PDF]
Scripta Medica, 2022 Background/Aim: Therapy of diabetes mellitus type 2 includes drugs that act as inhibitors of dipeptidyl peptidase 4 (DPP-4) enzyme. Several DPP-4 inhibitors are marketed today and although they have favourable safety profile and tolerability, they show ...
Rogić Sanja, Gagić Žarko
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Quantitative structureâactivity relationship (QSAR) analysis of aromatic effector specificity in NtrC-like transcriptional activators from aromatic oxidizing bacteria [PDF]
FEMS Microbiology Letters, 2003 A quantitative structure-activity relationship (QSAR) approach was taken to provide mechanistic insights into the interaction between the chemical structure of inducing compounds and the transcriptional activation of aromatic monooxygenase operons among the XylR/DmpR subclass of bacterial NtrC-like transcriptional regulators. Compared to XylR and DmpR,
Park, Joonhong +3 more
openaire +3 more sources