Study of the relationship between spatial structure and anticholinesterase activity of o-phosphorylate oximes

Plyamovatyi, A. Kh.; Vandyukova, I. I.; Shagidullin, R. R.; Makhaeva, G. F.; Malygin, V. V.; Gorbunov, S. M.

doi:10.1007/bf02464156

Cited by 4 publications

(3 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although QSAR models to predict K i (Johnson et al 1985;Plyamovatyi et al 1997;Ruark et al 2013;Lee and Barron 2016) and median lethal dose (LD 50 ) values (Devillers 2004;Bermúdez-Saldaña and Cronin 2006;García-Domenech et al 2007;Zhao and Yu 2013;Camacho-Mendoza et al 2018;Ding et al 2018) have been reported, these models suffer from small datasets, insufficient structural structure diversity, oversimplified modeling algorithms, and the lack of both strict validation and applicability domain (AD) evaluations; thus, their practical use is limited. For example, based on semi-empirical quantum chemical (QC) descriptors, Johnson et al (1985) constructed linear QSAR models of 19 OPs with their hydrolysis rate constants using a stepwise linear regression analysis method.…”

Section: Introductionmentioning

confidence: 99%

“…They found that the hydrolysis rates of OPs are closely related to the charge of the phosphorus atom and the steric effects of the leaving group. Plyamovatyi et al (1997) constructed linear QSAR models for the K i values of 41 OPs with respect to human AChE (hAChE) using empirical and experimental parameters related to the hydrophobic, spatial, and electronic properties of the OP substituents. Although the correlation coefficient of the best model was relatively high ( r = 0.936 ), the structures of these OPs were homologs.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Ensemble machine learning to evaluate the in vivo acute oral toxicity and in vitro human acetylcholinesterase inhibitory activity of organophosphates

Wang¹,

Ding²,

Shi³

et al. 2021

Arch Toxicol

View full text Add to dashboard Cite

Organophosphates (OPs) are hazardous chemicals widely used in industry and agriculture. Distribution of their residues in nature causes serious risks to humans, animals, and plants. To reduce hazards from OPs, quantitative structure-activity relationship (QSAR) models for predicting their acute oral toxicity in rats and mice and inhibition constants concerning human acetylcholinesterase were developed according to the bioactivity data of 456 unique OPs. Based on robust, two-dimensional molecular descriptors and quantum chemical descriptors, which accurately reflect OP electronic structures and reactivities, the influences of eight machine-learning algorithms on the prediction performance of the QSAR models were explored, and consensus QSAR models were constructed. Several strict model validation indices and the results of applicability domain evaluations show that the established consensus QSAR models exhibit good robustness, practical prediction abilities, and wide application scopes. Poor correlation was observed between acute oral toxicity at the mammalian level and the inhibition constants at the molecular level, indicating that the acute toxicity of OPs cannot be evaluated only by the experimental data of enzyme inhibitory activity, their toxicokinetic characteristics must also be considered. The constructed QSAR models described herein provide rapid, theoretical assessment of the bioactivity of unstudied or unknown OPs, as well as guidance for making decisions regarding their regulation.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Ensemble machine learning to evaluate the in vivo acute oral toxicity and in vitro human acetylcholinesterase inhibitory activity of organophosphates

Wang¹,

Ding²,

Shi³

et al. 2021

Arch Toxicol

View full text Add to dashboard Cite

show abstract

“…In this study, we analyzed data on the antiesterase activity and selectivity of 58 O phosphorylated oximes [6][7][8][9] containing phosphate (1), thiophosphate (2), (3), and phenylphosphonate (4) fragments with different leaving groups.…”

mentioning

confidence: 99%

Molecular design of O-phosphorylated oximes—Selective inhibitors of butyrylcholinesterase

Radchenko

Melnikov

Makhaeva

et al. 2012

Dokl Biochem Biophys

Self Cite

View full text Add to dashboard Cite

Quantitative structure–activity relationships for organophosphates binding to acetylcholinesterase

et al. 2012

View full text Add to dashboard Cite

Organophosphates are a group of pesticides and chemical warfare nerve agents that inhibit acetylcholinesterase, the enzyme responsible for hydrolysis of the excitatory neurotransmitter acetylcholine. Numerous structural variants exist for this chemical class, and data regarding their toxicity can be difficult to obtain in a timely fashion. At the same time, their use as pesticides and military weapons is widespread, which presents a major concern and challenge in evaluating human toxicity. To address this concern, a quantitative structure-activity relationship (QSAR) was developed to predict pentavalent organophosphate oxon human acetylcholinesterase bimolecular rate constants. A database of 278 three-dimensional structures and their bimolecular rates was developed from 15 peer-reviewed publications. A database of simplified molecular input line entry notations and their respective acetylcholinesterase bimolecular rate constants are listed in Supplementary Material, Table I. The database was quite diverse, spanning 7 log units of activity. In order to describe their structure, 675 molecular descriptors were calculated using AMPAC 8.0 and CODESSA 2.7.10. Orthogonal projection to latent structures regression, bootstrap leave-random-many-out cross-validation and y-randomization were used to develop an externally validated consensus QSAR model. The domain of applicability was assessed by the William's plot. Six external compounds were outside the warning leverage indicating potential model extrapolation. A number of compounds had residuals >2 or <-2, indicating potential outliers or activity cliffs. The results show that the HOMO-LUMO energy gap contributed most significantly to the binding affinity. A mean training R (2) of 0.80, a mean test set R (2) of 0.76 and a consensus external test set R (2) of 0.66 were achieved using the QSAR. The training and external test set RMSE values were found to be 0.76 and 0.88. The results suggest that this QSAR model can be used in physiologically based pharmacokinetic/pharmacodynamic models of organophosphate toxicity to determine the rate of acetylcholinesterase inhibition.

show abstract

Study of the relationship between spatial structure and anticholinesterase activity of o-phosphorylate oximes

Cited by 4 publications

References 13 publications

Ensemble machine learning to evaluate the in vivo acute oral toxicity and in vitro human acetylcholinesterase inhibitory activity of organophosphates

Ensemble machine learning to evaluate the in vivo acute oral toxicity and in vitro human acetylcholinesterase inhibitory activity of organophosphates

Molecular design of O-phosphorylated oximes—Selective inhibitors of butyrylcholinesterase

Quantitative structure–activity relationships for organophosphates binding to acetylcholinesterase

Contact Info

Product

Resources

About