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Optimal selection of learning data for highly accurate QSAR prediction of chemical biodegradability: a machine learning-based approach
In this study, we propose a novel approach for the optimal selection of training set that enables a highly accurate prediction of the biodegradability of chemicals by QSAR. Our findings indicate that the proposed method effectively reduces the root mean squared error and improves the prediction accuracy.PMID:37674414 | DOI:10.1080/1062936X.2023.2251889 (Source: SAR and QSAR in Environmental Research)
Source: SAR and QSAR in Environmental Research - September 7, 2023 Category: Environmental Health Authors: K Takeda K Takeuchi Y Sakuratani K Kimbara Source Type: research

Exploring the Traditional Chinese Medicine (TCM) database chemical space to target I7L protease from monkeypox virus using molecular screening and simulation approaches
SAR QSAR Environ Res. 2023 Sep 7:1-20. doi: 10.1080/1062936X.2023.2250723. Online ahead of print.ABSTRACTIn the current study, we used molecular screening and simulation approaches to target I7L protease from monkeypox virus (mpox) from the Traditional Chinese Medicines (TCM) database. Using molecular screening, only four hits TCM27763, TCM33057, TCM34450 and TCM31564 demonstrated better pharmacological potential than TTP6171 (control). Binding of these molecules targeted Trp168, Asn171, Arg196, Cys237, Ser240, Trp242, Glu325, Ser326, and Cys328 residues and may affect the function of I7L protease in in vitro assay. Moreov...
Source: SAR and QSAR in Environmental Research - September 7, 2023 Category: Environmental Health Authors: A Khan M Shahab F Nasir Y Waheed A Alshammari A Mohammad G Zichen R Li D Q Wei Source Type: research

What is the ecotoxicity of a given chemical for a given aquatic species? Predicting interactions between species and chemicals using recommender system techniques
SAR QSAR Environ Res. 2023 Sep 6:1-24. doi: 10.1080/1062936X.2023.2254225. Online ahead of print.ABSTRACTEcotoxicological safety assessment of chemicals requires toxicity data on multiple species, despite the general desire of minimizing animal testing. Predictive models, specifically machine learning (ML) methods, are one of the tools capable of solving this apparent contradiction as they allow to generalize toxicity patterns across chemicals and species. However, despite the availability of large public toxicity datasets, the data is highly sparse, complicating model development. The aim of this study is to provide insig...
Source: SAR and QSAR in Environmental Research - September 6, 2023 Category: Environmental Health Authors: M Viljanen J Minnema P N H Wassenaar E Rorije W Peijnenburg Source Type: research

Discovery of dual-target natural antimalarial agents against DHODH and PMT of < em > Plasmodium falciparum < /em > : pharmacophore modelling, molecular docking, quantum mechanics, and molecular dynamics simulations
The objective of this study was to identify new natural compounds that can target two P. falciparum enzymes; P. falciparum Dihydroorotate dehydrogenase (PfDHODH) and P. falciparum phosphoethanolamine methyltransferase (PfPMT). To accomplish this, e-pharmacophore modelling and molecular docking were employed against PfDHODH. Following this, 1201 natural compounds with docking scores of ≤ -7 kcal/mol were docked into the active site of the second enzyme PMT. The top nine compounds were subjected to further investigation using MM-GBSA free binding energy calculations and ADME analysis. The results revealed favourable free b...
Source: SAR and QSAR in Environmental Research - September 4, 2023 Category: Environmental Health Authors: E M Elamin S E Eshage S M Mohmmode R M Mukhtar M Mahjoub E Sadelin T H Shoaib A Edris E M Elshamly A A Makki A Ashour A E Sherif W Osman S R M Ibrahim G A Mohamed A A Alzain Source Type: research

3D-QSAR-based design, synthesis and biological evaluation of 2,4-disubstituted quinoline derivatives as antimalarial agents
SAR QSAR Environ Res. 2023 Jul-Sep;34(8):639-659. doi: 10.1080/1062936X.2023.2247326.ABSTRACT2,4-Disubstituted quinoline derivatives were designed based on a 3D-QSAR study, synthesized and evaluated for antimalarial activity. A large dataset of 178 quinoline derivatives was used to perform a 3D-QSAR study using CoMFA and CoMSIA models. PLS analysis provided statistically validated results for CoMFA (r2ncv = 0.969, q2 = 0.677, r2cv = 0.682) and CoMSIA (r2ncv = 0.962, q2 = 0.741, r2cv = 0.683) models. Two series of a total of 40 2,4-disubstituted quinoline derivatives were designed with amide (quinoline-4-carboxamide) and se...
Source: SAR and QSAR in Environmental Research - August 31, 2023 Category: Environmental Health Authors: V K Vyas S Bhati M Sharma P Gehlot N Patel S Dalai Source Type: research

Machine learning-based models for accessing thermal conductivity of liquids at different temperature conditions
SAR QSAR Environ Res. 2023 Jul-Sep;34(8):605-617. doi: 10.1080/1062936X.2023.2244410. Epub 2023 Aug 29.ABSTRACTCombating global warming-related climate change demands prompt actions to reduce greenhouse gas emissions, particularly carbon dioxide. Biomass-based biofuels represent a promising alternative fossil energy source. To convert biomass into energy, numerous conversion processes are performed at high pressure and temperature conditions, and the design and dimensioning of such processes requires thermophysical property data, particularly thermal conductivity, which are not always available in the literature. In this p...
Source: SAR and QSAR in Environmental Research - August 29, 2023 Category: Environmental Health Authors: R Moreno Jimenez B Creton S Marre Source Type: research