Environmental risk-based ranking of solvents using the combination of a multimedia model and multi-criteria decision analysis

Marek Tobiszewski, Jacek Namieśnik and Francisco Pena-Pereira

Green Chem., 2017, 19, 1034
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QSAR models of human data can enrich or replace LLNA testing for human skin sensitization

Vinicius M. Alves, Stephen J. Capuzzi, Eugene N. Muratov, Rodolpho C. Braga, Thomas E. Thornton, Denis Fourches, Judy Strickland, Nicole Kleinstreuer, Carolina H. Andrade and Alexander Tropsha

Green Chem., 2016, 18, 6501
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Ecotoxicological risk assessment of organic compounds against various aquatic and terrestrial species: application of interspecies i-QSTTR and species sensitivity distribution techniques

Kabiruddin Khan and Kunal Roy

Green Chem., 2022, 24, 2160
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In silico prediction of chemical aquatic toxicity for marine crustaceans via machine learning

Lin Liu, Hongbin Yang, Yingchun Cai, Qianqian Cao, Lixia Sun, Zhuang Wang, Weihua Li, Guixia Liu, Philip W. Lee and Yun Tang

Toxicol. Res., 2019, 8, 341
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Systematic QSAR and iQCCR modelling of fused/non-fused aromatic hydrocarbons (FNFAHs) carcinogenicity to rodents: reducing unnecessary chemical synthesis and animal testing

Feifan Li, Tengjiao Fan, Guohui Sun, Lijiao Zhao, Rugang Zhong and Yongzhen Peng

Green Chem., 2022, 24, 5304
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QSAR modeling of cumulative environmental end-points for the prioritization of hazardous chemicals

Paola Gramatica, Ester Papa and Alessandro Sangion

Environ. Sci.: Processes Impacts, 2018, 20, 38
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Ecotoxicological risk assessment of pesticides against different aquatic and terrestrial species: using mechanistic QSTR and iQSTTR modelling approaches to fill the toxicity data gap

Yishan Li, Tengjiao Fan, Ting Ren, Na Zhang, Lijiao Zhao, Rugang Zhong and Guohui Sun

Green Chem., 2024, 26, 839
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Predicting lignin removal efficiency in deep eutectic solvent-based biomass fractionation: an explainable machine learning approach

Zijing Zhong, Babbiker Mohammed Taher Gorish, Yue Bai, Waha Ismail Yahia Abdelmula, Wenqian Dang and Daochen Zhu

Green Chem., 2025, 27, 11036
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Metal bioaccumulation prediction via QSPR-q-RASPR synergy and cross-species risk analysis

Ramin Abdullayev, Kabiruddin Khan, Gopala Krishna Jillella, Varun Gopalakrishnan Nair, Sk. Abdul Amin, Joyita Roy, Mahmoud Bousily and Agnieszka Gajewicz-Skretna

Green Chem., 2025, 27, 9679
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Predicting the density and viscosity of hydrophobic eutectic solvents: towards the development of sustainable solvents

Tarek Lemaoui, Ahmad S. Darwish, Ayoub Attoui, Farah Abu Hatab, Nour El Houda Hammoudi, Yacine Benguerba, Lourdes F. Vega and Inas M. Alnashef

Green Chem., 2020, 22, 8511
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Molecular-Based Guide to Predict the pH of Eutectic Solvents: Promoting an Efficient Design Approach for New Green Solvents

Tarek Lemaoui, Farah Abu Hatab, Ahmad S. Darwish, Ayoub Attoui, Nour El Houda Hammoudi, Ghaiath Almustafa, Mohamed Benaicha, Yacine Benguerba and Inas M. Alnashef

ACS Sustainable Chem. Eng., 2021, 9, 5783
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Hazard of pharmaceuticals for aquatic environment: Prioritization by structural approaches and prediction of ecotoxicity

Alessandro Sangion and Paola Gramatica

Environment International, 2016, 95, 131
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Prioritization of the ecotoxicological hazard of PAHs towards aquatic species spanning three trophic levels using 2D-QSTR, read-across and machine learning-driven modelling approaches

Feifan Li, Peng Wang, Tengjiao Fan, Na Zhang, Lijiao Zhao, Rugang Zhong and Guohui Sun

Journal of Hazardous Materials, 2024, 465, 133410
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Synthesis of thiazolidine-2,4-dione tethered 1,2,3-triazoles as α-amylase inhibitors: In vitro approach coupled with QSAR, molecular docking, molecular dynamics and ADMET studies

Rahul Singh, Jayant Sindhu, Meena Devi, Parvin Kumar, Sohan Lal, Ashwani Kumar, Devender Singh and Harish Kumar

European Journal of Medicinal Chemistry, 2024, 275, 116623
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QSAR assessment of aquatic toxicity potential of diverse agrochemicals

A. Nath, P.K. Ojha and K. Roy

SAR and QSAR in Environmental Research, 2023, 34, 923
DOI: 10.1080/1062936X.2023.2278074

First report on the QSAR modelling and multistep virtual screening of the inhibitors of nonstructural protein Nsp14 of SARS-CoV-2: Reducing unnecessary chemical synthesis and experimental tests

Qianqian Wang, Tengjiao Fan, Runqing Jia, Na Zhang, Lijiao Zhao, Rugang Zhong and Guohui Sun

Arabian Journal of Chemistry, 2024, 17, 105614
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Predicting the CO2 Capture Capability of Deep Eutectic Solvents and Screening over 1000 of their Combinations Using Machine Learning

Tarek Lemaoui, Abir Boublia, Soumaya Lemaoui, Ahmad S. Darwish, Barbara Ernst, Manawwer Alam, Yacine Benguerba, Fawzi Banat and Inas M. AlNashef

ACS Sustainable Chem. Eng., 2023, 11, 9564
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Chronic and acute eco-toxicity modeling of carcinogenic and hazardous air pollutants toward humans for critical risk assessment and regulatory decision-making

Ankur Kumar, Probir Kumar Ojha and Kunal Roy

Computational Toxicology, 2025, 34, 100358
DOI: 10.1016/j.comtox.2025.100358

The rat acute oral toxicity of trifluoromethyl compounds (TFMs): a computational toxicology study combining the 2D-QSTR, read-across and consensus modeling methods

Xinyi Lu, Xin Wang, Shuo Chen, Tengjiao Fan, Lijiao Zhao, Rugang Zhong and Guohui Sun

Arch Toxicol, 2024, 98, 2213
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Modelling lethality and teratogenicity of zebrafish ( Danio rerio ) due to β-lactam antibiotics employing the QSTR approach

A. Nath, P.K. Ojha and K. Roy

SAR and QSAR in Environmental Research, 2024, 35, 565
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Attenuation of antigen-specific T helper 1 immunity by Neolitsea hiiranensis and its derived terpenoids

Yin-Hua Cheng, Ih-Sheng Chen, Ying-Chi Lin, Chun-Wei Tung, Hsun-Shuo Chang and Chia-Chi Wang

PeerJ, 2016, 4, e2758
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Ecotoxicological QSAR modelling of the acute toxicity of fused and non-fused polycyclic aromatic hydrocarbons (FNFPAHs) against two aquatic organisms: Consensus modelling and comparison with ECOSAR

Feifan Li, Guohui Sun, Tengjiao Fan, Na Zhang, Lijiao Zhao, Rugang Zhong and Yongzhen Peng

Aquatic Toxicology, 2023, 255, 106393
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Predicting the Surface Tension of Deep Eutectic Solvents Using Artificial Neural Networks

Tarek Lemaoui, Abir Boublia, Ahmad S. Darwish, Manawwer Alam, Sungmin Park, Byong-Hun Jeon, Fawzi Banat, Yacine Benguerba and Inas M. AlNashef

ACS Omega, 2022, 7, 32194
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Celebrating 40 Years of Career

Ester Papa, Alessandro Sangion and Nicola Chirico

Molecular Informatics, 2019, 38
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Ecotoxicological modelling of cosmetics for aquatic organisms: A QSTR approach

K. Khan and K. Roy

SAR and QSAR in Environmental Research, 2017, 28, 567
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Machine learning approach to map the thermal conductivity of over 2,000 neoteric solvents for green energy storage applications

Tarek Lemaoui, Ahmad S. Darwish, Ghaiath Almustafa, Abir Boublia, P.R. Sarika, Nabil Abdel Jabbar, Taleb Ibrahim, Paul Nancarrow, Krishna Kumar Yadav, Ahmed M. Fallatah, Mohamed Abbas, Jari S. Algethami, Yacine Benguerba, Byong-Hun Jeon, Fawzi Banat and Inas M. AlNashef

Energy Storage Materials, 2023, 59, 102795
DOI: 10.1016/j.ensm.2023.102795

Consensus QSAR modeling of toxicity of pharmaceuticals to different aquatic organisms: Ranking and prioritization of the DrugBank database compounds

Kabiruddin Khan, Emilio Benfenati and Kunal Roy

Ecotoxicology and Environmental Safety, 2019, 168, 287
DOI: 10.1016/j.ecoenv.2018.10.060

Reliable and representative in silico predictions of freshwater ecotoxicological hazardous concentrations

Mélanie Douziech, Ad M.J. Ragas, Rosalie van Zelm, Rik Oldenkamp, A. Jan Hendriks, Henry King, Rafika Oktivaningrum and Mark A.J. Huijbregts

Environment International, 2020, 134, 105334
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Defining the Human-Biota Thresholds of Toxicological Concern for Organic Chemicals in Freshwater: The Proposed Strategy of the LIFE VERMEER Project Using VEGA Tools

Diego Baderna, Roberta Faoro, Gianluca Selvestrel, Adrien Troise, Davide Luciani, Sandrine Andres and Emilio Benfenati

Molecules, 2021, 26, 1928
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Contaminants of emerging concern: a review of new approach in AOP technologies

Maryam Salimi, Ali Esrafili, Mitra Gholami, Ahmad Jonidi Jafari, Roshanak Rezaei Kalantary, Mahdi Farzadkia, Majid Kermani and Hamid Reza Sobhi

Environ Monit Assess, 2017, 189
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Elucidation of molecular mechanisms involved in tadpole toxicity employing QSTR and q-RASAR approach

Kabiruddin Khan, Gopala Krishna Jillella and Agnieszka Gajewicz-Skretna

Aquatic Toxicology, 2024, 277, 107136
DOI: 10.1016/j.aquatox.2024.107136

QSTR Models in Dioxins and Dioxin-like Compounds Provide Insights into Gene Expression Dysregulation

Elisa G. Eleazar, Andrei Raphael M. Carrera, Janus Isaiah R. Quiambao, Alvin R. Caparanga and Lemmuel L. Tayo

Toxics, 2024, 12, 597
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A regression-based model to predict chemical migration from packaging to food

Mélanie Douziech, Ana Benítez-López, Alexi Ernstoff, Cecilia Askham, A. Jan Hendriks, Henry King and Mark A. J. Huijbregts

J Expo Sci Environ Epidemiol, 2020, 30, 469
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Ecotoxicological QSAR study of fused/non-fused polycyclic aromatic hydrocarbons (FNFPAHs): Assessment and priority ranking of the acute toxicity to Pimephales promelas by QSAR and consensus modeling methods

Shuo Chen, Guohui Sun, Tengjiao Fan, Feifan Li, Yuancong Xu, Na Zhang, Lijiao Zhao and Rugang Zhong

Science of The Total Environment, 2023, 876, 162736
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Considerations for future quantitative structure-activity relationship (QSAR) modelling for heavy metals – A case study of mercury

Rebecca von Hellfeld, Christoph Gade, Neil Vargesson and Astley Hastings

Toxicology, 2023, 499, 153661
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Solvent effects on the spectroscopic properties of Damascone derivatives: A sequential Monte Carlo/Quantum Mechanics study

Agnaldo Rosa de Almeida, Leonardo Bruno Assis Oliveira and Guilherme Colherinhas

Chemical Physics Letters, 2019, 730, 531
DOI: 10.1016/j.cplett.2019.05.028

Decoding cyanide toxicity: Integrating Quantitative Structure-Toxicity Relationships (QSTR) with species sensitivity distributions and q-RASTR modeling

Kabiruddin Khan, Ramin Abdullayev, Gopala Krishna Jillella, Varun Gopalakrishnan Nair, Mahmoud Bousily, Supratik Kar and Agnieszka Gajewicz-Skretna

Ecotoxicology and Environmental Safety, 2025, 291, 117824
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Preparation of ceramic ultrafiltration membrane using green synthesized CuO nanoparticles for chromium (VI) removal and optimization by response surface methodology

Piyali Choudhury, Priyanka Mondal, Swachchha Majumdar, Sudeshna Saha and Ganesh C. Sahoo

Journal of Cleaner Production, 2018, 203, 511
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Ensemble QSAR Modeling to Predict Multispecies Fish Toxicity Lethal Concentrations and Points of Departure

Thomas Y. Sheffield and Richard S. Judson

Environ. Sci. Technol., 2019, 53, 12793
DOI: 10.1021/acs.est.9b03957

In vivo toxicity of nitroaromatic compounds to rats: QSTR modelling and interspecies toxicity relationship with mouse

Yuxing Hao, Guohui Sun, Tengjiao Fan, Xiaoyu Tang, Jing Zhang, Yongdong Liu, Na Zhang, Lijiao Zhao, Rugang Zhong and Yongzhen Peng

Journal of Hazardous Materials, 2020, 399, 122981
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Design and Testing of Safer, More Effective Preservatives for Consumer Products

Heather L. Buckley, William M. Hart-Cooper, Jong H. Kim, David M. Faulkner, Luisa W. Cheng, Kathleen L. Chan, Christopher D. Vulpe, William J. Orts, Susan E. Amrose and Martin J. Mulvihill

ACS Sustainable Chem. Eng., 2017, 5, 4320
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Hazard screening of contaminants of emerging concern (CECs) in Sweden’s three largest lakes and their associated rivers

Daniel Malnes, Sylvia Waara, Romain Figuière, Lutz Ahrens, Karin Wiberg, Stephan J. Köhler and Oksana Golovko

Journal of Hazardous Materials, 2023, 453, 131376
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Prediction of acute toxicity for Chlorella vulgaris caused by tire wear particle-derived compounds using quantitative structure-activity relationship models

Jie-Ru Jiang, Wen-Xi Cai, Zhi-Feng Chen, Xiao-Liang Liao and Zongwei Cai

Water Research, 2024, 256, 121643
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Modeling pesticides toxicity to Sheepshead minnow using QSAR

Lu Yang, Yinghuan Wang, Weiyu Hao, Jing Chang, Yifan Pan, Jianzhong Li and Huili Wang

Ecotoxicology and Environmental Safety, 2020, 193, 110352
DOI: 10.1016/j.ecoenv.2020.110352

Ecotoxicological Modeling of Organic Chemicals for Their Acute Toxicity in Algae Using Classification and Toxicophore-Based Approaches

Kabiruddin Khan and Probir Kumar Ojha

International Journal of Quantitative Structure-Property Relationships, 2020, 5, 17
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Predictive in silico models for aquatic toxicity of cosmetic and personal care additive mixtures

Yu-Ting Yang and Hong-Gang Ni

Water Research, 2023, 236, 119981
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Emerging Organic Contaminants in Chinese Surface Water: Identification of Priority Pollutants

Mengmeng Zhong, Tielong Wang, Wenxing Zhao, Jun Huang, Bin Wang, Lee Blaney, Qingwei Bu and Gang Yu

Engineering, 2022, 11, 111
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Development of human biotransformation QSARs and application for PBT assessment refinement

Ester Papa, Alessandro Sangion, Jon A. Arnot and Paola Gramatica

Food and Chemical Toxicology, 2018, 112, 535
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Risk Assessment of Cosmetic Preservatives Using QSAR

Monika Bhardwaj, Neeraj Masand, Jagannath Sahoo and Vaishali M. Patil

International Journal of Quantitative Structure-Property Relationships, 2020, 5, 44
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Principles of QSAR Modeling

Paola Gramatica

International Journal of Quantitative Structure-Property Relationships, 2020, 5, 61
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Chronic aquatic toxicity assessment of diverse chemicals on Daphnia magna using QSAR and chemical read-across

Ankur Kumar, Vinay Kumar, Probir Kumar Ojha and Kunal Roy

Regulatory Toxicology and Pharmacology, 2024, 148, 105572
DOI: 10.1016/j.yrtph.2024.105572

Computational modeling of air pollutants for aquatic risk: Prediction of ecological toxicity and exploring structural characteristics

Feyza Kelleci Çelik and Gul Karaduman

Chemosphere, 2024, 366, 143501
DOI: 10.1016/j.chemosphere.2024.143501

QSARINS‐Chem standalone version: A new platform‐independent software to profile chemicals for physico‐chemical properties, fate, and toxicity

Nicola Chirico, Alessandro Sangion, Paola Gramatica, Linda Bertato, Ilaria Casartelli and Ester Papa

J Comput Chem, 2021, 42, 1452
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QSAR and Chemical Read-Across Analysis of 370 Potential MGMT Inactivators to Identify the Structural Features Influencing Inactivation Potency

Guohui Sun, Peiying Bai, Tengjiao Fan, Lijiao Zhao, Rugang Zhong, R. McElhinney, T. McMurry, Dorothy Donnelly, Joan McCormick, Jane Kelly and Geoffrey Margison

Pharmaceutics, 2023, 15, 2170
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Molecular-based artificial neural networks for selecting deep eutectic solvents for the removal of contaminants from aqueous media

Narjis E. Awaja, Ghaiath Almustafa, Ahmad S. Darwish, Tarek Lemaoui, Yacine Benguerba, Fawzi Banat, Hassan A. Arafat and Inas AlNashef

Chemical Engineering Journal, 2023, 476, 146429
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Predictive ecotoxicity of MoA 1 of organic chemicals using in silico approaches

Luana de Morais e Silva, Mateus Feitosa Alves, Luciana Scotti, Wilton Silva Lopes and Marcus Tullius Scotti

Ecotoxicology and Environmental Safety, 2018, 153, 151
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Ecotoxicological QSAR modeling of organic compounds against fish: Application of fragment based descriptors in feature analysis

Kabiruddin Khan, Diego Baderna, Claudia Cappelli, Cosimo Toma, Anna Lombardo, Kunal Roy and Emilio Benfenati

Aquatic Toxicology, 2019, 212, 162
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Priority screening on emerging contaminants in sediments of the Yangtze River, China

Yu Wen, Siyu Huang, Zhihao Qin, Zhongli Chen and Ying Shao

Environ Sci Eur, 2024, 36
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Toward Application and Implementation of in Silico Tools and Workflows within Benign by Design Approaches

Stefanie Lorenz, Ann-Kathrin Amsel, Neele Puhlmann, Marco Reich, Oliver Olsson and Klaus Kümmerer

ACS Sustainable Chem. Eng., 2021, 9, 12461
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Prioritization of pharmaceuticals in water environment in China based on environmental criteria and risk analysis of top-priority pharmaceuticals

Yan Li, Luyan Zhang, Jie Ding and Xianshu Liu

Journal of Environmental Management, 2020, 253, 109732
DOI: 10.1016/j.jenvman.2019.109732

Ecotoxicological QSAR modeling of endocrine disruptor chemicals

Kabiruddin Khan, Kunal Roy and Emilio Benfenati

Journal of Hazardous Materials, 2019, 369, 707
DOI: 10.1016/j.jhazmat.2019.02.019

Assessment of chemical constituents of personal care products (PCPs) and their environmental implications: A case of South Africa

Sebatane Sharon Mabitla, Natsayi Chiwaye and Michael O. Daramola

Materials Today: Proceedings, 2024, 105, 209
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On the Virtues of Automated Quantitative Structure–Activity Relationship: The New Kid on the Block

Marcelo T de Oliveira and Edson Katekawa

Future Med. Chem., 2018, 10, 335
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Chemometric QSAR modeling of acute oral toxicity of Polycyclic Aromatic Hydrocarbons (PAHs) to rat using simple 2D descriptors and interspecies toxicity modeling with mouse

Guohui Sun, Yifan Zhang, Luyu Pei, Yuqing Lou, Yao Mu, Jiayi Yun, Feifan Li, Yachen Wang, Zhaoqi Hao, Sha Xi, Chen Li, Chuhan Chen, Lijiao Zhao, Na Zhang, Rugang Zhong and Yongzhen Peng

Ecotoxicology and Environmental Safety, 2021, 222, 112525
DOI: 10.1016/j.ecoenv.2021.112525

Assessing Viscosity in Sustainable Deep Eutectic Solvents and Cosolvent Mixtures: An Artificial Neural Network-Based Molecular Approach

Luan Vittor Tavares Duarte de Alencar, Sabrina Belén Rodríguez-Reartes, Frederico Wanderley Tavares and Fèlix Llovell

ACS Sustainable Chem. Eng., 2024, 12, 7987
DOI: 10.1021/acssuschemeng.3c07219

Endocrine disruptor identification and multitoxicity level assessment of organic chemicals: An example of multiple machine learning models

Ning Hao, Yuanyuan Zhao, Peixuan Sun, Zhengyang Deng, Xiran Cui, Jiapeng Liu and Wenjin Zhao

Journal of Hazardous Materials, 2025, 485, 136896
DOI: 10.1016/j.jhazmat.2024.136896

An alternative to in-vivo/in-vitro drug toxicity testing: Environmentally relevant approaches for toxicity assessment of pharmaceuticals towards rats

Pabitra Samanta, Ankur Kumar and Probir Kumar Ojha

Chemosphere, 2025, 388, 144693
DOI: 10.1016/j.chemosphere.2025.144693

Ecotoxicological QSAR modelling of organic chemicals against Pseudokirchneriella subcapitata using consensus predictions approach

K. Khan and K. Roy

SAR and QSAR in Environmental Research, 2019, 30, 665
DOI: 10.1080/1062936X.2019.1648315

Intelligent consensus predictions of bioconcentration factor of pharmaceuticals using 2D and fragment-based descriptors

Kabiruddin Khan, Vinay Kumar, Erika Colombo, Anna Lombardo, Emilio Benfenati and Kunal Roy

Environment International, 2022, 170, 107625
DOI: 10.1016/j.envint.2022.107625

Molecular-based artificial neural network for predicting the electrical conductivity of deep eutectic solvents

Abir Boublia, Tarek Lemaoui, Farah Abu Hatab, Ahmad S. Darwish, Fawzi Banat, Yacine Benguerba and Inas M. AlNashef

Journal of Molecular Liquids, 2022, 366, 120225
DOI: 10.1016/j.molliq.2022.120225

QSAR modelling of organic dyes for their acute toxicity in Daphnia magna using 2D-descriptors

G.K. Jillella and K. Roy

SAR and QSAR in Environmental Research, 2022, 33, 111
DOI: 10.1080/1062936X.2022.2033318

Multitask Neural Network for Mapping the Glass Transition and Melting Temperature Space of Homo- and Co-Polyhydroxyalkanoates Using σProfiles Molecular Inputs

Abir Boublia, Tarek Lemaoui, Jawaher AlYammahi, Ahmad S. Darwish, Akil Ahmad, Manawwer Alam, Fawzi Banat, Yacine Benguerba and Inas M. AlNashef

ACS Sustainable Chem. Eng., 2023, 11, 208
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Ecotoxicity interspecies QAAR models from Daphnia toxicity of pharmaceuticals and personal care products

A. Sangion and P. Gramatica

SAR and QSAR in Environmental Research, 2016, 27, 781
DOI: 10.1080/1062936X.2016.1233139

In silico modelling of acute toxicity of 1, 2, 4-triazole antifungal agents towards zebrafish (Danio rerio) embryos: Application of the Small Dataset Modeller tool

Aniket Nath, Priyanka De and Kunal Roy

Toxicology in Vitro, 2021, 75, 105205
DOI: 10.1016/j.tiv.2021.105205

Molecular Initiating Events of Bisphenols on Androgen Receptor-Mediated Pathways Provide Guidelines for in Silico Screening and Design of Substitute Compounds

Qinchang Chen, Xiaoxiang Wang, Haoyue Tan, Wei Shi, Xiaowei Zhang, Si Wei, John P. Giesy and Hongxia Yu

Environ. Sci. Technol. Lett., 2019, 6, 205
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Ionic liquids as environmental hazards – Crucial data in view of future PBT and PMT assessment

Dorota Kowalska, Jakub Maculewicz, Piotr Stepnowski and Joanna Dołżonek

Journal of Hazardous Materials, 2021, 403, 123896
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Support vector machine-based model for toxicity of organic compounds against fish

Xinliang Yu

Regulatory Toxicology and Pharmacology, 2021, 123, 104942
DOI: 10.1016/j.yrtph.2021.104942

Confronting variability with uncertainty in the ecotoxicological impact assessment of down-the-drain products

Mélanie Douziech, Rik Oldenkamp, Rosalie van Zelm, Henry King, A. Jan Hendriks, Anne-Sophie Ficheux and Mark A.J. Huijbregts

Environment International, 2019, 126, 37
DOI: 10.1016/j.envint.2019.01.080

Are we ready to combat the ecotoxicity of COVID-19 pharmaceuticals? An in silico aquatic risk assessment

Kabiruddin Khan, Supratik Kar and Kunal Roy

Aquatic Toxicology, 2023, 256, 106416
DOI: 10.1016/j.aquatox.2023.106416

Theoretical Studies on the Quantitative Structure–Toxicity Relationship of Polychlorinated Biphenyl Congeners Reveal High Affinity Binding to Multiple Human Nuclear Receptors

Andrei Raphael M. Carrera, Elisa G. Eleazar, Alvin R. Caparanga and Lemmuel L. Tayo

Toxics, 2024, 12, 49
DOI: 10.3390/toxics12010049