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SAR and QSAR in Environmental Research Volume 27, 2016 - Issue 2
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Articles

QSAR study on the antimalarial activity of Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors

X. HouState Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, Beijing University of Chemical Technology, Beijing, P.R. China
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X. ChenState Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, Beijing University of Chemical Technology, Beijing, P.R. China
,
M. ZhangState Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, Beijing University of Chemical Technology, Beijing, P.R. China
&
A. YanState Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, Beijing University of Chemical Technology, Beijing, P.R. China;Stake Key Laboratory of Natural and Biomimetic Drugs, Peking University, Beijing, P.R. ChinaCorrespondence[email protected]
Pages 101-124 | Received 25 Jul 2015, Accepted 17 Dec 2015, Published online: 25 Feb 2016

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V.K. Vyas, S. Bhati, M. Sharma, P. Gehlot, N. Patel & S. Dalai. (2023) 3D-QSAR-based design, synthesis and biological evaluation of 2,4-disubstituted quinoline derivatives as antimalarial agents. SAR and QSAR in Environmental Research 34:8, pages 639-659.
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J.H. Zothantluanga, D. Chetia, S. Rajkhowa & A.K. Umar. (2023) Unsupervised machine learning, QSAR modelling and web tool development for streamlining the lead identification process of antimalarial flavonoids. SAR and QSAR in Environmental Research 34:2, pages 117-146.
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Vivek K. Vyas, Sapna Bhati, Shivani Patel & Manjunath Ghate. (2022) Structure- and ligand-based drug design methods for the modeling of antimalarial agents: a review of updates from 2012 onwards. Journal of Biomolecular Structure and Dynamics 40:20, pages 10481-10506.
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Probir Kumar Ojha, Vinay Kumar, Joyita Roy & Kunal Roy. (2021) Recent advances in quantitative structure–activity relationship models of antimalarial drugs. Expert Opinion on Drug Discovery 16:6, pages 659-695.
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Danishuddin, G. Madhukar, M.Z. Malik & N. Subbarao. (2019) Development and rigorous validation of antimalarial predictive models using machine learning approaches. SAR and QSAR in Environmental Research 30:8, pages 543-560.
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J. Devillers. (2018) Repurposing drugs for use against Zika virus infection. SAR and QSAR in Environmental Research 29:2, pages 103-115.
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Articles from other publishers (10)

Vivek K Vyas, Tanvi Shukla & Manmohan Sharma. (2023) Medicinal chemistry approaches for the discovery of Plasmodium falciparum dihydroorotate dehydrogenase inhibitors as antimalarial agents . Future Medicinal Chemistry 15:14, pages 1295-1321.
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Lucas A. Machado, Eduardo Krempser & Ana Carolina Ramos Guimarães. (2022) A machine learning-based virtual screening for natural compounds capable of inhibiting the HIV-1 integrase. Frontiers in Drug Discovery 2.
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Medard Edmund Mswahili, Gati Lother Martin, Jiyoung Woo, Guang J. Choi & Young-Seob Jeong. (2021) Antimalarial Drug Predictions Using Molecular Descriptors and Machine Learning against Plasmodium Falciparum. Biomolecules 11:12, pages 1750.
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Aliyu Wappah Mahmud, Gideon Adamu Shallangwa & Adamu Uzairu. (2020) In silico modeling of tetraoxane-8-aminoquinoline hybrids active against Plasmodium falciparum. Beni-Suef University Journal of Basic and Applied Sciences 9:1.
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Gunther Fischer. 2019. 1 101 .
Shweta Bhagat, Anuj Gahlawat & Prasad V. Bharatam. 2019. Structural Bioinformatics: Applications in Preclinical Drug Discovery Process. Structural Bioinformatics: Applications in Preclinical Drug Discovery Process 177 220 .
Lucas VB Hoelz, Felipe A Calil, Maria C Nonato, Luiz CS Pinheiro & Nubia Boechat. (2018) Plasmodium falciparum dihydroorotate dehydrogenase: a drug target against malaria . Future Medicinal Chemistry 10:15, pages 1853-1874.
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Marcelo T de Oliveira & Edson Katekawa. (2018) On the virtues of automated quantitative structure–activity relationship: the new kid on the block. Future Medicinal Chemistry 10:3, pages 335-342.
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Sivakumar Prasanth Kumar. (2018) PLHINT: A knowledge-driven computational approach based on the intermolecular H bond interactions at the protein-ligand interface from docking solutions. Journal of Molecular Graphics and Modelling 79, pages 194-212.
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Li Wen, Qing Li, Wei Li, Qiao Cai & Yong-Ming Cai. (2017) A QSAR Study Based on SVM for the Compound of Hydroxyl Benzoic Esters. Bioinorganic Chemistry and Applications 2017, pages 1-10.
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