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  • 1-10 of  1,184 results for ""Quantitative structure–activity relationship""
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Academic Journal

Advanced QSPR modeling of profens using machine learning and molecular descriptors for NSAID analysis.

  • Authors : Ahmed WE; Department of Mathematics and Statistics, College of Science, Imam Muhammad Ibn Saud Islamic University (IMSIU), PO Box 90950, Riyadh, Saudi Arabia.; Hanif MF

Subjects: Machine Learning* ; Anti-Inflammatory Agents, Non-Steroidal*/Anti-Inflammatory Agents, Non-Steroidal*/Anti-Inflammatory Agents, Non-Steroidal*/chemistry ; Quantitative Structure-Activity Relationship*

  • Source: Scientific reports [Sci Rep] 2025 Jul 20; Vol. 15 (1), pp. 26356. Date of Electronic Publication: 2025 Jul 20.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN:

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Academic Journal

A dataset for machine learning-based QSAR models establishment to screen beta-lactamase inhibitors using the FARM -BIOMOL chemical library.

  • Authors : Pitakbut T; Department of Biology, Pharmaceutical Biology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Staudtstr. 5, 91058, Erlangen, Germany. .; Shenzhen Key Laboratory of Intelligent Bioinformatics and Center for High-Performance Computing, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China. .

Subjects: Quantitative Structure-Activity Relationship* ; Machine Learning* ; beta-Lactamase Inhibitors*/beta-Lactamase Inhibitors*/beta-Lactamase Inhibitors*/pharmacology

  • Source: BMC research notes [BMC Res Notes] 2025 Mar 03; Vol. 18 (1), pp. 91. Date of Electronic Publication: 2025 Mar 03.Publisher: Biomed Central Country of Publication: England NLM ID: 101462768 Publication Model: Electronic Cited Medium: Internet ISSN: 1756-0500

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Academic Journal

Machine learning assisted classification RASAR modeling for the nephrotoxicity potential of a curated set of orally active drugs.

  • Authors : Banerjee A; Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700 032, India.; Roy K

Subjects: Machine Learning* ; Quantitative Structure-Activity Relationship*; Humans

  • Source: Scientific reports [Sci Rep] 2025 Jan 04; Vol. 15 (1), pp. 808. Date of Electronic Publication: 2025 Jan 04.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN:

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Academic Journal

Exploring entropy measures with topological indices on colorectal cancer drugs using curvilinear regression analysis and machine learning approaches.

  • Authors : Fazal M; Department of Mathematics, Lahore College for Women University, Lahore, Pakistan.; Kanwal S

Subjects: Machine Learning* ; Colorectal Neoplasms*/Colorectal Neoplasms*/Colorectal Neoplasms*/drug therapy ; Antineoplastic Agents*/Antineoplastic Agents*/Antineoplastic Agents*/chemistry

  • Source: PloS one [PLoS One] 2025 Jul 09; Vol. 20 (7), pp. e0327369. Date of Electronic Publication: 2025 Jul 09 (Print Publication: 2025).Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet

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Academic Journal

Combined interaction of fungicides binary mixtures: experimental study and machine learning-driven QSAR modeling.

  • Authors : Abbod M; Department of Plant Protection, Faculty of Agriculture, Al-Baath University, Homs, Syria. .; Mohammad A

Subjects: Fungicides, Industrial*/Fungicides, Industrial*/Fungicides, Industrial*/pharmacology ; Fungicides, Industrial*/Fungicides, Industrial*/Fungicides, Industrial*/chemistry ; Quantitative Structure-Activity Relationship*

  • Source: Scientific reports [Sci Rep] 2024 Jun 03; Vol. 14 (1), pp. 12700. Date of Electronic Publication: 2024 Jun 03.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN:

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Academic Journal

Drug repurposing targeting COVID-19 3CL protease using molecular docking and machine learning regression approaches.

  • Authors : Aqeel I; Biomedical Information Research Lab, Department of Computer & Information Sciences, Pakistan Institute of Engineering & Applied Sciences, Nilore, Islamabad, 45650, Pakistan. .; Majid A

Subjects: Drug Repositioning*/Drug Repositioning*/Drug Repositioning*/methods ; Molecular Docking Simulation* ; Machine Learning*

  • Source: Scientific reports [Sci Rep] 2025 May 28; Vol. 15 (1), pp. 18722. Date of Electronic Publication: 2025 May 28.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN:

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Academic Journal

Seeking Correlation Among Porin Permeabilities and Minimum Inhibitory Concentrations Through Machine Learning: A Promising Route to the Essential Molecular Descriptors.

  • Authors : Boi S; Department of Chemical and Geological Sciences, University of Cagliari, S.P. 8 km 0,700, I-09042 Monserrato, CA, Italy.; Puxeddu S

Subjects: Machine Learning* ; Porins*/Porins*/Porins*/metabolism ; Porins*/Porins*/Porins*/chemistry

  • Source: Molecules (Basel, Switzerland) [Molecules] 2025 Mar 09; Vol. 30 (6). Date of Electronic Publication: 2025 Mar 09.Publisher: MDPI Country of Publication: Switzerland NLM ID: 100964009 Publication Model: Electronic Cited Medium: Internet ISSN: 1420-3049

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Academic Journal

Machine Learning Tool for New Selective Serotonin and Serotonin-Norepinephrine Reuptake Inhibitors.

  • Authors : Łapińska N; Department of Pharmaceutical Technology and Biopharmaceutics, Jagiellonian University Medical College, 30-688 Kraków, Poland.; Szlęk J

Subjects: Machine Learning* ; Serotonin and Noradrenaline Reuptake Inhibitors*/Serotonin and Noradrenaline Reuptake Inhibitors*/Serotonin and Noradrenaline Reuptake Inhibitors*/chemistry ; Serotonin and Noradrenaline Reuptake Inhibitors*/Serotonin and Noradrenaline Reuptake Inhibitors*/Serotonin and Noradrenaline Reuptake Inhibitors*/pharmacology

  • Source: Molecules (Basel, Switzerland) [Molecules] 2025 Jan 31; Vol. 30 (3). Date of Electronic Publication: 2025 Jan 31.Publisher: MDPI Country of Publication: Switzerland NLM ID: 100964009 Publication Model: Electronic Cited Medium: Internet ISSN: 1420-3049

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Academic Journal

A python approach for prediction of physicochemical properties of anti-arrhythmia drugs using topological descriptors.

  • Authors : Qin H; Department of Rehabilitation Medicine, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China.; Rehman M

Subjects: Machine Learning* ; Anti-Arrhythmia Agents*/Anti-Arrhythmia Agents*/Anti-Arrhythmia Agents*/chemistry ; Anti-Arrhythmia Agents*/Anti-Arrhythmia Agents*/Anti-Arrhythmia Agents*/pharmacology

  • Source: Scientific reports [Sci Rep] 2025 Jan 11; Vol. 15 (1), pp. 1742. Date of Electronic Publication: 2025 Jan 11.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN:

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Academic Journal

Harnessing the Power of Machine Learning Guided Discovery of NLRP3 Inhibitors Towards the Effective Treatment of Rheumatoid Arthritis.

  • Authors : Ilyas S; Department of Herbal Pharmacology, College of Korean Medicine, Gachon University, 1342 Seongnamdae-ro, Sujeong-gu, Seongnam-si 13120, Republic of Korea.; Manan A

Subjects: Machine Learning* ; NLR Family, Pyrin Domain-Containing 3 Protein*/NLR Family, Pyrin Domain-Containing 3 Protein*/NLR Family, Pyrin Domain-Containing 3 Protein*/antagonists & inhibitors ; NLR Family, Pyrin Domain-Containing 3 Protein*/NLR Family, Pyrin Domain-Containing 3 Protein*/NLR Family, Pyrin Domain-Containing 3 Protein*/chemistry

  • Source: Cells [Cells] 2024 Dec 30; Vol. 14 (1). Date of Electronic Publication: 2024 Dec 30.Publisher: MDPI Country of Publication: Switzerland NLM ID: 101600052 Publication Model: Electronic Cited Medium: Internet ISSN: 2073-4409

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  • 1-10 of  1,184 results for ""Quantitative structure–activity relationship""